WMS This is a description of your Web Map Server. WFS WMS GEOSERVER

NONE NONE text/xml image/png application/atom+xml application/json;type=utfgrid application/pdf application/rss+xml application/vnd.google-earth.kml+xml application/vnd.google-earth.kml+xml;mode=networklink application/vnd.google-earth.kmz image/geotiff image/geotiff8 image/gif image/jpeg image/png; mode=8bit image/svg+xml image/tiff image/tiff8 image/vnd.jpeg-png image/vnd.jpeg-png8 text/html; subtype=openlayers text/html; subtype=openlayers2 text/html; subtype=openlayers3 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml; subtype=gml/3.1.1 text/html application/json XML INIMAGE BLANK JSON This is a description of your Web Map Server. EPSG:4326 EPSG:3785 EPSG:3857 EPSG:900913 EPSG:32647 EPSG:32736 CRS:84 -180.0 180.0 -90.0 90.0 geonode:GGDI No abstract provided GGDI WCS ImageMosaic EPSG:4326 CRS:84 40.5 52.0 -2.25 12.5 2003-01-01T00:00:00.000Z,2004-01-01T00:00:00.000Z,2005-01-01T00:00:00.000Z,2006-01-01T00:00:00.000Z,2007-01-01T00:00:00.000Z,2008-01-01T00:00:00.000Z,2009-01-01T00:00:00.000Z,2010-01-01T00:00:00.000Z,2011-01-01T00:00:00.000Z,2012-01-01T00:00:00.000Z,2013-01-01T00:00:00.000Z,2014-01-01T00:00:00.000Z,2015-01-01T00:00:00.000Z,2016-01-01T00:00:00.000Z,2017-01-01T00:00:00.000Z,2018-01-01T00:00:00.000Z,2019-01-01T00:00:00.000Z,2020-01-01T00:00:00.000Z,2021-01-01T00:00:00.000Z,2022-01-01T00:00:00.000Z,2023-01-01T00:00:00.000Z,2024-01-01T00:00:00.000Z other other other other text/xml other other geonode:GRE This dataset provides the annual mean groundwater storage anomaly balance for each year between 2003-2024 over Somalia, at a spatial resolution of 0.25° × 0.25°. Groundwater Storage Anomalies are estimated using observations from the GRACE and GRACE-FO satellite missions, which detect variations in the Earth’s gravitational field caused by changes in water mass. These gravity variations are used to derive Terrestrial Water Storage Anomalies (TWA). To isolate the groundwater component from TWA, the contributions of other hydrological components—such as snow water equivalent, soil moisture, and canopy water—are removed. These components are estimated using output data from three Global Land Data Assimilation System (GLDAS) land surface models. Three independent GWSA estimates are produced from the three GLDAS models and subsequently combined into an ensemble. The groundwater storage anomalies and the derived products were calculated on a monthly basis and then aggregated into annual values (mm/year). GRE WCS ImageMosaic EPSG:4326 CRS:84 40.5 52.0 -2.25 12.5 2003-01-01T00:00:00.000Z,2004-01-01T00:00:00.000Z,2005-01-01T00:00:00.000Z,2006-01-01T00:00:00.000Z,2007-01-01T00:00:00.000Z,2008-01-01T00:00:00.000Z,2009-01-01T00:00:00.000Z,2010-01-01T00:00:00.000Z,2011-01-01T00:00:00.000Z,2012-01-01T00:00:00.000Z,2013-01-01T00:00:00.000Z,2014-01-01T00:00:00.000Z,2015-01-01T00:00:00.000Z,2016-01-01T00:00:00.000Z,2017-01-01T00:00:00.000Z,2018-01-01T00:00:00.000Z,2019-01-01T00:00:00.000Z,2020-01-01T00:00:00.000Z,2021-01-01T00:00:00.000Z,2022-01-01T00:00:00.000Z,2023-01-01T00:00:00.000Z,2024-01-01T00:00:00.000Z other other other other other text/xml other other other other other text/xml other other geonode:NDWI_data No abstract provided NDWI_data WCS ImageMosaic EPSG:4326 CRS:84 40.98895860450441 50.850034972869636 -1.5896587267779054 11.128329739672632 2025-01-01T00:00:00.000Z,2025-02-01T00:00:00.000Z,2025-03-01T00:00:00.000Z,2025-04-01T00:00:00.000Z,2025-05-01T00:00:00.000Z,2025-06-01T00:00:00.000Z,2025-07-01T00:00:00.000Z,2025-08-01T00:00:00.000Z,2025-09-01T00:00:00.000Z other other other other text/xml other other other other other other text/xml other other geonode:SOM_FABDEM_ASPECT_4326 The aspect dataset derived from FABDEM v1.2 describes the compass direction that each terrain slope faces, calculated from the Forest and Buildings Removed Digital Elevation Model at approximately 30-metre spatial resolution. Aspect values indicate the direction of maximum slope and are commonly expressed in degrees measured clockwise from north (0–360°), with special values assigned to flat areas where aspect is undefined. By relying on FABDEM, which removes height biases from forests and buildings, this aspect layer more accurately reflects the true orientation of the land surface. Aspect is a critical terrain parameter influencing micro-climate, solar radiation exposure, soil moisture distribution, vegetation patterns, and agricultural productivity. This dataset is suitable for applications such as land suitability analysis, crop and rangeland assessment, ecological and habitat modelling, climate and drought studies, and environmental planning. When combined with slope and elevation data, the aspect layer provides valuable insights into terrain controls on environmental and hydrological processes. SOM_FABDEM_ASPECT_4326 WCS GeoTIFF EPSG:4326 CRS:84 39.89894138948103 52.182792484769394 -2.093455891025119 12.096925576554675 other other other other other other text/xml other other other other text/xml other other geonode:SOM_FABDEM_HILLSHADE-z2_V1_2_alb_m_4326 The hillshade dataset derived from FABDEM v1.2 is a shaded relief representation of the terrain generated from the Forest and Buildings Removed Digital Elevation Model at approximately 30-metre spatial resolution. Hillshade simulates the effect of illumination on the land surface by applying an artificial light source defined by a specific sun azimuth and altitude, enhancing the visual interpretation of topographic features. Using FABDEM as the input DEM ensures that the hillshade emphasizes true terrain morphology by minimizing distortions caused by vegetation and buildings. The resulting product provides a clear and realistic visualization of landforms such as ridges, valleys, plains, escarpments, and drainage patterns. Hillshade is primarily intended as a cartographic and visualization layer and is widely used as a base map to support the interpretation of other spatial datasets, including hydrology, land cover, infrastructure, and hazard maps. While not typically used for quantitative analysis, it plays a critical role in terrain understanding, map communication, and decision support. SOM_FABDEM_HILLSHADE-z2_V1_2_alb_m_4326 WCS GeoTIFF EPSG:4326 CRS:84 39.89894138948103 52.182792484769394 -2.093455891025119 12.096925576554675 other other other other text/xml other other other other other other text/xml other other geonode:SOM_FABDEM_SLOPE_DEG_4326 The slope dataset derived from FABDEM v1.2 represents the rate of change in elevation across the terrain, calculated from the Forest and Buildings Removed Digital Elevation Model at approximately 30-metre spatial resolution. By using FABDEM as the source elevation data, this slope product minimizes the influence of vegetation canopy and built-up structures, providing a more accurate representation of true ground surface gradients. Slope values are typically expressed in degrees (or percent rise, depending on processing settings) and are essential for a wide range of geospatial and environmental applications, including hydrological modelling, soil erosion and land degradation assessment, flood risk analysis, landslide susceptibility mapping, infrastructure planning, and agricultural land suitability analysis. This dataset supports terrain-based decision-making by highlighting areas of steep and gentle slopes, which influence surface runoff, infiltration, accessibility, and land use potential. The slope layer is intended for use alongside other FABDEM-derived products such as elevation, aspect, and hillshade. SOM_FABDEM_SLOPE_DEG_4326 WCS GeoTIFF EPSG:4326 CRS:84 39.89894138948103 52.182792484769394 -2.093455891025119 12.096925576554675 other other other other text/xml other other other other other other text/xml other other geonode:SOM_FABDEM_V1_2_alb_m_4326 The FABDEM (Forest And Buildings removed Copernicus DEM) Version 1.2 dataset is a global, high-resolution digital elevation model designed to reduce elevation biases caused by vegetation and built-up structures. FABDEM is derived from the Copernicus GLO-30 DEM and applies advanced correction methods to remove the influence of forest canopy height and buildings, resulting in a terrain surface that more closely represents the true bare-earth elevation. The dataset is provided at a spatial resolution of 1 arc-second (approximately 30 metres at the equator) and offers consistent global coverage. Version 1.2 represents an update to the earlier FABDEM V1.0 release, incorporating methodological refinements and corrections as detailed in the official changelog. In addition to raster elevation tiles, a GeoJSON index of FABDEM tiles is included to support spatial referencing and data management. FABDEM is particularly suitable for hydrological and hydraulic modelling, flood risk and inundation mapping, terrain and slope analysis, watershed delineation, flow accumulation modelling, and other environmental and geospatial analyses where vegetation and building artefacts in elevation data can introduce significant uncertainty. The dataset is published in support of the peer-reviewed study “A 30 m global map of elevation with forests and buildings removed” and is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0) license. For commercial use, permission must be obtained from the data providers. stract provided SOM_FABDEM_V1_2_alb_m_4326 WCS GeoTIFF EPSG:4326 CRS:84 39.89894138948103 52.18279248475839 -2.0934558910127965 12.096925576554288 other other other other text/xml other other other other other other text/xml other other geonode:Wapor_100_AETI No abstract provided AETI WCS ImageMosaic EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 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other other other other other other text/xml other other other other text/xml other other geonode:Wapor_100_Evaporation No abstract provided Evaporation WCS ImageMosaic EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 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other other other other text/xml other other other other other other text/xml other other geonode:Wapor_100_Interception No abstract provided Interception WCS ImageMosaic EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 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other other other other text/xml other other other other other other text/xml other other geonode:Wapor_100_NPP No abstract provided NPP WCS ImageMosaic EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 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other other other other text/xml other other other other other other text/xml other other geonode:Wapor_100_RSM No abstract provided RSM WCS ImageMosaic EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 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other other other other text/xml other other other other other other text/xml other other geonode:Wapor_100_Transpiration No abstract provided Transpiration WCS ImageMosaic EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2018-01-01T00:00:00.000Z,2018-02-01T00:00:00.000Z,2018-03-01T00:00:00.000Z,2018-04-01T00:00:00.000Z,2018-05-01T00:00:00.000Z,2018-06-01T00:00:00.000Z,2018-07-01T00:00:00.000Z,2018-08-01T00:00:00.000Z,2018-09-01T00:00:00.000Z,2018-10-01T00:00:00.000Z,2018-11-01T00:00:00.000Z,2018-12-01T00:00:00.000Z,2019-01-01T00:00:00.000Z,2019-02-01T00:00:00.000Z,2019-03-01T00:00:00.000Z,2019-04-01T00:00:00.000Z,2019-05-01T00:00:00.000Z,2019-06-01T00:00:00.000Z,2019-07-01T00:00:00.000Z,2019-08-01T00:00:00.000Z,2019-09-01T00:00:00.000Z,2019-10-01T00:00:00.000Z,2019-11-01T00:00:00.000Z,2019-12-01T00:00:00.000Z,2020-01-01T00:00:00.000Z,2020-02-01T00:00:00.000Z,2020-03-01T00:00:00.000Z,2020-04-01T00:00:00.000Z,2020-05-01T00:00:00.000Z,2020-06-01T00:00:00.000Z,2020-07-01T00:00:00.000Z,2020-08-01T00:00:00.000Z,2020-09-01T00:00:00.000Z,2020-10-01T00:00:00.000Z,2020-11-01T00:00:00.000Z,2020-12-01T00:00:00.000Z,2021-01-01T00:00:00.000Z,2021-02-01T00:00:00.000Z,2021-03-01T00:00:00.000Z,2021-04-01T00:00:00.000Z,2021-05-01T00:00:00.000Z,2021-06-01T00:00:00.000Z,2021-07-01T00:00:00.000Z,2021-08-01T00:00:00.000Z,2021-09-01T00:00:00.000Z,2021-10-01T00:00:00.000Z,2021-11-01T00:00:00.000Z,2021-12-01T00:00:00.000Z,2022-01-01T00:00:00.000Z,2022-02-01T00:00:00.000Z,2022-03-01T00:00:00.000Z,2022-04-01T00:00:00.000Z,2022-05-01T00:00:00.000Z,2022-06-01T00:00:00.000Z,2022-07-01T00:00:00.000Z,2022-08-01T00:00:00.000Z,2022-09-01T00:00:00.000Z,2022-10-01T00:00:00.000Z,2022-11-01T00:00:00.000Z,2022-12-01T00:00:00.000Z,2023-01-01T00:00:00.000Z,2023-02-01T00:00:00.000Z,2023-03-01T00:00:00.000Z,2023-04-01T00:00:00.000Z,2023-05-01T00:00:00.000Z,2023-06-01T00:00:00.000Z,2023-07-01T00:00:00.000Z,2023-08-01T00:00:00.000Z,2023-09-01T00:00:00.000Z,2023-10-01T00:00:00.000Z,2023-11-01T00:00:00.000Z,2023-12-01T00:00:00.000Z,2024-01-01T00:00:00.000Z,2024-02-01T00:00:00.000Z,2024-03-01T00:00:00.000Z,2024-04-01T00:00:00.000Z,2024-05-01T00:00:00.000Z,2024-06-01T00:00:00.000Z,2024-07-01T00:00:00.000Z,2024-08-01T00:00:00.000Z,2024-09-01T00:00:00.000Z,2024-10-01T00:00:00.000Z,2024-11-01T00:00:00.000Z,2024-12-01T00:00:00.000Z,2025-01-01T00:00:00.000Z,2025-02-01T00:00:00.000Z,2025-03-01T00:00:00.000Z,2025-04-01T00:00:00.000Z,2025-05-01T00:00:00.000Z,2025-06-01T00:00:00.000Z,2025-07-01T00:00:00.000Z,2025-08-01T00:00:00.000Z,2025-09-01T00:00:00.000Z,2025-10-01T00:00:00.000Z,2025-11-01T00:00:00.000Z,2025-12-01T00:00:00.000Z,2026-01-01T00:00:00.000Z,2026-02-01T00:00:00.000Z,2026-03-01T00:00:00.000Z,2026-04-01T00:00:00.000Z other other other other text/xml other other other other other other text/xml other other geonode:Wapor_20_AETI No abstract provided AETI WCS ImageMosaic EPSG:4326 CRS:84 45.22988700856089 45.75008750740512 2.309935320023185 3.2200603331105047 2025-01-01T00:00:00.000Z,2025-02-01T00:00:00.000Z,2025-03-01T00:00:00.000Z,2025-04-01T00:00:00.000Z,2025-05-01T00:00:00.000Z,2025-06-01T00:00:00.000Z,2025-07-01T00:00:00.000Z other other other other text/xml other other other other other other text/xml other other geonode:Wapor_20_Evaporation No abstract provided Evaporation WCS ImageMosaic EPSG:4326 CRS:84 45.22988700856089 45.75008750740512 2.309935320023185 3.2200603331105047 2025-01-01T00:00:00.000Z,2025-02-01T00:00:00.000Z,2025-03-01T00:00:00.000Z,2025-04-01T00:00:00.000Z,2025-05-01T00:00:00.000Z,2025-06-01T00:00:00.000Z,2025-07-01T00:00:00.000Z other other other other text/xml other other other other other other text/xml other other geonode:Wapor_20_Interception No abstract provided Interception WCS ImageMosaic EPSG:4326 CRS:84 45.22988700856089 45.75008750740512 2.309935320023185 3.2200603331105047 2025-01-01T00:00:00.000Z,2025-02-01T00:00:00.000Z,2025-03-01T00:00:00.000Z,2025-04-01T00:00:00.000Z,2025-05-01T00:00:00.000Z,2025-06-01T00:00:00.000Z,2025-07-01T00:00:00.000Z other other other other text/xml other other other other other other text/xml other other geonode:Wapor_20_NPP No abstract provided NPP WCS ImageMosaic EPSG:4326 CRS:84 45.22988700856089 45.75008750740512 2.309935320023185 3.2200603331105047 2025-01-01T00:00:00.000Z,2025-02-01T00:00:00.000Z,2025-03-01T00:00:00.000Z,2025-04-01T00:00:00.000Z,2025-05-01T00:00:00.000Z,2025-06-01T00:00:00.000Z,2025-07-01T00:00:00.000Z other other other other text/xml other other other other other other text/xml other other geonode:Wapor_20_RSM No abstract provided RSM WCS ImageMosaic EPSG:4326 CRS:84 45.22988700856089 45.75008750740512 2.309935320023185 3.2200603331105047 2025-01-01T00:00:00.000Z,2025-02-01T00:00:00.000Z,2025-03-01T00:00:00.000Z,2025-04-01T00:00:00.000Z,2025-05-01T00:00:00.000Z,2025-06-01T00:00:00.000Z,2025-07-01T00:00:00.000Z other other other other text/xml other other other other other other text/xml other other geonode:Wapor_20_Transpiration No abstract provided Transpiration WCS ImageMosaic EPSG:4326 CRS:84 45.22988700856089 45.75008750740512 2.309935320023185 3.2200603331105047 2025-01-01T00:00:00.000Z,2025-02-01T00:00:00.000Z,2025-03-01T00:00:00.000Z,2025-04-01T00:00:00.000Z,2025-05-01T00:00:00.000Z,2025-06-01T00:00:00.000Z,2025-07-01T00:00:00.000Z other other other other text/xml other other other other other other text/xml other other geonode:afgooye__darte_palm_suitability_map_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture SWALIM afgooye__darte_palm_suitability_map_v1 Date Palm somalia afgooye Climate FAO EPSG:32638 CRS:84 44.646415213680655 45.166210734033186 1.7254052015155181 2.1889063752801454 other other other other text/xml other other geonode:afgooye__forage_suitability_map_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features pasture Soil agriculture rangeland forage SWALIM afgooye__forage_suitability_map_v1 afgooye somalia Climate FAO EPSG:32638 CRS:84 44.646415213680655 45.166210734033186 1.7254052015155181 2.1889063752801454 other other other other text/xml other other geonode:afgooye__maize_suitability_map_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability afgooye__maize_suitability_map_v1 features Soil agriculture SWALIM afgooye somalia maize Climate FAO EPSG:32638 CRS:84 44.646415213680655 45.166210734033186 1.7254052015155181 2.1889063752801454 other other other other text/xml other other geonode:afgooye__mango_suitability_map_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features afgooye__mango_suitability_map_v1 Soil agriculture Mango SWALIM afgooye somalia Climate FAO EPSG:32638 CRS:84 44.646415213680655 45.166210734033186 1.7254052015155181 2.1889063752801454 other other other other text/xml other other geonode:afgooye__onion_suitability_map_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture Onion SWALIM afgooye__onion_suitability_map_v1 Climate afgooye somalia FAO EPSG:32638 CRS:84 44.646415213680655 45.166210734033186 1.7254052015155181 2.1889063752801454 other other other other text/xml other other geonode:afgooye_banana_suitability_map_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture banana SWALIM afgooye afgooye_banana_suitability_map_v1 somalia Climate FAO EPSG:32638 CRS:84 44.646415213680655 45.166210734033186 1.7254052015155181 2.1889063752801454 other other other other text/xml other other geonode:afgooye_citrus_suitability_map_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture SWALIM afgooye somalia afgooye_citrus_suitability_map_v1 Climate Citrus FAO EPSG:32638 CRS:84 44.646415213680655 45.166210734033186 1.7254052015155181 2.1889063752801454 other other other other text/xml other other geonode:afgooye_final_soil_map_utm38n This dataset represents the semi-detailed soil maps of selected riverine Areas of Interest (AOIs) in southern and central Somalia, including Luuq, Belet Weyne, Afgooye, Jowhar, and Kismaayo. The maps were developed through integrated soil survey methodologies combining field observations, laboratory analysis, and geospatial interpretation. The dataset provides spatial information on soil distribution, land units, and key soil physical and chemical properties. It supports agricultural planning, irrigation development, land resource management, and climate-resilient interventions in the Shabelle and Juba river basins. The mapping is part of a broader SWALIM initiative aimed at improving soil knowledge at semi-detailed scale for sustainable land use planning. Methodology The soil maps for all AOIs were developed using a standardized methodology based on FAO soil survey guidelines and adapted to the Somali landscape context. 1. Land Unit Delineation (Photointerpretation) Preliminary land units were delineated using satellite imagery and landscape interpretation based on: geomorphology landforms surface characteristics 2. Field Soil Survey Field campaigns were conducted to collect soil profile (pedon) data, including: horizon description soil depth texture structure drainage conditions 3. Laboratory Analysis Soil samples were analyzed to determine key physical and chemical properties, including: Soil texture (sand, silt, clay) Bulk density Soil pH Electrical conductivity (salinity) Organic carbon and organic matter Total nitrogen Calcium carbonate Cation Exchange Capacity (CEC) Exchangeable bases (Ca, Mg, K, Na) Available water capacity (AWC) 4. Soil Classification and Mapping Soils were grouped into Land Units Classified using WRB (World Reference Base for Soil Resources) Mapped at semi-detailed scale (1:25,000) 5. Soil–Landscape Database Development A comprehensive dataset was developed integrating: Soil properties Climate characteristics Physiographic and landscape attributes This database supports further applications such as land suitability analysis. Spatial Resolution / Scale Scale: 1:25,000 (semi-detailed soil mapping) Geographic Coverage Riverine agricultural areas in Somalia: Luuq Belet Weyne Afgooye Jowhar Kismaayo Located along the Juba and Shabelle river systems Soil Characteristics Included Physical Properties Texture Soil depth Structure Drainage Permeability Available Water Capacity (AWC) Rooting depth Chemical Properties Soil pH Salinity (EC) Organic carbon Organic matter Total nitrogen Calcium carbonate Cation Exchange Capacity (CEC) Exchangeable cations (Ca, Mg, K, Na) Alkalinity (ESP) Landscape Attributes Flooding regimes Alluvial plains and terraces Soil moisture conditions Topography (slope, elevation) afgooye_final_soil_map_utm38n features Riverine Agriculture somalia shabelle SWALIM Land Units afgooye Soil Survey Soil Map juba Soil Properties WRB Classification EPSG:32638 CRS:84 44.646415213680655 45.166210734033186 1.7254052015155181 2.1889063752801454 other other other other text/xml other other geonode:afgooye_potentialhigherground_forfloodevacuat Datasets used for the analysis are :- Flood Extent, Elevation, Slope, Topographic Wetness Index (TWI),Drainage Density, Strategic Boreholes, Settlements, Land Cover and Roads\r\nBased on a predefined criteria, each of these datasets were first clipped to areas outside the flood extent but within a maximum distance of 10 Km from the flood extent boundary. The outputs were then reclassified into two classes namely; Suitable and Not Suitable. Using an iterative approach, each of these datasets was used to assign a weight to the suitability of a site. These weights are indicated on table 2 below. Thereafter, a multi-criteria evaluation weighted overlay operation was undertaken to determine the potential areas for evacuation sites. An area was then computed for the potential sites and their distance from the flood extent established. The output was then post – processed to remove invalid geometries and each site was ranked based on the distance from the flood prone area. Sites that are closer in distance were deemed to be most suitable hence a higher rank. The final layer was then visually checked based on the density of the topographic Wetness Index (TWI) which is based on runoffs during floods. Areas with dense TWI were eliminated to remain with only continuous areas. features afgooye_potentialhigherground_forfloodevacuat EPSG:4326 CRS:84 44.71230399386069 45.342860406402956 1.958741228294232 2.261656408500807 other other other other text/xml other other geonode:afgooye_sesame_suitability_map_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability afgooye_sesame_suitability_map_v1 features Soil agriculture SWALIM afgooye somalia sesame Climate FAO EPSG:32638 CRS:84 44.646415213680655 45.166210734033186 1.7254052015155181 2.1889063752801454 other other other other text/xml other other geonode:afgooye_sorghum_suitability_map_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture afgooye_sorghum_suitability_map_v1 SWALIM afgooye somalia Climate sorghum FAO EPSG:32638 CRS:84 44.646415213680655 45.166210734033186 1.7254052015155181 2.1889063752801454 other other other other text/xml other other geonode:afgooye_tomato_suitability_map_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture afgooye_tomato_suitability_map_v1 Climate SWALIM afgooye somalia tomato FAO EPSG:32638 CRS:84 44.646415213680655 45.166210734033186 1.7254052015155181 2.1889063752801454 other other other other text/xml other other geonode:afgooye_watermelon_suitability_map_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture water melon SWALIM afgooye somalia afgooye_watermelon_suitability_map_v1 Climate FAO EPSG:32638 CRS:84 44.646415213680655 45.166210734033186 1.7254052015155181 2.1889063752801454 other other other other text/xml other other geonode:airfields_unsos This layer contains data about airfields locations in Somalia. The layer is updated by the United Nations Support Office in Somalia (UNSOS) features airfields_unsos EPSG:4326 CRS:84 41.02911118700007 51.32642710300007 -0.389332999999965 11.947440000000029 other other other other text/xml other other geonode:all_watersources No abstract provided features all_watersources EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 other other other other text/xml other other other other other text/xml other other other geonode:aquifer_of_somaliland_puntland features aquifer_of_somaliland_puntland EPSG:4326 CRS:84 42.660856684000066 51.40984340000006 6.728666892000092 11.981461138000043 other other other other text/xml other other geonode:baardheere_potential_highergroundssuitablefor Datasets used for the analysis are :- Flood Extent, Elevation, Slope, Topographic Wetness Index (TWI),Drainage Density, Strategic Boreholes, Settlements, Land Cover and Roads\r\nBased on a predefined criteria, each of these datasets were first clipped to areas outside the flood extent but within a maximum distance of 10 Km from the flood extent boundary. The outputs were then reclassified into two classes namely; Suitable and Not Suitable. Using an iterative approach, each of these datasets was used to assign a weight to the suitability of a site. These weights are indicated on table 2 below. Thereafter, a multi-criteria evaluation weighted overlay operation was undertaken to determine the potential areas for evacuation sites. An area was then computed for the potential sites and their distance from the flood extent established. \r\nThe output was then post – processed to remove invalid geometries and each site was ranked based on the distance from the flood prone area. Sites that are closer in distance were deemed to be most suitable hence a higher rank. The final layer was then visually checked based on the density of the topographic Wetness Index (TWI) which is based on runoffs during floods. Areas with dense TWI were eliminated to remain with only continuous areas. floods grounds evacuation higher somalia baardheere_potential_highergroundssuitablefor shabelle features river juba EPSG:32638 CRS:84 42.12119319335759 42.42570436324285 1.9534163325692215 2.57992951358917 other other other other text/xml other other geonode:belet_weine_25k_final_lu This dataset represents the semi-detailed soil maps of selected riverine Areas of Interest (AOIs) in southern and central Somalia, including Luuq, Belet Weyne, Afgooye, Jowhar, and Kismaayo. The maps were developed through integrated soil survey methodologies combining field observations, laboratory analysis, and geospatial interpretation. The dataset provides spatial information on soil distribution, land units, and key soil physical and chemical properties. It supports agricultural planning, irrigation development, land resource management, and climate-resilient interventions in the Shabelle and Juba river basins. The mapping is part of a broader SWALIM initiative aimed at improving soil knowledge at semi-detailed scale for sustainable land use planning. Methodology The soil maps for all AOIs were developed using a standardized methodology based on FAO soil survey guidelines and adapted to the Somali landscape context. 1. Land Unit Delineation (Photointerpretation) Preliminary land units were delineated using satellite imagery and landscape interpretation based on: geomorphology landforms surface characteristics 2. Field Soil Survey Field campaigns were conducted to collect soil profile (pedon) data, including: horizon description soil depth texture structure drainage conditions 3. Laboratory Analysis Soil samples were analyzed to determine key physical and chemical properties, including: Soil texture (sand, silt, clay) Bulk density Soil pH Electrical conductivity (salinity) Organic carbon and organic matter Total nitrogen Calcium carbonate Cation Exchange Capacity (CEC) Exchangeable bases (Ca, Mg, K, Na) Available water capacity (AWC) 4. Soil Classification and Mapping Soils were grouped into Land Units Classified using WRB (World Reference Base for Soil Resources) Mapped at semi-detailed scale (1:25,000) 5. Soil–Landscape Database Development A comprehensive dataset was developed integrating: Soil properties Climate characteristics Physiographic and landscape attributes This database supports further applications such as land suitability analysis. Spatial Resolution / Scale Scale: 1:25,000 (semi-detailed soil mapping) Geographic Coverage Riverine agricultural areas in Somalia: Luuq Belet Weyne Afgooye Jowhar Kismaayo Located along the Juba and Shabelle river systems Soil Characteristics Included Physical Properties Texture Soil depth Structure Drainage Permeability Available Water Capacity (AWC) Rooting depth Chemical Properties Soil pH Salinity (EC) Organic carbon Organic matter Total nitrogen Calcium carbonate Cation Exchange Capacity (CEC) Exchangeable cations (Ca, Mg, K, Na) Alkalinity (ESP) Landscape Attributes Flooding regimes Alluvial plains and terraces Soil moisture conditions Topography (slope, elevation) belet weyne Soil Map belet_weine_25k_final_lu features Riverine Agriculture shabelle SWALIM Land Units Soil Properties Soil Survey somalia juba WRB Classification EPSG:32638 CRS:84 45.00259092982955 45.28620156080992 4.598546930118176 5.007539076935439 other other other other text/xml other other geonode:belet_weyne_banana_suitability_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) belet weyne land suitability crop suitability features Soil agriculture belet_weyne_banana_suitability_v1 banana SWALIM somalia Climate FAO EPSG:32638 CRS:84 45.00259092982955 45.28620156080992 4.598546930118176 5.007539076935439 other other other other other other text/xml geonode:belet_weyne_citrus_suitability_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) belet weyne land suitability crop suitability features belet_weyne_citrus_suitability_v1 Soil agriculture SWALIM somalia Climate Citrus FAO EPSG:32638 CRS:84 45.00259092982955 45.28620156080992 4.598546930118176 5.007539076935439 other other other other text/xml other other geonode:belet_weyne_forage_pasture_suitability_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) belet weyne land suitability crop suitability features pasture Soil agriculture forage belet_weyne_forage_pasture_suitability_v1 SWALIM somalia Climate FAO EPSG:32638 CRS:84 45.00259092982955 45.28620156080992 4.598546930118176 5.007539076935439 text/xml other other other other other other geonode:belet_weyne_maize_suitability_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) belet weyne land suitability crop suitability features Soil agriculture SWALIM belet_weyne_maize_suitability_v1 somalia maize Climate FAO EPSG:32638 CRS:84 45.00259092982955 45.28620156080992 4.598546930118176 5.007539076935439 other other other other text/xml other other geonode:belet_weyne_mango_suitability_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) belet weyne land suitability crop suitability features Soil belet_weyne_mango_suitability_v1 agriculture Mango SWALIM somalia Climate FAO EPSG:32638 CRS:84 45.00259092982955 45.28620156080992 4.598546930118176 5.007539076935439 other other other other text/xml other other geonode:belet_weyne_onion_suitability_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) belet weyne land suitability crop suitability features Soil agriculture Onion belet_weyne_onion_suitability_v1 SWALIM somalia Climate FAO EPSG:32638 CRS:84 45.00259092982955 45.28620156080992 4.598546930118176 5.007539076935439 other text/xml other other other other other geonode:belet_weyne_rice_suitability_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) belet weyne land suitability crop suitability rice features Soil agriculture belet_weyne_rice_suitability_v1 SWALIM somalia Climate FAO EPSG:32638 CRS:84 45.00259092982955 45.28620156080992 4.598546930118176 5.007539076935439 other other other other text/xml other other geonode:belet_weyne_sesame_suitability_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) belet weyne land suitability crop suitability features Soil agriculture FAO SWALIM somalia sesame Climate belet_weyne_sesame_suitability_v1 EPSG:32638 CRS:84 45.00259092982955 45.28620156080992 4.598546930118176 5.007539076935439 other other other other text/xml other other geonode:belet_weyne_sorghum_suitability_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) belet weyne land suitability crop suitability features rainfed agriculture SoilGrids belet_weyne_sorghum_suitability_v1 SWALIM soil suitability somalia sorghum EPSG:32638 CRS:84 45.00259092982955 45.28620156080992 4.598546930118176 5.007539076935439 other other other other text/xml other other geonode:belet_weyne_tomato_suitability_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) belet weyne land suitability crop suitability features Soil agriculture SWALIM Climate somalia tomato FAO belet_weyne_tomato_suitability_v1 EPSG:32638 CRS:84 45.00259092982955 45.28620156080992 4.598546930118176 5.007539076935439 other other other other text/xml other other geonode:belet_weyne_watermelon_suitability_v1 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) beletweyne land suitability crop suitability features Soil agriculture water melon SWALIM somalia belet_weyne_watermelon_suitability_v1 Climate FAO EPSG:32638 CRS:84 45.00259092982955 45.28620156080992 4.598546930118176 5.007539076935439 other other other other text/xml other other geonode:beletweyne_potential_suitable_higher_grounds_0_rlngr0f Datasets used for the analysis are :- Flood Extent, Elevation, Slope, Topographic Wetness Index (TWI),Drainage Density, Strategic Boreholes, Settlements, Land Cover and Roads. Based on a predefined criteria, each of these datasets were first clipped to areas outside the flood extent but within a maximum distance of 10 Km from the flood extent boundary. The outputs were then reclassified into two classes namely; Suitable and Not Suitable. Using an iterative approach, each of these datasets was used to assign a weight to the suitability of a site. These weights are indicated on table 2 below. Thereafter, a multi-criteria evaluation weighted overlay operation was undertaken to determine the potential areas for evacuation sites. An area was then computed for the potential sites and their distance from the flood extent established. The output was then post – processed to remove invalid geometries and each site was ranked based on the distance from the flood prone area. Sites that are closer in distance were deemed to be most suitable hence a higher rank. The final layer was then visually checked based on the density of the topographic Wetness Index (TWI) which is based on runoffs during floods. Areas with dense TWI were eliminated to remain with only continuous areas. evacuation beletweyne_potential_suitable_higher_grounds_0_rlngr0f features EPSG:4326 CRS:84 44.845503797016534 45.41536693283746 4.340550691572218 5.065590305508806 other other other other text/xml other other geonode:canal_irrigation_sample features canal_irrigation_sample EPSG:4326 CRS:84 42.011425 45.5976 -0.232069 4.892604 other other other other text/xml other other geonode:ch_2011_20130 The dataset shows the dynamics of charcoal production in Somalia from 2011 to 2013.Multi-temporal dataset of very high-resolution remote sensing images such as WorldView-1, 2 and 3 were used to map kiln locations in the study area. The acquisition dates of the images range from 2011 to 2013. Charcoal production sites can be seen on satellite images as dark round/ almost round patches. Many small tracks/ paths are a common feature at these sites. They are used for access and transport. The average radius of the kilns is 3.3m but some are as big as 6m in radius.Multi temporal analysis of vhr images reveals a tremendous increase of charcoal sites over the years. features ch_2011_20130 EPSG:4326 CRS:84 41.17737620500003 43.152011532000074 -1.295922628999961 1.370093332000067 other other other other text/xml other other geonode:ch_2014_20160 The dataset shows the dynamics of charcoal production in Somalia from 2014 to 2016.Multi-temporal dataset of very high-resolution remote sensing images such as WorldView-1, 2 and 3 were used to map kiln locations in the study area. The acquisition dates of the images range from 2014 to 2016. Charcoal production sites can be seen on satellite images as dark round/ almost round patches. Many small tracks/ paths are a common feature at these sites. They are used for access and transport. The average radius of the kilns is 3.3m but some are as big as 6m in radius.Multi temporal analysis of vhr images reveals a tremendous increase of charcoal sites over the years. features ch_2014_20160 EPSG:4326 CRS:84 41.19563669400003 43.16099484100005 -1.575587621999944 1.207521358000065 other other other other text/xml other other geonode:climate_zones_in_somalia Data on climate from pre-war meteorological stations (1961-1990) Data on topography by NASA - SRTM, 2000.The climate of Somalia is classified into four general climatic zones, Desert, Very arid, Semi arid and Humid - Semi arid. features climate_zones_in_somalia EPSG:4326 CRS:84 40.989505766000036 51.414127345000054 -1.66006135899994 11.985942840000064 other other other other text/xml other other geonode:dollow_potentialsuitablehigherground_evacuati Datasets used for the analysis are :- Flood Extent, Elevation, Slope, Topographic Wetness Index (TWI),Drainage Density, Strategic Boreholes, Settlements, Land Cover and Roads\r\nBased on a predefined criteria, each of these datasets were first clipped to areas outside the flood extent but within a maximum distance of 10 Km from the flood extent boundary. The outputs were then reclassified into two classes namely; Suitable and Not Suitable. Using an iterative approach, each of these datasets was used to assign a weight to the suitability of a site. These weights are indicated on table 2 below. Thereafter, a multi-criteria evaluation weighted overlay operation was undertaken to determine the potential areas for evacuation sites. An area was then computed for the potential sites and their distance from the flood extent established. \r\nThe output was then post – processed to remove invalid geometries and each site was ranked based on the distance from the flood prone area. Sites that are closer in distance were deemed to be most suitable hence a higher rank. The final layer was then visually checked based on the density of the topographic Wetness Index (TWI) which is based on runoffs during floods. Areas with dense TWI were eliminated to remain with only continuous areas.t provided floods grounds evacuation higher somalia shabelle features dollow_potentialsuitablehigherground_evacuati potential river juba EPSG:4326 CRS:84 41.86316236027364 42.341364946848856 3.898650628720187 4.179330379725302 other other other other text/xml other other geonode:floods_gu_2025 This data was produced through visual interpretation of Sentinel 1 and Sentinel 2 images.The actual flood extent may be different than the actual due to cloud cover on analysis images that hindered assessment in some areas and limitations of radar to detect flooding within urban areas features floods_gu_2025 EPSG:4326 CRS:84 45.411623311211365 45.59944702148437 2.429279697911902 2.876478139269138 other other other other text/xml other other geonode:forestsuitability_tamarindusindica_north The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species Tamarindus Indicain selected areas innorthern part of Somalia (Garbiley and Boroma areas in Somaliland). features forestsuitability_tamarindusindica_north EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:gcf_analysis_subwatersheds_selectedlandscapes_07112025_updated features gcf_analysis_subwatersheds_selectedlandscapes_07112025_updated EPSG:4326 CRS:84 42.157037968445024 50.05080386458849 -0.610932647735064 9.672775640927147 other other other other text/xml other other geonode:gdawater_groundwaterresourcesestimation_meanannualgroundwaters The mean storage anomaly balance over the study period (2003-2024). The results indicate that the overall balance is nearly closed, with maximum deviations staying within ±8 mm over the 20-year period. The results show a north-south gradient, with predominantly negative balance values in the northern regions, and increasingly positive values towards the south. This pattern coincides with that of the mean annual precipitation, suggesting that groundwater dynamics are closely influenced by rainfall patterns. The northeastern area exhibits the most significant negative balance reaching values near -8 mm/year over the study period (2003-2024). However, in the northern part of the country, certain areas show a significant positive balance in groundwater storage (close to 8 mm/year), coinciding with the Karkaar Mountains. Running parallel to the Gulf of Aden coast, these mountains rise to elevations of up to 2,460 meters at Mount Shimbiris, the highest peak in the country. They receive higher precipitation than the surrounding arid lowlands, contributing to localized increases in groundwater storage. In contrast, the central and southern regions of the country show a widespread increase in groundwater storage, consistent with the higher annual rainfall observed in these areas. This pattern is especially evident along the lower courses of the Juba and Shabelle rivers. The adjacent alluvial plains, composed of permeable sediments, allow substantial infiltration during high-flow periods. In the Mogadishu area, the wetlands fed by the Shabelle River play a crucial role in recharging the aquifers. gdawater_groundwaterresourcesestimation_meanannualgroundwaters WCS GeoTIFF EPSG:4326 CRS:84 40.5 52.0 -2.25 12.5 other other other other text/xml other other geonode:gdawater_groundwaterresourcesestimation_meanannualnegativegrou Average groundwater anomalies were also calculated for both positive and negative anomalies. Both sets of results show the same spatial distribution pattern, with the highest and lowest anomalies values located along the Al Madow Mountain range (in the Karkaar Mountains, north) and the Jubba and Shabelle rivers lower course (south). In the former, this spatial coincidence can be explained by higher precipitation values, whereas in the latter it is attributed to a strong interaction between surface and subsurface water systems. gdawater_groundwaterresourcesestimation_meanannualnegativegrou WCS GeoTIFF EPSG:4326 CRS:84 40.5 52.0 -2.25 12.5 other other other other text/xml other other geonode:gdawater_groundwaterresourcesestimation_meanannualpositivegrou Average groundwater anomalies were also calculated for both positive and negative anomalies. Both sets of results show the same spatial distribution pattern, with the highest and lowest anomalies values located along the Al Madow Mountain range (in the Karkaar Mountains, north) and the Jubba and Shabelle rivers lower course (south). In the former, this spatial coincidence can be explained by higher precipitation values, whereas in the latter it is attributed to a strong interaction between surface and subsurface water systems. gdawater_groundwaterresourcesestimation_meanannualpositivegrou WCS GeoTIFF EPSG:4326 CRS:84 40.5 52.0 -2.25 12.5 other other other other text/xml other other geonode:gdawater_groundwaterresourcesestimation_meanseason5efb14924de3 Mean seasonal distribution of groundwater storage balance across Somalia for the period 2003–2024 for Jun-Aug. The seasonal evolution of the groundwater storage balance closely follows the country's climatic patterns. During the dry seasons (Jilaal and Xagaa), the groundwater storage balance is generally negative, particularly in the central and southern regions. This is consistent with the low precipitation observed in the same months. Notably, the lower courses of the Shabelle and Jubba rivers exhibit strong negative balances between June and August, which may suggest that groundwater is sustaining baseflow during the dry period. In contrast, the Gu season leads to significant improvements in groundwater storage balance across southern and central Somalia, where the southwest monsoon brings the heaviest rainfall. However, the northeastern coast maintains a neutral to slightly negative balance, due to relatively lower precipitation. During Deyr, groundwater storage balance starts to recover in the central and southern areas, likely driven by river recharge and increased infiltration from the rainfall of this shorter rainy season. gdawater_groundwaterresourcesestimation_meanseason5efb14924de3 WCS GeoTIFF EPSG:4326 CRS:84 40.5 52.0 -2.25 12.5 other other other other text/xml other other geonode:gdawater_groundwaterresourcesestimation_meanseason78bf00bebc7b Mean seasonal distribution of groundwater storage balance across Somalia for the period 2003–2024 for Mar-May. The seasonal evolution of the groundwater storage balance closely follows the country's climatic patterns. During the dry seasons (Jilaal and Xagaa), the groundwater storage balance is generally negative, particularly in the central and southern regions. This is consistent with the low precipitation observed in the same months. Notably, the lower courses of the Shabelle and Jubba rivers exhibit strong negative balances between June and August, which may suggest that groundwater is sustaining baseflow during the dry period. In contrast, the Gu season leads to significant improvements in groundwater storage balance across southern and central Somalia, where the southwest monsoon brings the heaviest rainfall. However, the northeastern coast maintains a neutral to slightly negative balance, due to relatively lower precipitation. During Deyr, groundwater storage balance starts to recover in the central and southern areas, likely driven by river recharge and increased infiltration from the rainfall of this shorter rainy season. gdawater_groundwaterresourcesestimation_meanseason78bf00bebc7b WCS GeoTIFF EPSG:4326 CRS:84 40.5 52.0 -2.25 12.5 other other other other text/xml other other geonode:gdawater_groundwaterresourcesestimation_meanseasonalgroundwate Mean seasonal distribution of groundwater storage balance across Somalia for the period 2003–2024 for Dec-Feb. The seasonal evolution of the groundwater storage balance closely follows the country's climatic patterns. During the dry seasons (Jilaal and Xagaa), the groundwater storage balance is generally negative, particularly in the central and southern regions. This is consistent with the low precipitation observed in the same months. Notably, the lower courses of the Shabelle and Jubba rivers exhibit strong negative balances between June and August, which may suggest that groundwater is sustaining baseflow during the dry period. In contrast, the Gu season leads to significant improvements in groundwater storage balance across southern and central Somalia, where the southwest monsoon brings the heaviest rainfall. However, the northeastern coast maintains a neutral to slightly negative balance, due to relatively lower precipitation. During Deyr, groundwater storage balance starts to recover in the central and southern areas, likely driven by river recharge and increased infiltration from the rainfall of this shorter rainy season. gdawater_groundwaterresourcesestimation_meanseasonalgroundwate WCS GeoTIFF EPSG:4326 CRS:84 40.5 52.0 -2.25 12.5 other other other other text/xml other other geonode:gdawater_groundwaterresourcesestimation_meanseasond8846e9f8d49 Mean seasonal distribution of groundwater storage balance across Somalia for the period 2003–2024 for Sep-Nov. The seasonal evolution of the groundwater storage balance closely follows the country's climatic patterns. During the dry seasons (Jilaal and Xagaa), the groundwater storage balance is generally negative, particularly in the central and southern regions. This is consistent with the low precipitation observed in the same months. Notably, the lower courses of the Shabelle and Jubba rivers exhibit strong negative balances between June and August, which may suggest that groundwater is sustaining baseflow during the dry period. In contrast, the Gu season leads to significant improvements in groundwater storage balance across southern and central Somalia, where the southwest monsoon brings the heaviest rainfall. However, the northeastern coast maintains a neutral to slightly negative balance, due to relatively lower precipitation. During Deyr, groundwater storage balance starts to recover in the central and southern areas, likely driven by river recharge and increased infiltration from the rainfall of this shorter rainy season. gdawater_groundwaterresourcesestimation_meanseasond8846e9f8d49 WCS GeoTIFF EPSG:4326 CRS:84 40.5 52.0 -2.25 12.5 other other other other text/xml other other geonode:gedo_acquifers This dataset represents the hydrogeological assessment of Gedo Region, Somalia, prepared under the FAO SWALIM Programme. The main objective of the study was to improve water supply availability by identifying sustainable groundwater resources through evaluation of existing hydrogeological data and remote sensing applications. Groundwater is the sole water source for much of the region, apart from the Juba River. Methodology Summary The study compiled and analysed geological, geophysical, hydrological, and hydrogeological information from previous surveys, SWIMS database, and NGO reports. Remote sensing analysis of LANDSAT imagery was used to assess geomorphology, hydrography, fault patterns, and lithostratigraphic boundaries. GIS tools supported aquifer classification, groundwater flow modelling, hydrochemistry evaluation, and map production. Key activities included: Classification of aquifers and aquicludes, evaluation of recharge, flow directions, and discharge. Hydrochemistry assessment and review of water quality data. Development of a regional hydrogeological map at 1:500,000 scale showing aquifer systems, groundwater flow, major water points, and hydrographic networks. Selection and detailed mapping of three Areas of Interest (AoIs) at 1:200,000 scale, including groundwater resource assessment and water demand estimation. Identification of priority zones for groundwater exploration and drilling. Proposal for an initial groundwater monitoring network and recommendations for sustainable water use. Coverage Geographic extent: Gedo Region, Somalia Scale: Regional (1:500,000); local AoIs (1:200,000) Thematic Content Aquifer systems (intergranular, fissured-karstic, complex) Aquicludes River basins and hydrographic networks Groundwater flow directions Water points (boreholes, shallow wells) Hydrochemistry information Areas of Interest for detailed assessment Data Sources SWIMS Database (FAO SWALIM) Previous hydrogeological and geophysical surveys Remote sensing analysis (LANDSAT imagery) Adaptation of Abbate et al. (1994) regional geological map gedo_acquifers features EPSG:32638 CRS:84 40.98121671328216 43.144298889537644 1.2326622410209658 4.307583854094412 other other other other text/xml other other geonode:geology_abbate_et_al_1993 General geological map of Somalia features geology_abbate_et_al_1993 EPSG:4326 CRS:84 40.99123540700003 51.409296391000055 -1.714700773999937 11.981956052000044 other other other other text/xml other other geonode:grazesuitabilitycamels_north The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for animal grazing (Cattle) in selected areas innorthern part of Somalia (Garbiley and Boroma areas in Somaliland). features grazesuitabilitycamels_north EPSG:4326 CRS:84 43.01092679300007 44.46210394500008 9.166513131000045 10.689748208000026 other other other other text/xml other other geonode:grazesuitabilitycattle_n The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for animal grazing (Cattle) in selected areas innorthern part of Somalia (Garbiley and Boroma areas in Somaliland). features grazesuitabilitycattle_n EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:grazesuitabilitycattle_south The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for animal grazing (Cattle) in selected areas insouthern part of Somalia (Juba and Shabelle riverine areas). features grazesuitabilitycattle_south EPSG:4326 CRS:84 41.89169460000005 46.15003254800007 -0.266810086999953 5.060045358000025 other other other other text/xml other other geonode:grazesuitabilitygoats_n The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for animal grazing (Goats) in selected areas in northern part of Somalia (Garbiley and Boroma areas in Somaliland). features grazesuitabilitygoats_n EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other other text/xml other geonode:grazesuitabilitysheep_north The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for animal grazing (Sheep) in selected areas in northern part of Somalia (Garbiley and Boroma areas in Somaliland). features grazesuitabilitysheep_north EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:growing_period_length Somalia Crops Growing Length Periods based on the two rainy seasons in Somalia GU and Deyr. features growing_period_length EPSG:4326 CRS:84 40.98994827100006 51.41412734900007 -1.649199515999953 11.985942840000064 other other other other text/xml other other geonode:harbors_unsos The source of this data is United Nations Support Office in Somalia (UNSOS) features harbors_unsos EPSG:4326 CRS:84 42.54626100000007 49.81773000000004 -0.360289999999964 11.283660000000054 other other other other text/xml other other geonode:harmonised_settlement_14112022 OCHA Somalia Harmonised settlement 14 11 2022 somalia population harmonised_settlement_14112022 features settlements EPSG:4326 CRS:84 40.99208 51.28266 -1.63754 11.96039 other other other other text/xml other other geonode:horn_of_africa_roads_unsos The layer contains roads data for the Horn of Africa. United Nations Support Office in Somalia (UNSOS) has collected this data from sources such as ICPAC_IGAD_UNOSAT, then UNSOS has made some updates. features horn_of_africa_roads_unsos EPSG:4326 CRS:84 34.09901703700007 51.36650595700007 -1.65470763899998 11.964393999000038 other other other other text/xml other other geonode:hydromet_stations_july_2021 There are only two perennial rivers in Somalia; the Juba and the Shabelle. Due to the arid and semi-arid nature of the northern parts of the country, the rivers are dry and flashy with water flowing for few hours and there are no river gauging stations in these rivers. Before 1991, the Ministry of Agriculture was mandated to operate the river flow and climate gauging stations. However, the network collapsed following the break of civil war in the early nineties. No data was collected between 1991 and 2001/2. SWALIM re-established the network in 2001/2 and by installing new stations in some areas and the network has continued to expend progressively. Out of the 14 river gauging stations that were operational before the war only eight stations are currently operational; four on the Shabelle and four on the Juba. The climate monitoring network has over 100 stations across Somalia. FAO SWALIM has partnered with the Ministry of Energy and Water Resources (MOEWR) and Ministry of Agriculture (MOA) in river and climate data collection respectively. However, under the current context with federal governments and regions, the Puntland ministry of Environment, Agriculture and climate change and the Somaliland Ministry of Agricultural development are responsible for climate data in their respective regions. hydromet_stations_july_2021 somalia shabelle 2021 features breakges river juba EPSG:4326 CRS:84 42.079382 50.811797 -0.350043336883837 11.96532 other other other other text/xml other other geonode:international_disputed_border Somalia International Disputed Borders features international_disputed_border EPSG:4326 CRS:84 32.99993896500007 54.53052902200005 -4.676485090999961 19.00233268700009 other other other other text/xml other other geonode:jowhar_date_palm_suitability This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture jowhar SWALIM jowhar_date_palm_suitability Date Palm somalia Climate FAO EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:jowhar_forage_suitability This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features pasture Soil agriculture forage jowhar SWALIM somalia jowhar_forage_suitability Climate FAO EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:jowhar_lu_soil_map_v2 This dataset represents the semi-detailed soil maps of selected riverine Areas of Interest (AOIs) in southern and central Somalia, including Luuq, Belet Weyne, Afgooye, Jowhar, and Kismaayo. The maps were developed through integrated soil survey methodologies combining field observations, laboratory analysis, and geospatial interpretation. The dataset provides spatial information on soil distribution, land units, and key soil physical and chemical properties. It supports agricultural planning, irrigation development, land resource management, and climate-resilient interventions in the Shabelle and Juba river basins. The mapping is part of a broader SWALIM initiative aimed at improving soil knowledge at semi-detailed scale for sustainable land use planning. Methodology The soil maps for all AOIs were developed using a standardized methodology based on FAO soil survey guidelines and adapted to the Somali landscape context. 1. Land Unit Delineation (Photointerpretation) Preliminary land units were delineated using satellite imagery and landscape interpretation based on: geomorphology landforms surface characteristics 2. Field Soil Survey Field campaigns were conducted to collect soil profile (pedon) data, including: horizon description soil depth texture structure drainage conditions 3. Laboratory Analysis Soil samples were analyzed to determine key physical and chemical properties, including: Soil texture (sand, silt, clay) Bulk density Soil pH Electrical conductivity (salinity) Organic carbon and organic matter Total nitrogen Calcium carbonate Cation Exchange Capacity (CEC) Exchangeable bases (Ca, Mg, K, Na) Available water capacity (AWC) 4. Soil Classification and Mapping Soils were grouped into Land Units Classified using WRB (World Reference Base for Soil Resources) Mapped at semi-detailed scale (1:25,000) 5. Soil–Landscape Database Development A comprehensive dataset was developed integrating: Soil properties Climate characteristics Physiographic and landscape attributes This database supports further applications such as land suitability analysis. Spatial Resolution / Scale Scale: 1:25,000 (semi-detailed soil mapping) Geographic Coverage Riverine agricultural areas in Somalia: Luuq Belet Weyne Afgooye Jowhar Kismaayo Located along the Juba and Shabelle river systems Soil Characteristics Included Physical Properties Texture Soil depth Structure Drainage Permeability Available Water Capacity (AWC) Rooting depth Chemical Properties Soil pH Salinity (EC) Organic carbon Organic matter Total nitrogen Calcium carbonate Cation Exchange Capacity (CEC) Exchangeable cations (Ca, Mg, K, Na) Alkalinity (ESP) Landscape Attributes Flooding regimes Alluvial plains and terraces Soil moisture conditions Topography (slope, elevation) Soil Map jowhar_lu_soil_map_v2 features Riverine Agriculture jowhar shabelle SWALIM Land Units Soil Properties Soil Survey somalia juba WRB Classification EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:jowhar_maize_suitability This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil jowhar_maize_suitability agriculture jowhar SWALIM somalia maize Climate FAO EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:jowhar_mango_suitability This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture Mango jowhar_mango_suitability jowhar SWALIM somalia Climate FAO EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:jowhar_onion_suitability This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability jowhar_onion_suitability features Soil agriculture Onion jowhar SWALIM somalia Climate FAO EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:jowhar_paddy_rice_suitability This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability paddy rice features jowhar_paddy_rice_suitability Soil agriculture jowhar SWALIM somalia Climate FAO EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:jowhar_potential_suitable_higher_grounds_for_ Datasets used for the analysis are :- Flood Extent, Elevation, Slope, Topographic Wetness Index (TWI),Drainage Density, Strategic Boreholes, Settlements, Land Cover and Roads\r\nBased on a predefined criteria, each of these datasets were first clipped to areas outside the flood extent but within a maximum distance of 10 Km from the flood extent boundary. The outputs were then reclassified into two classes namely; Suitable and Not Suitable. Using an iterative approach, each of these datasets was used to assign a weight to the suitability of a site. These weights are indicated on table 2 below. Thereafter, a multi-criteria evaluation weighted overlay operation was undertaken to determine the potential areas for evacuation sites. An area was then computed for the potential sites and their distance from the flood extent established. \r\nThe output was then post – processed to remove invalid geometries and each site was ranked based on the distance from the flood prone area. Sites that are closer in distance were deemed to be most suitable hence a higher rank. The final layer was then visually checked based on the density of the topographic Wetness Index (TWI) which is based on runoffs during floods. Areas with dense TWI were eliminated to remain with only continuous areas. floods grounds evacuation higher somalia jowhar_potential_suitable_higher_grounds_for_ shabelle features potential river juba EPSG:4326 CRS:84 45.129924716631606 45.93873155424707 2.735755014094051 3.238304687052858 other other other other text/xml other other geonode:jowhar_profile_location features jowhar_profile_location EPSG:32638 CRS:84 45.43875623866943 45.655300714580974 2.6803966047632315 2.9790570639232525 other other other other text/xml other other geonode:jowhar_sesame_suitability This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture jowhar SWALIM somalia sesame Climate FAO jowhar_sesame_suitability EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:jowhar_sorghum_suitability This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture jowhar SWALIM somalia jowhar_sorghum_suitability Climate sorghum FAO EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:jowhar_suitability_banana This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture jowhar_suitability_banana banana jowhar SWALIM somalia Climate FAO EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:jowhar_suitability_citrus This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture jowhar SWALIM somalia Climate Citrus FAO jowhar_suitability_citrus EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:jowhar_tomato_suitability This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features jowhar_tomato_suitability Soil agriculture jowhar SWALIM Climate somalia tomato FAO EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:jowhar_watermelon_suitability This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability features Soil agriculture jowhar water melon SWALIM somalia jowhar_watermelon_suitability Climate FAO EPSG:32638 CRS:84 45.38002527814642 45.75322635132957 2.5059669416177432 3.0265576012996753 other other other other text/xml other other geonode:juba_shabelle_river_floods_gu_2023 This data was produced through visual interpretation of Sentinel 1, Sentinel 2, World View 3 satellite images and UNOSAT Analysis. The Flood Extent may be smaller than the actual due to cloud cover on analysis images that hindered assessment in some areas and limitations of radar to detect flooding within urban areas 2023 floods juba_shabelle_river_floods_gu_2023 somalia shabelle features gu river juba EPSG:4326 CRS:84 41.69500491500003 45.758267285000045 -0.251569337999968 5.011365984000065 other other other other text/xml other other geonode:kismaayo_banana_suit_v2 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability kismaayo features Soil agriculture banana kismaayo_banana_suit_v2 SWALIM somalia Climate FAO EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:kismaayo_citrus_suit_v2 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) kismaayo_citrus_suit_v2 crop suitability kismaayo features land suitability Soil agriculture SWALIM somalia Climate Citrus FAO EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:kismaayo_date_palm_suit_v2 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) kismaayo_date_palm_suit_v2 land suitability crop suitability kismaayo features Soil agriculture SWALIM Date Palm somalia Climate FAO EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:kismaayo_grazing_suit_v2 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability kismaayo features pasture Soil agriculture rangeland kismaayo_grazing_suit_v2 grazing SWALIM somalia Climate FAO EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:kismaayo_maize_suit_v2 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability kismaayo features Soil agriculture kismaayo_maize_suit_v2 SWALIM somalia maize Climate FAO EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:kismaayo_mango_suit_v2 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability kismaayo features Soil agriculture Mango kismaayo_mango_suit_v2 SWALIM somalia Climate FAO EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:kismaayo_onion_suit_v2 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability kismaayo features Soil agriculture kismaayo_onion_suit_v2 Onion SWALIM somalia Climate FAO EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:kismaayo_paddy_rice_suit_v2 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) kismaayo_paddy_rice_suit_v2 land suitability crop suitability paddy rice kismaayo features Soil agriculture SWALIM somalia Climate FAO EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:kismaayo_sesame_suit_v2 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability kismaayo features Soil agriculture SWALIM somalia sesame Climate FAO kismaayo_sesame_suit_v2 EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:kismaayo_soilmap_soildata_v2 This dataset represents the semi-detailed soil maps of selected riverine Areas of Interest (AOIs) in southern and central Somalia, including Luuq, Belet Weyne, Afgooye, Jowhar, and Kismaayo. The maps were developed through integrated soil survey methodologies combining field observations, laboratory analysis, and geospatial interpretation. The dataset provides spatial information on soil distribution, land units, and key soil physical and chemical properties. It supports agricultural planning, irrigation development, land resource management, and climate-resilient interventions in the Shabelle and Juba river basins. The mapping is part of a broader SWALIM initiative aimed at improving soil knowledge at semi-detailed scale for sustainable land use planning. Methodology The soil maps for all AOIs were developed using a standardized methodology based on FAO soil survey guidelines and adapted to the Somali landscape context. 1. Land Unit Delineation (Photointerpretation) Preliminary land units were delineated using satellite imagery and landscape interpretation based on: geomorphology landforms surface characteristics 2. Field Soil Survey Field campaigns were conducted to collect soil profile (pedon) data, including: horizon description soil depth texture structure drainage conditions 3. Laboratory Analysis Soil samples were analyzed to determine key physical and chemical properties, including: Soil texture (sand, silt, clay) Bulk density Soil pH Electrical conductivity (salinity) Organic carbon and organic matter Total nitrogen Calcium carbonate Cation Exchange Capacity (CEC) Exchangeable bases (Ca, Mg, K, Na) Available water capacity (AWC) 4. Soil Classification and Mapping Soils were grouped into Land Units Classified using WRB (World Reference Base for Soil Resources) Mapped at semi-detailed scale (1:25,000) 5. Soil–Landscape Database Development A comprehensive dataset was developed integrating: Soil properties Climate characteristics Physiographic and landscape attributes This database supports further applications such as land suitability analysis. Spatial Resolution / Scale Scale: 1:25,000 (semi-detailed soil mapping) Geographic Coverage Riverine agricultural areas in Somalia: Luuq Belet Weyne Afgooye Jowhar Kismaayo Located along the Juba and Shabelle river systems Soil Characteristics Included Physical Properties Texture Soil depth Structure Drainage Permeability Available Water Capacity (AWC) Rooting depth Chemical Properties Soil pH Salinity (EC) Organic carbon Organic matter Total nitrogen Calcium carbonate Cation Exchange Capacity (CEC) Exchangeable cations (Ca, Mg, K, Na) Alkalinity (ESP) Landscape Attributes Flooding regimes Alluvial plains and terraces Soil moisture conditions Topography (slope, elevation) Soil Map kismaayo features Riverine Agriculture shabelle SWALIM Land Units Soil Properties Soil Survey somalia juba WRB Classification kismaayo_soilmap_soildata_v2 EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:kismaayo_sorghum_suit_v2 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability kismaayo features Soil agriculture kismaayo_sorghum_suit_v2 SWALIM somalia Climate sorghum FAO EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:kismaayo_tomato_suit_v2 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability kismaayo features kismaayo_tomato_suit_v2 Soil agriculture SWALIM Climate somalia tomato FAO EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:kismaayo_watermelon_suit_v2 This dataset represents soil and climate suitability for agricultural production across selected areas of Somalia. The analysis applies a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic characteristics. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying levels of limitations affecting agricultural productivity. The dataset has been developed for multiple districts including Jowhar, Kismaayo, Beletweyne, Afgooye and Luuq under resilience and agricultural development initiatives. Methodology Land suitability was undertaken by considering land utilization types for rainfed and irrigated agriculture. The process involved assessing land use requirements, land characteristics, and land qualities such as moisture availability, radiation regime, and soil workability. A parametric approach rated limitations on a five-level scale, producing numerical scores based on crop-specific root zone evaluations. The matching of land-use requirements with land qualities and land characteristics determines the suitability of a particular land unit for a particular land utilization type. The ranking values are then summarized, giving each land unit a class of suitability. The classes are: S1 – Highly Suitable: Land with no or only minor limitations that do not significantly affect productivity, benefits, or input requirements. S2 – Moderately Suitable: Land with moderately severe limitations that reduce productivity and increase inputs compared to S1. S3 – Marginally Suitable: Land with severe limitations that significantly reduce productivity or require high inputs. N1 – Currently Not Suitable: Land with very severe limitations that prevent sustained use under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations that make sustained agricultural use impossible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model FABDEM (30 m) FAO-SWALIM and UNDP datasets Project Context This dataset was produced for targeted Areas of Interest (AOIs) under resilience and agricultural development initiatives, including projects such as: Climate-resilient Livelihoods to Boost Food Production and Nutrition Outcomes (CLIMB) Somalia Crisis Recovery Project (SCRP) Building Resilience in Middle Shabelle (BRiMS Phase 1) land suitability crop suitability kismaayo features Soil agriculture SWALIM Climate somalia kismaayo_watermelon_suit_v2 water melon FAO EPSG:4326 CRS:84 42.45840657117793 42.6226803822845 -0.291413779298069 0.005215557978834 other other other other text/xml other other geonode:labsoil Data Shows soils field samples collected in the Northern and southern parts of Somalia by SWALIM during soil surveys in 2006 and 2008 respectively.For field photos attached to some of the sample points see the link https://www.dropbox.com/sh/n60nk7i00g76r1e/AAAYlbJUDYgR_MmWKcvkKyVMa?dl=0 features labsoil EPSG:4326 CRS:84 42.25800000000004 45.79119999900007 0.039444400000036 10.628200001000039 other other other other text/xml other other geonode:land_covernorth The Methodology adopted for land cover classes involved processing of satellite images of Landsat, Aster and Ikonos.This was followed by photointerpretation and and production of basemaps by SWALIM. Field data collection was then carried out and the maps then revised. Please refer to FAO-SWALIM Technical report number 03 for more information on this. features land_covernorth EPSG:32638 CRS:84 43.007251089913694 44.46284752986155 9.162947876314933 10.691058244859452 other other other other other text/xml other geonode:land_forestsuitability_acacianilotica_n The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species Acacia Niloticain selected areas in northern part of Somalia (Garbiley and Boroma areas in Somaliland). features land_forestsuitability_acacianilotica_n EPSG:4326 CRS:84 43.01092679300007 44.46210394500008 9.166513131000045 10.689748208000026 other other other other text/xml other other geonode:land_forestsuitability_balanitesaegyptiaca_n The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species Balanites Aegyptiacain selected areas in northern part of Somalia (Garbiley and Boroma areas in Somaliland). features land_forestsuitability_balanitesaegyptiaca_n EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:landcover_2000 The land cover has been produced from visual interpretation of digitally enhanced LANDSAT TM images (Bands 4,3,2) acquired mainly in the year 1995 - 1998. The land cover classes have been developed using the FAO/UNEP international standard LCCS classification system. The purpose of the Africover landcover database is to provide the information required for natural resource assessment and management, environmental modeling and decision-making. The LCCS legend for the country, a list of the LCCS classifiers used in the interpretation, LCCS glossary of terms, a list of thematic classes and their frequency in a mixed unit, and a report on the frequency and scale adequacy, can be found in the full resolution landcover database report found in the same folder as the dataset. FAO Project code GCP/RAF/287/ITA features landcover_2000 EPSG:4326 CRS:84 40.98862838700006 51.41272354100005 -1.667189716999928 11.99218845400003 other other other other text/xml other other geonode:landcover_mangroveforest0 Patches of mangroves are found in Zeylac, Berbera and Calula on the northern coastline and in Kismayo on the southern coast. Mangrove swamp communities are also situated at the tidal estuaries of the seasonal rivers towards the Indian Ocean coast and Gulf of Aden. They areas include Bushbush, Caanoole and Lag Badanaa. The mangroves, like the Golis forest, are facing increased pressure of commercial exploitation. features landcover_mangroveforest0 EPSG:4326 CRS:84 41.95973096000006 50.80897644000004 -1.015475849999973 11.987464120000027 other other other other text/xml other other geonode:landcover_ne_1988 The land cover has been produced from visual interpretation of LANDSAT images. features landcover_ne_1988 EPSG:4326 CRS:84 48.01002975000006 49.41157533000006 7.058458920000021 9.907768245000057 other other other other text/xml other other geonode:landcover_ne_2007 Land cover classes were created using the Land Cover Classification System (LCSS) of FAO, Landsat satellite image interpretation, and field validation. features landcover_ne_2007 EPSG:4326 CRS:84 48.01002796000006 49.411575320000054 7.058458920000021 9.907768245000057 other other other other text/xml other other geonode:landcover_nw_2007 Land cover classes were created using the Land Cover Classification System (LCSS) of FAO, Landsat satellite image interpretation, and field validation. landcover_nw_2007 features EPSG:4326 CRS:84 43.011011490000044 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:landcover_riverine_2007 Land cover is the physical material at the surface of the earth. Land cover includes grass, asphalt, trees, bare ground, water, etc. The land cover map of the riverine areas forms the most recent, most detailed and most consistent data set produced by SWALIM. The map is result of exhaustive aerial photograph interpretation by SWALIM experts. However, the map gives more attention to the cropped areas, giving the crop type and acreage. The final map has been aggregated into few manageable land cover classes. Among the striking features of the map are the areas that were once cropped and now remain abandoned. features landcover_riverine_2007 EPSG:4326 CRS:84 41.28020095800008 46.150032544000055 -0.510218972999951 5.060045358000025 other other other other text/xml other other geonode:luuq_potentialsuitablehigherground_forevacuat Datasets used for the analysis are :- Flood Extent, Elevation, Slope, Topographic Wetness Index (TWI),Drainage Density, Strategic Boreholes, Settlements, Land Cover and Roads\r\nBased on a predefined criteria, each of these datasets were first clipped to areas outside the flood extent but within a maximum distance of 10 Km from the flood extent boundary. The outputs were then reclassified into two classes namely; Suitable and Not Suitable. Using an iterative approach, each of these datasets was used to assign a weight to the suitability of a site. These weights are indicated on table 2 below. Thereafter, a multi-criteria evaluation weighted overlay operation was undertaken to determine the potential areas for evacuation sites. An area was then computed for the potential sites and their distance from the flood extent established. \r\nThe output was then post – processed to remove invalid geometries and each site was ranked based on the distance from the flood prone area. Sites that are closer in distance were deemed to be most suitable hence a higher rank. The final layer was then visually checked based on the density of the topographic Wetness Index (TWI) which is based on runoffs during floods. Areas with dense TWI were eliminated to remain with only continuous areas.t provided somalia shabelle luuq_potentialsuitablehigherground_forevacuat features river juba EPSG:4326 CRS:84 42.33214392765078 42.67775912689938 3.480640891110264 4.083094438539265 other other other other text/xml other other geonode:mogadishu_city_roads Digital city map of Mogadishu based on local citymaps, NIMA citymaps, Landsat ETM+ and QB-images features mogadishu_city_roads EPSG:4326 CRS:84 45.22171107400004 45.47246052700007 1.997457074000067 2.135359390000076 other other other other text/xml other other geonode:mogadishu_districts_unocha Digital city map of Mogadishu based on local city maps, NIMA city maps, Landsat ETM+ and QB-images features mogadishu_districts_unocha EPSG:4326 CRS:84 45.22952244600003 45.43303938300005 1.974369931000069 2.099879804000068 other other other other other text/xml other geonode:mv_se_root_ts No abstract provided features mv_se_root_ts EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 2018-01-01T00:00:00.000Z,2018-02-01T00:00:00.000Z,2018-03-01T00:00:00.000Z,2018-04-01T00:00:00.000Z,2018-05-01T00:00:00.000Z,2018-06-01T00:00:00.000Z,2018-07-01T00:00:00.000Z,2018-08-01T00:00:00.000Z,2018-09-01T00:00:00.000Z,2018-10-01T00:00:00.000Z,2018-11-01T00:00:00.000Z,2018-12-01T00:00:00.000Z,2019-01-01T00:00:00.000Z,2019-02-01T00:00:00.000Z,2019-03-01T00:00:00.000Z,2019-04-01T00:00:00.000Z,2019-05-01T00:00:00.000Z,2019-06-01T00:00:00.000Z,2019-07-01T00:00:00.000Z,2019-08-01T00:00:00.000Z,2019-09-01T00:00:00.000Z,2019-10-01T00:00:00.000Z,2019-11-01T00:00:00.000Z,2019-12-01T00:00:00.000Z,2020-01-01T00:00:00.000Z,2020-02-01T00:00:00.000Z,2020-03-01T00:00:00.000Z,2020-04-01T00:00:00.000Z,2020-05-01T00:00:00.000Z,2020-06-01T00:00:00.000Z,2020-07-01T00:00:00.000Z,2020-08-01T00:00:00.000Z,2020-09-01T00:00:00.000Z,2020-10-01T00:00:00.000Z,2020-11-01T00:00:00.000Z,2020-12-01T00:00:00.000Z,2021-01-01T00:00:00.000Z,2021-02-01T00:00:00.000Z,2021-03-01T00:00:00.000Z,2021-04-01T00:00:00.000Z,2021-05-01T00:00:00.000Z,2021-06-01T00:00:00.000Z,2021-07-01T00:00:00.000Z,2021-08-01T00:00:00.000Z,2021-09-01T00:00:00.000Z,2021-10-01T00:00:00.000Z,2021-11-01T00:00:00.000Z,2021-12-01T00:00:00.000Z,2022-01-01T00:00:00.000Z,2022-02-01T00:00:00.000Z,2022-03-01T00:00:00.000Z,2022-04-01T00:00:00.000Z,2022-05-01T00:00:00.000Z,2022-06-01T00:00:00.000Z,2022-07-01T00:00:00.000Z,2022-08-01T00:00:00.000Z,2022-09-01T00:00:00.000Z,2022-10-01T00:00:00.000Z,2022-11-01T00:00:00.000Z,2022-12-01T00:00:00.000Z,2023-01-01T00:00:00.000Z,2023-02-01T00:00:00.000Z,2023-03-01T00:00:00.000Z,2023-04-01T00:00:00.000Z,2023-05-01T00:00:00.000Z,2023-06-01T00:00:00.000Z,2023-07-01T00:00:00.000Z,2023-08-01T00:00:00.000Z,2023-09-01T00:00:00.000Z,2023-10-01T00:00:00.000Z,2023-11-01T00:00:00.000Z,2023-12-01T00:00:00.000Z,2024-01-01T00:00:00.000Z,2024-02-01T00:00:00.000Z,2024-03-01T00:00:00.000Z,2024-04-01T00:00:00.000Z,2024-05-01T00:00:00.000Z,2024-06-01T00:00:00.000Z,2024-07-01T00:00:00.000Z,2024-08-01T00:00:00.000Z,2024-09-01T00:00:00.000Z,2024-10-01T00:00:00.000Z,2024-11-01T00:00:00.000Z,2024-12-01T00:00:00.000Z,2025-01-01T00:00:00.000Z,2025-02-01T00:00:00.000Z,2025-03-01T00:00:00.000Z,2025-04-01T00:00:00.000Z,2025-05-01T00:00:00.000Z,2025-06-01T00:00:00.000Z,2025-07-01T00:00:00.000Z,2025-08-01T00:00:00.000Z text/xml other other other other other other other other other other other text/xml other geonode:pre_gu_2024_frmmis_march_2024 FAO-SWALIM has updated the status of the river breakages along the Juba and Shabelle Rivers using available Very High Resolution (VHR) satellite imagery and a Digital Elevation Model (DEM). Four types of breakages have been identified, namely; open, overflow, Canal Flooding Point, and closed with sandbags. The open breakages are those that are currently open as observed on the latest VHR image available. All the observations reported refers to the latest suitable VHR satellite image available, which is indicated in the online database. \r\n\r\n299 Open breakage points have been identified, 190 on the Shabelle River and 109 on the Juba River which require immediate action. Additionally, 97 Canal Overflow points and 747 Overflows were also identified during this season.\r\n\r\nUsers are advised that the methodology is biased towards Remote Sensing (RS) interpretation with only limited “ground truthing” due to access constraints. Open breakages might have been omitted in some cases where satellite images may not have been very clear (e.g. heavy cloud cover) or were not available. pre_gu_2024_frmmis_march_2024 river somalia shabelle features juba breakges EPSG:4326 CRS:84 42.06809 45.67867 -0.09637 4.89294 other other other other text/xml other other geonode:relief_nw_faoswalim This data is about Somalia relief and landscape which represents information about elevations and landforms of north western part of Somalia. Data on topography from NASA SRTM 90 m. features relief_nw_faoswalim EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:reservoirs This dataset contains 54,802 mapped surface water sources across Somalia, including Berkads (33,649), Haffir dams (14,488), and natural ponds (6,665), digitized through a coordinated crowd-mapping campaign led by the Humanitarian OpenStreetMap Team (HOT-OSM) in collaboration with FAO Somalia Water and Land Information Management (SWALIM). The data was collected between 2024–2025 using remote mapping and validation workflows based on high-resolution satellite imagery and OpenStreetMap (OSM) standards. Features were digitized as polygons and attributed with water source type, shape, and descriptive characteristics to support water availability assessment, drought preparedness, and early warning analysis. The finalized dataset has been quality-controlled and integrated into FAO’s early warning and decision-support systems and is made available for humanitarian and development partners to support drought response, water resource planning, and resilience programming across Somalia. Data Access and Updates This dataset is maintained within the OpenStreetMap (OSM) ecosystem and may be updated over time through ongoing OSM community contributions. The data can be accessed through any platform or application that supports OpenStreetMap data, including desktop GIS software such as QGIS and OSM query services such as Overpass Turbo (https://overpass-turbo.eu/). The surface water sources can be queried and extracted using standard OSM tags, including: natural=reservoir water=reservoir Additional feature classification can be derived from associated attributes indicating water source type (Berkad, Haffir, Natural Pond) and geometry. features reservoirs EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 other other other other text/xml other other other other other other text/xml other other geonode:reservoirs_monitor No abstract provided features resrvoirs_monitor EPSG:4326 CRS:84 40.9912106 50.8477423 -1.5873291 11.1260654 2025-01-01T00:00:00.000Z,2025-02-01T00:00:00.000Z,2025-03-01T00:00:00.000Z,2025-04-01T00:00:00.000Z,2025-05-01T00:00:00.000Z,2025-06-01T00:00:00.000Z,2025-07-01T00:00:00.000Z,2025-08-01T00:00:00.000Z,2025-09-01T00:00:00.000Z other other other other text/xml other other other other other other text/xml other other geonode:river_breakage_shabell_aug_2025 FAO-SWALIM has updating the status of the river breakages along the Juba and Shabelle Rivers using available Very High Resolution (VHR) satellite imagery and a Digital Elevation Model (DEM). Five types of breakages have been identified; Open, Overflow, Canal Breakage, Canal Intake Flooding and Closed with sandbags. The open breakages are those that are currently open as observed on the latest VHR image available. All the observations reported refers to the latest suitable VHR satellite image available, which is indicated in the online database. A legend/Key for further explanation of the different types of breakages is provided.  Along the Shabelle river, a total of 126 Open breakage points, 55 Canal flooding points, 188 Overflow points and 7 points closed with sandbags have been identified. Users are advised that the methodology is biased towards Remote Sensing (RS) interpretation with only limited “ground truthing” due to access constraints. Open breakages might have been omitted in some cases where satellite images may not have been very clear (e.g. heavy cloud cover) or were not available.  For questions or further clarifications related to the reports, you can contact us by sending an email to SWALIM@fao.org.  features river_breakage_shabell_aug_2025 EPSG:4326 CRS:84 44.12800000000004 45.67867000000007 1.551000000000045 4.892940000000067 other other other other text/xml other other geonode:river_breakages_juba_shabelle_march2026 FAO-SWALIM has released the status of the river breakages along the Juba and Shabelle Rivers using available Very High Resolution (VHR) satellite imagery and a Digital Elevation Model (DEM). Five types of breakages have been identified; Open, Overflow, Canal Breakage, Canal Intake Flooding and Closed with sandbags. The open breakages are those that are currently open as observed on the latest VHR image available. All the observations reported refers to the latest suitable VHR satellite image available, which is indicated in the online database. A legend/Key for further explanation of the different types of breakages is provided. A long the Shabelle river, 171 Open points, 2 Canal Breakages, 51 Canal flooding points, 323 Overflow points and 17 points closed with sandbags have been identified while along Juba river 104 Open points, 1 Canal Breakage, 16 Canal flooding points, 83 Overflow points and 1 point closed with sandbags have been identified. Several other points, which are either potential or temporarily closed with sandbags, have also been identified. shabelle river breakages river_breakages_juba_shabelle_march2026 FAO SWALIM features somalia floods juba EPSG:4326 CRS:84 42.06187852925861 45.67792175611577 -0.095961273859731 4.893462037080062 other other other other other other text/xml geonode:river_juba_breakage_aug_2025 FAO-SWALIM has updating the status of the river breakages along the Juba and Shabelle Rivers using available Very High Resolution (VHR) satellite imagery and a Digital Elevation Model (DEM). Five types of breakages have been identified; Open, Overflow, Canal Breakage, Canal Intake Flooding and Closed with sandbags. The open breakages are those that are currently open as observed on the latest VHR image available. All the observations reported refers to the latest suitable VHR satellite image available, which is indicated in the online database. A legend/Key for further explanation of the different types of breakages is provided.  Along the Juba River 105 Open breakage points, 14 Canal flooding points, 31 Overflow points and 2 points closed with sandbags have been identified.  Users are advised that the methodology is biased towards Remote Sensing (RS) interpretation with only limited “ground truthing” due to access constraints. Open breakages might have been omitted in some cases where satellite images may not have been very clear (e.g. heavy cloud cover) or were not available.  For questions or further clarifications related to the reports, you can contact us by sending an email to SWALIM@fao.org.  features river_juba_breakage_aug_2025 EPSG:3857 CRS:84 42.062708985935565 42.778638664845076 -0.0963662694276506 4.179544681127806 other other other other text/xml other other geonode:river_juba_shabelle_breakage_apr2023_18042022 SWALIM has updated the status of the river breakages along the Juba and Shabelle Rivers using available Very High Resolution (VHR) satellite imagery acquired from World View 2/World View 3 and PLEIADES and a Digital Elevation Model (DEM).Six types of breakages have been identified, namely; Canal Flooding Point, open, overflow, potential overflows, potential breakages and closed with sandbags. The open breakages are those that are currently open as observed on the latest VHR image available. All the observations reported refers to the latest suitable VHR satellite image available, which is indicated in the online database.\r\n\r\n65 Open breakage points have been identified, 39 on the Shabelle River and 26 on the Juba River which require immediate action. 15 Overflows were also identified during this season.\r\n\r\nUsers are advised that the methodology is biased towards Remote Sensing (RS) interpretation with only limited “ground truthing” due to access constraints. Open breakages might have been omitted in some cases where satellite images may not have been very clear (e.g. heavy cloud cover) or were not available. 2023 river_juba_shabelle_breakage_apr2023_18042022 river shabelle somalia features breakages juba EPSG:4326 CRS:84 42.06809008 45.67867 -0.07097 4.89294 text/xml other other other other other other geonode:river_juba_shabelle_breakage_aug2021_26082021 SWALIM has been mapped twice a year the river breakages along the two rivers since 2015. This had been made possible with the use of World View Very High-Resolution (VHR) satellite imagery provided by Digital Globe. Due to lower temporal resolution of images present in Digital Globe archive, Pleiades Images provided by Airbus supplemented the image gaps in some areas. Where possible the preliminary findings from the images were verified with field observations to confirm the status of river breakages. In this case, the field river breakages surveys were carried out in Belet Weyne, Jowhar, Balcad and Afgooye districts all along the Shabelle River. In other cases, breakages which had been verified on VHR in March 2021 and there was either cloudy images or no images at all in the current assessment have been marked as ‘Not verified’.\r\n\r\nAlong the Juba River, 32 open points, 6 overflows and another 123 potential breakages and 75 potential overflows were identified. Further, 103 open points, 106 overflows and 103 potential breakages and 322 potential overflows were identified along the Shabelle River.\r\n\r\nIt has been observed that the number of points either open or overflows has been increasing over the years probably due to the continuous weakening of the river banks following three years of successive heavy floods in 2018, 2019 and 2020. These points need immediate closure or reinforcement before the 2021 Deyr rainy season which is expected to start in Mid-October 2021. 2021 river somalia shabelle features juba river_juba_shabelle_breakage_aug2021_26082021 breakges EPSG:4326 CRS:84 42.0680900799999 45.6786699999999 -0.07097 4.89294 other other other other text/xml other other geonode:river_juba_shabelle_breakage_september_2023 FAO-SWALIM has updated the status of the river breakages along the Juba and Shabelle Rivers using available Very High Resolution (VHR) satellite imagery and a Digital Elevation Model (DEM). Four types of breakages have been identified, namely; Open, Overflow, Canal Flooding Point, and Closed with sandbags. The open breakages are those that are currently open as observed on the latest VHR image available. All the observations reported refers to the latest suitable VHR satellite image available, which is indicated in the online database. 196 Open breakage points have been identified, 170 on the Shabelle River and 26 on the Juba River which require immediate action. 168 Overflows were also identified during this season. 2023 river shabelle features somalia breakages juba river_juba_shabelle_breakage_september_2023 EPSG:4326 CRS:84 42.0680900803 45.67867 -0.0709700000654 4.89294 other other other other text/xml other other geonode:river_juba_shabelle_breakages_feb_2021 Along the Juba River, 46 open points, 8 overflows and another 65 potential overflows were identified. The Juba River assessment also identified over 100 potential breakage points. Further, the team have identified 57 open points, 225 overflows and 74 potential overflows along the Shabelle River. These points need immediate closure or reinforcement before the Gu rainy season which is expected to start in Mid-April 2021.\r\n\r\nIt is worth noting that due to limited availability of VHR images, there has been a delay in completing the assessment of Shabelle River breakages. FAO SWALIM is in the process of procuring images to cover the assessment gap and partners will be notified once the finalized product is ready. 2021 river somalia shabelle features juba river_juba_shabelle_breakages_feb_2021 breakges EPSG:4326 CRS:84 42.06809008 45.6786699999998 -0.07097 4.89294 other other other other text/xml other other geonode:salty_ground_water_sources This data contains areas with Salty ground water features salty_ground_water_sources EPSG:4326 CRS:84 45.90456756800006 48.66227248700005 3.301845846000049 6.605074081000055 other other other other text/xml other other geonode:shabelle_hagaa_floods_11092020 This data was produced through visual interpretation of Sentinel 1 and Sentinel 2 satellite images acquired between August and September floods somalia shabelle features 2020 river shabelle_hagaa_floods_11092020 hagaa EPSG:32638 CRS:84 44.58523412846264 45.7159422715063 1.754250619618238 5.0100251749227604 other other other other text/xml other other geonode:shabelle_juba_aug_2020frrmis__w9i4api FAO SWALIM has finalized the analysis and mapping of the river breakages along the Juba and Shabelle rivers using very high resolution satellite imagery. Breakages identified in the map have been classified into five different categories; Open, Overflow, Potential Overflows, Potential breakages and Closed with sandbags. A total of 154 Open points have been identified, 109 on the Shabelle River and 45 on the Juba River which require immediate attention. river somalia shabelle features breakages juba shabelle_juba_aug_2020frrmis__w9i4api 2020 EPSG:4326 CRS:84 42.068186 45.67867 -0.07097 4.89294 other other other other text/xml other other geonode:shabelle_juba_breakages_feb_2022 Three consecutive poor rainy seasons within the Juba and Shabelle River basins inside Somalia and the Ethiopian highlands have led to the current serious hydrological drought along the two rivers. The river levels in the upper sections are currently at their historical minimum, while the mid and lower sections of the Shabelle River having run dry. With no rains expected in February and most of March, the river flow will continue to decline. The reduced river flow along the two rivers has negatively impacted agriculture production, domestic and livestock water use. This has also led to an increase of new river breakages as the riverine communities attempt to extract the limited resource to support livelihood activities.\r\n\r\nSWALIM has completed analysis and mapping of the river breakages along the two rivers using very high resolution satellite images acquired thanks to the kind contribution of the Embassy of France. The study has identified 101 open points along the Shabelle, out of which 24 points are new and the rest have remained open since the last survey in August 2021. Along the Juba River, 35 open points were identified out of which 5 are new points. During this drought period, it is expected that the riverine communities will continue to extract water from the rivers by breaching the banks and this will only see an increase of the open river bank points.\r\n\r\nSeveral other weak points which are not necessarily open but have the potential to overflow or break were identified during the analysis. The summary of the different types of points mapped.  shabelle_juba_breakages_feb_2022 river shabelle features somalia breakages juba 2022 EPSG:4326 CRS:84 42.06809008 45.67867 -0.07097 4.89294 other other other other text/xml other other geonode:shabelle_juba_feb_2020frrmis_vxt8mgw FAO SWALIM has finalized the analysis and mapping of the river breakages along the Juba and Shabelle rivers using very high resolution satellite imagery. Breakages identified in the map have been classified into five different categories; Open, Overflow, Potential Overflows, Potential breakages and Closed with sandbags. A total of 152 Open points have been identified, 100 on the Shabelle River and 52 on the Juba River which require immediate attention. river somalia shabelle features breakages juba 2020 shabelle_juba_feb_2020frrmis_vxt8mgw EPSG:4326 CRS:84 42.068186 45.67867 -0.07097 4.864157 other other other other text/xml other other geonode:shabelle_juba_river_breakages_aug2019 Breakages identified in the map have been classified into six different categories; Open, Overflow, Potential Overflows, Potential breakages, Closed with sandbags and Closed. A total of 84 Open points were identified, 39 on the Shabelle River and 45 on the Juba River which require immediate action in advance of the strong possibility of normal to above normal Deyr (October-December) 2019 season rainfall. river somalia shabelle features breakages juba shabelle_juba_river_breakages_aug2019 2019 EPSG:4326 CRS:84 42.06818600000008 45.678670000000125 -0.070969999999988 4.864156999999977 other other other other text/xml other other geonode:shabelle_juba_river_breakages_feb2017 A total of 37 Open points were identified, 19 along Juba River and 18 along Shabelle River. Several other points, which are either potential ; 359 or temporarily closed with sandbags ;122 were also identified. features shabelle_juba_river_breakages_feb2017 EPSG:4326 CRS:84 42.06818600000008 45.678670000000125 -0.070969999999988 4.864156999999977 other other other other other text/xml other geonode:shabelle_juba_river_breakages_feb2019 Four types of breakages have been identified, namely; open, potential, closed with sandbags and closed. The open breakages are those that are still open as observed on the latest VHR image available, therefore a field verification is needed before planning any repair. river shabelle_juba_river_breakages_feb2019 somalia shabelle features breakages juba 2019 EPSG:4326 CRS:84 42.06818600000008 45.678670000000125 -0.070969999999988 4.864156999999977 other other other other text/xml other other geonode:shabelle_juba_river_breakages_feb_2018 A total of 68 Open points were identified, 41 along Juba River and 27 along Shabelle River. Several other points, which are either potential ; 401 or temporarily closed with sandbags ;64 were also identified. river somalia shabelle 2018 breakages features juba shabelle_juba_river_breakages_feb_2018 EPSG:4326 CRS:84 42.06818600000008 45.677561622644134 -0.070969999999988 4.854544026805797 other other other other text/xml other other geonode:shabelle_juba_river_breakages_july2018 A total of 101 Open points were identified, 54 along Juba River and 47 along Shabelle River.The Gu 2018 heavy rains led to increased river levels and subsequent additional river breakages. 205 Overflow (Overbank river spillage) points were also been identified. The estimated cumulative length of the Overflow sections along the river bank is approximately 82.6 km whose calculation is derived from visible spillages and fresh sand deposits during the flooding period. Several other points, which are either potential or temporarily closed with sandbags, have also been identified. features shabelle_juba_river_breakages_july2018 EPSG:4326 CRS:84 42.06818600000008 45.678670000000125 -0.070969999999988 4.864156999999977 other other other other text/xml other other geonode:shabelle_river_flooding_30th_oct_2019 floods somalia shabelle features 2019 river shabelle_river_flooding_30th_oct_2019 EPSG:32638 CRS:84 44.99717216789348 45.71956338915466 2.335273550273971 5.0196905090468205 other other other other text/xml other other geonode:sm_camel_grazing_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for extensive grazing and forage production across Somalia. The analysis integrates soil, climate, and topographic parameters using a parametric land suitability evaluation framework based on FAO guidelines. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable). Methodology The suitability analysis was conducted using a parametric land evaluation approach following FAO (1976) and Sys et al. (1991), where land suitability is determined by matching environmental conditions with requirements for grazing and forage production. A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil data (250 m resolution, machine learning-based) WoSIS soil profile database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) Due to limited field soil data (~25% land unit coverage), SoilGrids was used to derive key soil properties across multiple depths . Each land unit was evaluated using: Climate factors (rainfall, temperature, LGP) Soil properties (texture, depth, salinity, fertility, drainage) Terrain characteristics (slope, elevation) A matching table approach was applied, where: Parameters were classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation produced a final suitability index The evaluation emphasizes biomass production potential and resilience to harsh conditions, which are critical for grazing systems. Final suitability classes: S2: Moderately suitable S3: Marginally suitable N1: Temporarily unsuitable N2: Permanently unsuitable Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – Global soil database) WoSIS Soil Profile Database SRTM DEM (30 m resolution) SWALIM Length of Growing Period (LGP, 2007) Climate data (rainfall and temperature) Spatial Resolution Soil data: 250 m (SoilGrids) DEM: 30 m Output map scale: 1:1,500,000 land suitability features pasture rangeland forage grazing SWALIM camel somalia sm_camel_grazing_suit_v2 livestock EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_cattle_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for extensive grazing and forage production across Somalia. The analysis integrates soil, climate, and topographic parameters using a parametric land suitability evaluation framework based on FAO guidelines. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable). Methodology The suitability analysis was conducted using a parametric land evaluation approach following FAO (1976) and Sys et al. (1991), where land suitability is determined by matching environmental conditions with requirements for grazing and forage production. A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil data (250 m resolution, machine learning-based) WoSIS soil profile database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) Due to limited field soil data (~25% land unit coverage), SoilGrids was used to derive key soil properties across multiple depths . Each land unit was evaluated using: Climate factors (rainfall, temperature, LGP) Soil properties (texture, depth, salinity, fertility, drainage) Terrain characteristics (slope, elevation) A matching table approach was applied, where: Parameters were classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation produced a final suitability index The evaluation emphasizes biomass production potential and resilience to harsh conditions, which are critical for grazing systems. Final suitability classes: S2: Moderately suitable S3: Marginally suitable N1: Temporarily unsuitable N2: Permanently unsuitable Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – Global soil database) WoSIS Soil Profile Database SRTM DEM (30 m resolution) SWALIM Length of Growing Period (LGP, 2007) Climate data (rainfall and temperature) Spatial Resolution Soil data: 250 m (SoilGrids) DEM: 30 m Output map scale: 1:1,500,000 land suitability features pasture SoilGrids rangeland forage grazing somalia SWALIM sm_cattle_suit_v2 resilience livestock EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_citrus_suit_v3_1 This dataset represents the spatial distribution of soil and climate suitability for irrigated citrus cultivation across Somalia. The analysis was conducted using a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic factors. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable), reflecting varying levels of constraints for citrus production. Methodology The suitability analysis was conducted using a parametric land evaluation framework following FAO (1976) and Sys et al. (1991), where land characteristics are matched with crop requirements through a numerical rating system A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil database (250 m resolution) WoSIS soil profile database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) Due to limited ground soil data, where only 71 out of 318 land units are covered by existing soil profiles, SoilGrids machine learning-derived data was used to fill spatial gaps and complete the national coverage The evaluation considered: Climate factors (temperature, rainfall, LGP, wind) Soil properties (texture, depth, salinity, fertility, drainage, organic carbon) Terrain characteristics (slope, elevation, aspect, erosion risk) Hydrological conditions (flooding risk, permeability, drainage) A matching table approach was used, where: Each parameter was classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation produced a final suitability index The analysis was performed under irrigated conditions, and water availability was not included in the evaluation and must be assessed separately before implementation Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – global soil database) WoSIS Soil Profile Database SRTM DEM (30 m) SWALIM Length of Growing Period (2007) Climate data (rainfall and temperature) Spatial Resolution Soil data: 250 m DEM: 30 m Output map scale: 1:1,500,000 irrigated agriculture sm_citrus_suit_v3_1 land suitability crop suitability features SoilGrids SWALIM soil suitability somalia Citrus EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_drip_suit_v3_1 This dataset represents the spatial distribution of soil suitability for drip irrigation across Somalia. The analysis was conducted using a parametric land evaluation approach based on FAO methodology and the framework of Sys et al. (1991), integrating soil, topographic, hydrological, and fertility-related factors relevant to drip irrigation. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable), reflecting varying levels of constraints affecting drip irrigation development. Methodology The suitability analysis was conducted using a parametric evaluation system following Sys et al. (1991), based on morphology and the physical and chemical properties of soils relevant to irrigation suitability. The evaluation was performed for drip irrigation as one of the two irrigation systems assessed in the report, particularly as a system that can be applied in areas with poor water availability. The parameters applied to the parametric model included: Landscape parameters: slope, surface coarse fragments, erosion risk Soil parameters: rooting depth, internal stoniness, texture, permeability, internal drainage, internal coarse fragments, available water capacity, water table Fertility parameters: pH, salinity, alkalinity, and cation exchange capacity The required data was obtained and calculated from: Existing soil data (312 soil profiles) Africa SoilGrids data (ISRIC global gridded information) Digital Elevation Model (30 m resolution) Erosion risk map (USLE based) A matching table approach was used, where: Each parameter was classified into suitability levels (S1–N2) Numerical ratings were assigned Weighted aggregation produced the final suitability class for each land unit For drip irrigation, the control section is 80 cm, which distinguishes it from surface irrigation. Important notice: the irrigation suitability refers only to the potential irrigation area and does not consider water availability. features Irrigation Suitability Drip Irrigation sm_drip_suit_v3_1 SWALIM soil suitability somalia Land Evaluation EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_forage_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for extensive grazing and forage production across Somalia. The analysis integrates soil, climate, and topographic parameters using a parametric land suitability evaluation framework based on FAO guidelines. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable). Methodology The suitability analysis was conducted using a parametric land evaluation approach following FAO (1976) and Sys et al. (1991), where land suitability is determined by matching environmental conditions with requirements for grazing and forage production. A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil data (250 m resolution, machine learning-based) WoSIS soil profile database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) Due to limited field soil data (~25% land unit coverage), SoilGrids was used to derive key soil properties across multiple depths . Each land unit was evaluated using: Climate factors (rainfall, temperature, LGP) Soil properties (texture, depth, salinity, fertility, drainage) Terrain characteristics (slope, elevation) A matching table approach was applied, where: Parameters were classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation produced a final suitability index The evaluation emphasizes biomass production potential and resilience to harsh conditions, which are critical for grazing systems. Final suitability classes: S2: Moderately suitable S3: Marginally suitable N1: Temporarily unsuitable N2: Permanently unsuitable Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – Global soil database) WoSIS Soil Profile Database SRTM DEM (30 m resolution) SWALIM Length of Growing Period (LGP, 2007) Climate data (rainfall and temperature) Spatial Resolution Soil data: 250 m (SoilGrids) DEM: 30 m Output map scale: 1:1,500,000 land suitability features pasture SoilGrids rangeland forage grazing SWALIM somalia resilience sm_forage_suit_v2 livestock EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_franckincense_suit_v3 This dataset represents the spatial distribution of soil and climate suitability for franckincense cultivation across Somalia. The analysis was conducted using a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic factors. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable), reflecting varying levels of constraints for franckincense production. Methodology The suitability analysis was conducted using a parametric land evaluation framework following FAO (1976) and Sys et al. (1991), where land characteristics are matched with land-use requirements through a numerical rating system. A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil database (250 m resolution) WoSIS soil profile database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) Due to limited ground soil data, where only 71 out of 318 land units are covered by existing soil profiles, SoilGrids machine learning-derived data was used to fill spatial gaps and complete the national coverage The evaluation considered: Climate factors (temperature, rainfall, wind) Soil properties (texture, depth, salinity, fertility, drainage, organic carbon) Terrain characteristics (slope, elevation, aspect, erosion risk) Hydrological conditions (flooding risk, permeability, drainage) A matching table approach was used, where: Each parameter was classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation produced a final suitability index The analysis was performed considering the ecological requirements of franckincense, including its adaptation to arid and semi-arid environments and dryland conditions Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – global soil database) WoSIS Soil Profile Database SRTM DEM (30 m) SWALIM Length of Growing Period (2007) Climate data (rainfall and temperature) Dryland Agriculture land suitability crop suitability features SoilGrids sm_franckincense_suit_v3 SWALIM Franckincense soil suitability somalia EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_goats_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for extensive grazing and forage production across Somalia. The analysis integrates soil, climate, and topographic parameters using a parametric land suitability evaluation framework based on FAO guidelines. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable). Methodology The suitability analysis was conducted using a parametric land evaluation approach following FAO (1976) and Sys et al. (1991), where land suitability is determined by matching environmental conditions with requirements for grazing and forage production. A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil data (250 m resolution, machine learning-based) WoSIS soil profile database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) Due to limited field soil data (~25% land unit coverage), SoilGrids was used to derive key soil properties across multiple depths . Each land unit was evaluated using: Climate factors (rainfall, temperature, LGP) Soil properties (texture, depth, salinity, fertility, drainage) Terrain characteristics (slope, elevation) A matching table approach was applied, where: Parameters were classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation produced a final suitability index The evaluation emphasizes biomass production potential and resilience to harsh conditions, which are critical for grazing systems. Final suitability classes: S2: Moderately suitable S3: Marginally suitable N1: Temporarily unsuitable N2: Permanently unsuitable Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – Global soil database) WoSIS Soil Profile Database SRTM DEM (30 m resolution) SWALIM Length of Growing Period (LGP, 2007) Climate data (rainfall and temperature) Spatial Resolution Soil data: 250 m (SoilGrids) DEM: 30 m Output map scale: 1:1,500,000 land suitability sm_goats_suit_v2 features pasture SoilGrids rangeland forage grazing SWALIM somalia resilience livestock EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_irrtigated_rice_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for paddy (irrigated rice) cultivation across Somalia. The analysis was conducted using a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic factors. Suitability classes include S1 (highly suitable), S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable), reflecting varying levels of constraints for rice production. The evaluation considers rice grown under wet (paddy) and irrigated conditions, focusing on soil and climate suitability without explicitly accounting for water availability and irrigation infrastructure. Methodology The suitability analysis was conducted using a parametric land evaluation framework following FAO (1976) and Sys et al. (1991), where land characteristics are matched with crop requirements through a numerical rating system. A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil database (250 m resolution, machine learning-based) WoSIS soil profile database (over 230,000 profiles globally) Climate data (temperature and rainfall) Length of Growing Period (LGP – SWALIM, 2007) SRTM Digital Elevation Model (30 m) Due to limited ground soil data (only 71 out of 318 land units), SoilGrids machine learning-derived data was used to fill spatial gaps and derive key soil parameters across multiple depths. The evaluation considered: Climate factors (temperature, rainfall, LGP) Soil properties (texture, depth, salinity, fertility, drainage, organic carbon) Terrain characteristics (slope, elevation, erosion risk, aspect) A matching table approach was used, where: Each parameter was classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation produced a final suitability index Separate matching tables were developed for paddy rice (wet conditions) and irrigated rice systems, incorporating crop-specific thresholds for hydrology, soil, and climate conditions. Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – global soil database) WoSIS Soil Profile Database SRTM DEM (30 m) SWALIM Length of Growing Period (2007) Climate data (rainfall and temperature) Spatial Resolution Soil data: 250 m DEM: 30 m Output map scale: 1:1,500,000 Irrigated Rice crop suitability sm_irrtigated_rice_suit_v2 features land suitability agriculture SWALIM soil suitability somalia EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_maize_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for rainfed and irrigated maize cultivation across Somalia. The analysis was conducted using a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic factors. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable), reflecting varying levels of constraints for maize production. Methodology The suitability analysis was conducted using a parametric land evaluation framework following FAO (1976) and Sys et al. (1991), where land characteristics are matched with crop requirements through a numerical rating system. A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil database (250 m resolution) WoSIS soil profile database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) Due to limited ground soil data, where only 71 out of 318 land units are covered by existing soil profiles, SoilGrids machine learning-derived data was used to fill spatial gaps and complete the national coverage The evaluation considered: Climate factors (temperature, rainfall, LGP) Soil properties (texture, depth, salinity, fertility, drainage) Terrain characteristics (slope, elevation, erosion risk) Hydrological conditions (flooding risk, permeability, drainage) A matching table approach was used, where: Each parameter was classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation produced a final suitability index The analysis was performed for both rainfed and irrigated maize using crop-specific requirements and matching tables derived from literature and field experience Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – global soil database) WoSIS Soil Profile Database SRTM DEM (30 m) SWALIM Length of Growing Period (2007) Climate data (rainfall and temperature) irrigated agriculture land suitability sm_maize_suit_v2 crop suitability features rainfed agriculture SoilGrids SWALIM soil suitability somalia maize EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_mango_suit_v3_1 This dataset presents the suitability classification for mango production across Somalia based on soil, climate and terrain conditions. The analysis integrates soil characteristics, climatic variables, and topographic parameters to identify areas suitable for mango cultivation under both rainfed and irrigated conditions. The output provides spatial distribution of suitability classes to support agricultural planning and crop development. land suitability features Soil agriculture Mango FAO SWALIM Climate sm_mango_suit_v3_1 somalia Irrigation Rainfed EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_onion_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for irrigated onion cultivation across Somalia. The analysis was conducted using a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic factors. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable), reflecting varying levels of constraints for onion production. Methodology The suitability analysis was conducted using a parametric land evaluation framework following FAO (1976) and Sys et al. (1991), where land characteristics are matched with crop requirements through a numerical rating system. A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil database (250 m resolution) WoSIS soil profile database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) Due to limited ground soil data (covering only about 25% of land units), SoilGrids machine learning-derived data was used to fill spatial gaps and derive key soil parameters across multiple depths The evaluation considered: Climate factors (temperature, rainfall, LGP) Soil properties (texture, depth, salinity, fertility, drainage) Terrain characteristics (slope, elevation, erosion risk) A matching table approach was used, where: Each parameter was classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation produced a final suitability index The analysis was conducted under irrigated conditions, as onion cultivation requires irrigation and water availability was not included in the evaluation land suitability crop suitability features Soil agriculture Onion SWALIM Climate somalia sm_onion_suit_v2 Irrigation FAO EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_paddy_rice_suit_v3 This dataset represents the spatial distribution of soil and climate suitability for paddy (irrigated rice) cultivation across Somalia. The analysis was conducted using a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic factors. Suitability classes include S1 (highly suitable), S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable), reflecting varying levels of constraints for rice production. The evaluation considers rice grown under wet (paddy) and irrigated conditions, focusing on soil and climate suitability without explicitly accounting for water availability and irrigation infrastructure. Methodology The suitability analysis was conducted using a parametric land evaluation framework following FAO (1976) and Sys et al. (1991), where land characteristics are matched with crop requirements through a numerical rating system. A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil database (250 m resolution, machine learning-based) WoSIS soil profile database (over 230,000 profiles globally) Climate data (temperature and rainfall) Length of Growing Period (LGP – SWALIM, 2007) SRTM Digital Elevation Model (30 m) Due to limited ground soil data (only 71 out of 318 land units), SoilGrids machine learning-derived data was used to fill spatial gaps and derive key soil parameters across multiple depths. The evaluation considered: Climate factors (temperature, rainfall, LGP) Soil properties (texture, depth, salinity, fertility, drainage, organic carbon) Terrain characteristics (slope, elevation, erosion risk, aspect) A matching table approach was used, where: Each parameter was classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation produced a final suitability index Separate matching tables were developed for paddy rice (wet conditions) and irrigated rice systems, incorporating crop-specific thresholds for hydrology, soil, and climate conditions. Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – global soil database) WoSIS Soil Profile Database SRTM DEM (30 m) SWALIM Length of Growing Period (2007) Climate data (rainfall and temperature) Spatial Resolution Soil data: 250 m DEM: 30 m Output map scale: 1:1,500,000 irrigated agriculture land suitability crop suitability features rice sm_paddy_rice_suit_v3 SoilGrids SWALIM soil suitability somalia paddy EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_sesame_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for rainfed sesame cultivation across Somalia. The analysis was conducted using a parametric land evaluation approach based on FAO guidelines, integrating soil, climate, and topographic factors. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable), reflecting varying levels of constraints for sesame production. Methodology The suitability analysis was conducted using a parametric land evaluation framework following FAO (1976) and Sys et al. (1991), where land characteristics are matched with crop requirements through a numerical rating system. A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil database (250 m resolution) WoSIS soil profile database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) Due to limited ground soil data (covering only ~25% of land units), SoilGrids machine learning-derived data was used to fill spatial gaps and derive key soil parameters across multiple depths . The evaluation considered: Climate factors (temperature, rainfall, LGP) Soil properties (texture, depth, salinity, fertility, drainage) Terrain characteristics (slope, elevation, erosion risk) A matching table approach was used, where: Each parameter was classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation produced a final suitability index The analysis was performed under rainfed conditions, reflecting typical sesame production systems in Somalia. Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – global soil database) WoSIS Soil Profile Database SRTM DEM (30 m) SWALIM Length of Growing Period (2007) Climate data (rainfall and temperature) Spatial Resolution Soil data: 250 m DEM: 30 m Output map scale: 1:1,500,000 land suitability crop suitability features rainfed agriculture SoilGrids SWALIM sm_sesame_suit_v2 soil suitability somalia sesame EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_sheep_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for extensive grazing and forage production across Somalia. The analysis integrates soil, climate, and topographic parameters using a parametric land suitability evaluation framework based on FAO guidelines. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable). Methodology The suitability analysis was conducted using a parametric land evaluation approach following FAO (1976) and Sys et al. (1991), where land suitability is determined by matching environmental conditions with requirements for grazing and forage production. A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil data (250 m resolution, machine learning-based) WoSIS soil profile database Climate data (rainfall and temperature) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) Due to limited field soil data (~25% land unit coverage), SoilGrids was used to derive key soil properties across multiple depths . Each land unit was evaluated using: Climate factors (rainfall, temperature, LGP) Soil properties (texture, depth, salinity, fertility, drainage) Terrain characteristics (slope, elevation) A matching table approach was applied, where: Parameters were classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation produced a final suitability index The evaluation emphasizes biomass production potential and resilience to harsh conditions, which are critical for grazing systems. Final suitability classes: S2: Moderately suitable S3: Marginally suitable N1: Temporarily unsuitable N2: Permanently unsuitable Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – Global soil database) WoSIS Soil Profile Database SRTM DEM (30 m resolution) SWALIM Length of Growing Period (LGP, 2007) Climate data (rainfall and temperature) Spatial Resolution Soil data: 250 m (SoilGrids) DEM: 30 m Output map scale: 1:1,500,000 land suitability features pasture SoilGrids rangeland forage grazing SWALIM sm_sheep_suit_v2 somalia resilience livestock EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_sorghum_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for rainfed sorghum cultivation across Somalia. The analysis integrates soil, climate, and topographic parameters using a parametric land suitability evaluation framework based on FAO guidelines. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable). Methodology The suitability analysis was conducted using a parametric land evaluation approach following FAO (1976) and Sys et al. (1991), where land suitability is determined by matching crop requirements with environmental conditions. A national land database was developed by integrating: Somalia soil map (250,000 scale, SWALIM 2020) SoilGrids global soil data (250 m resolution, machine learning-based) WoSIS soil profile database Climate data (temperature and rainfall) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) Due to limited field soil data (only ~25% coverage of land units), SoilGrids was used to derive soil properties such as texture, pH, salinity, organic carbon, rooting depth, and nutrient content across multiple depths (0–200 cm) . Each land unit was characterized using: Climate variables (rainfall, temperature, LGP) Topographic variables (slope, elevation, aspect) Soil properties (texture, depth, salinity, fertility, drainage) A matching table approach was applied, where: Crop-specific thresholds for sorghum were defined Parameters were classified into suitability classes (S1–N2) Numerical ratings (0–100) were assigned Weighted aggregation was used to compute a final suitability index The evaluation specifically considers rainfed conditions, making rainfall and LGP critical limiting factors. Final suitability classes: S2: Moderately suitable S3: Marginally suitable N1: Temporarily unsuitable N2: Permanently unsuitable Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – Global soil database) WoSIS Soil Profile Database SRTM DEM (30 m resolution) SWALIM Length of Growing Period (LGP, 2007) Climate data (temperature and rainfall) Spatial Resolution Soil data: 250 m (SoilGrids) DEM: 30 m Output map scale: 1:1,500,000 land suitability features rainfed agriculture SoilGrids sorghum sm_sorghum_suit_v2 SWALIM climate suitability somalia soil suitability food security EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_surface_suit_v3_1 This dataset represents soil suitability for surface farming across selected agricultural areas in Somalia. The analysis evaluates the capacity of land to support crop production under surface farming practices, focusing on soil characteristics and land qualities that influence root development, moisture retention, and field operability. The assessment follows a parametric land evaluation approach based on FAO guidelines, where soil limitations are rated and aggregated to determine overall suitability. Suitability classes include S1 (Highly Suitable), S2 (Moderately Suitable), S3 (Marginally Suitable), N1 (Currently Not Suitable), and N2 (Permanently Not Suitable), reflecting varying degrees of constraints affecting surface-based cultivation. Methodology Land suitability for surface farming was assessed by considering land utilization requirements specific to surface-based agricultural practices. The process involved evaluating key soil characteristics and land qualities such as soil texture, depth, drainage conditions, workability, and moisture availability, which directly influence the effectiveness of surface farming. A parametric approach was used to rate soil limitations on a five-level scale, producing numerical scores based on root zone conditions and surface operability. The matching of land-use requirements with soil characteristics and land qualities determines the suitability of each land unit for surface farming. The resulting scores were aggregated to assign each land unit to a suitability class. The classes are: S1 – Highly Suitable: Land with no or only minor limitations for surface farming, with optimal soil conditions and minimal constraints. S2 – Moderately Suitable: Land with moderate limitations affecting productivity or requiring some management interventions. S3 – Marginally Suitable: Land with significant limitations that reduce productivity or increase input requirements. N1 – Currently Not Suitable: Land with severe limitations that prevent effective surface farming under current conditions but may be improved. N2 – Permanently Not Suitable: Land with extreme limitations such as very shallow soils, excessive salinity, or persistent waterlogging that make surface farming unfeasible. Data Sources Somalia Soil Map (SWALIM) SoilGrids (ISRIC) WoSIS Soil Database FABDEM (30 m) SRTM Digital Elevation Model FAO-SWALIM and UNDP datasets Spatial Resolution Soil data: ~250 m DEM (FABDEM): 30 m Surface Farming features agriculture sm_surface_suit_v3_1 SWALIM soil suitability somalia FAO Land Evaluation EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_tomato_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for tomato cultivation across Somalia. The analysis integrates soil, climate, and topographic parameters using a parametric land suitability evaluation framework based on FAO guidelines. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable). Methodology The suitability analysis was conducted using a parametric land evaluation approach following FAO (1976) and Sys et al. (1991), where land suitability is determined by matching crop requirements with environmental conditions. A national land database was developed by integrating: Somalia soil map (250,000 scale) SoilGrids global soil data (250 m resolution, machine learning-based) Climate data (temperature and rainfall) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) for slope, elevation, and aspect Each land unit was characterized using parameters such as soil texture, pH, salinity, organic carbon, rooting depth, slope, rainfall, and temperature. A matching table approach was applied, where: Each parameter was classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Parameters were weighted and aggregated into a final suitability index The final suitability classes derived were: S2: Moderately suitable S3: Marginally suitable N1: Temporarily unsuitable N2: Permanently unsuitable Tomato suitability is strongly influenced by soil drainage, salinity, and temperature conditions, which act as key limiting factors in several regions. Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – Global soil database) WoSIS Soil Profile Database SRTM DEM (30 m resolution) SWALIM Length of Growing Period (LGP, 2007) Climate data (temperature and rainfall) Spatial Resolution Soil data: 250 m (SoilGrids) DEM: 30 m Output map scale: 1:1,500,000 land suitability sm_tomato_suit_v2 features SoilGrids irrigation agriculture SWALIM climate suitability somalia soil suitability tomato EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_vetiveria_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for Vetiveria (Vetiver grass) cultivation across Somalia. The analysis integrates soil, climate, and topographic parameters using a parametric land suitability evaluation framework based on FAO guidelines. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable). Methodology The suitability analysis was conducted using a parametric land evaluation approach following FAO (1976) and Sys et al. (1991), where land suitability is determined by matching crop requirements with environmental conditions. A national land database was developed by integrating: Somalia soil map (250,000 scale) SoilGrids global soil data (250 m resolution, machine learning-based) Climate data (temperature and rainfall) Length of Growing Period (LGP) SRTM Digital Elevation Model (30 m) for slope, elevation, and aspect Each land unit was characterized using parameters such as soil texture, pH, salinity, organic carbon, rooting depth, slope, rainfall, and temperature. A matching table approach was applied, where: Each parameter was classified into suitability levels (S1–N2) Numerical ratings (0–100) were assigned Parameters were weighted and aggregated into a final suitability index The final suitability classes derived were: S2: Moderately suitable S3: Marginally suitable N1: Temporarily unsuitable N2: Permanently unsuitable Unlike other crops, Vetiveria is highly adaptable to harsh conditions (e.g., salinity, poor soils), which influences the classification results. Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – Global soil database) WoSIS Soil Profile Database SRTM DEM (30 m resolution) SWALIM Length of Growing Period (LGP, 2007) Climate data (temperature and rainfall) Spatial Resolution Soil data: 250 m (SoilGrids) DEM: 30 m Output map scale: 1:1,500,000 Vetiver grass land suitability features SoilGrids forage soil conservation SWALIM erosion control somalia sm_vetiveria_suit_v2 Vetiveria EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:sm_watermelon_suit_v2 This dataset represents the spatial distribution of soil and climate suitability for watermelon cultivation across Somalia. The analysis integrates soil, climate, and topographic parameters using a parametric land suitability evaluation framework based on FAO guidelines. Suitability classes include S2 (moderately suitable), S3 (marginally suitable), N1 (temporarily unsuitable), and N2 (permanently unsuitable). Methodology The suitability analysis was conducted using a parametric land evaluation approach following FAO (1976) and Sys et al. (1991). Land suitability was determined by matching crop requirements with soil, climate, and terrain characteristics. A national soil database was developed by integrating: Existing Somalia soil map (250,000 scale) SoilGrids global soil data (250 m resolution, machine learning-based) Climate data (temperature and rainfall) Length of Growing Period (LGP) Digital Elevation Model (SRTM 30 m) for slope, elevation, and aspect Each land unit was characterized using key parameters including soil texture, pH, salinity, organic carbon, rooting depth, slope, rainfall, and temperature. A matching table approach was applied, where each parameter was: Classified into suitability levels (S1–N2) Assigned numerical ratings (0–100) Weighted and combined to produce a final suitability index The final suitability classes were derived as: S2: Moderately suitable S3: Marginally suitable N1: Temporarily unsuitable N2: Permanently unsuitable The analysis assumes irrigation availability and does not explicitly account for water resource constraints. Data Sources Somalia Soil Map (SWALIM, 2020) SoilGrids (ISRIC – Global soil database) WoSIS Soil Profile Database SRTM DEM (30 m resolution) SWALIM Length of Growing Period (LGP, 2007) Climate data (temperature and rainfall) land suitability features SoilGrids agriculture sm_watermelon_suit_v2 crop suitability SWALIM climate suitability somalia 1:250000 watermelon EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other text/xml other other geonode:soil_100k_n_faoswalim This dataset is about a semi detailed soil map at a scale of 1:100,000 for Dur Dur and Gibeley areas in north Somalia features soil_100k_n_faoswalim EPSG:4326 CRS:84 43.01101391000003 44.46210107700006 9.166527244000065 10.689734255000076 other other other other text/xml other other geonode:soil_100k_s_faoswalim This datasets shows a semi detailed soil map at a scale of 1:100,000 for for Juba and Shabelle Riverine Areas in south Somalia. features soil_100k_s_faoswalim EPSG:4326 CRS:84 41.89169460000005 46.150032544000055 -0.266810086999953 5.060045358000025 other other other other text/xml other other geonode:soil_50k_n_faoswalim This dataset is about a detailed soil map at a scale of 1:50,000 for north western part of Somaliland in Somalia. features soil_50k_n_faoswalim EPSG:4326 CRS:84 43.01101303100006 44.46210479700005 9.166513443000042 10.12070465100004 other other other other text/xml other other geonode:soil_jowhar_faoswalim_248b1dc54593c5f1150f61ba26597ce9 This dataset is about a semi detailed soil map at a scale of 1:100,000 for Jowhar areain Somalia. Data is produced by FAO SWALIM (Somalia Water and Land Information Management Project) features soil_jowhar_faoswalim_248b1dc54593c5f1150f61ba26597ce9 EPSG:4326 CRS:84 45.49910802100004 45.602213807000055 2.688847342000031 2.803132805000075 other other other other text/xml other other geonode:soil_simplified_faoswalim2012_07f65f9b2301611e18ba84bd51d3a9e7 SWALIM has conducted numerous surveys of the soil in different parts of Somalia which is resulted in compiling a national soil database for Somalia soil_simplified_faoswalim2012_07f65f9b2301611e18ba84bd51d3a9e7 features EPSG:4326 CRS:84 40.98863220800007 51.413032427000076 -1.662052869999968 11.985202787000048 text/xml other other other other other other geonode:som_adm0_country_boundary_unocha Somalia administrative boundary , admin 0 (Country of Somalia). The source of this data is United Nation Development Programme (UNEP) 1998. UNOCHA is a contributor. features som_adm0_country_boundary_unocha EPSG:4326 CRS:84 40.994316999000034 51.413032532000045 -1.664914401999908 11.985202789000084 other other other other text/xml other other geonode:som_adm1_states_unocha features som_adm1_states_unocha EPSG:4326 CRS:84 40.98863224200005 51.415153485000076 -1.65423822799994 11.988364065000042 other other other other text/xml other other geonode:som_adm2_regions_unocha Somalia country administrative boundary admin2 (Regionsof Somalia). The source of this data is United Nation Development Programme (UNEP) 1998. UNOCHA is contributor. features som_adm2_regions_unocha EPSG:4326 CRS:84 40.994316999000034 51.413032532000045 -1.664914401999908 11.985202789000084 other other other other text/xml other other geonode:som_adm3_districts_unocha Somalia country administrative boundary admin2 (Districts of Somalia). The source of this data is United Nation Development Programme (UNEP) 1998. UNOCHA is contributor. features som_adm3_districts_unocha EPSG:4326 CRS:84 40.994316999000034 51.413032532000045 -1.664914401999908 11.985202789000084 other other other other text/xml other other geonode:som_cropland_gfsad_30m_2015 The GFSAD30 is a NASA funded project to provide high resolution global cropland data and their water use that contributes towards global food security in the twenty-first century. The Global Food Security-support Analysis Data (GFSAD) 30meter Cropland Extent Africa Nominal 2015 products are derived through multi-sensor remote sensing data (e.g., Landsat, MODIS, AVHRR), secondary data, and field-plot data and aims at documenting cropland dynamics from 1990 to 2017 features som_cropland_gfsad_30m_2015 EPSG:4326 CRS:84 41.005362880000064 50.40051309200004 -1.628016788999958 11.284860871000035 other other other other text/xml other other geonode:som_drainage_network_extracted_from_osm Drainage network extracted from OpenStreetMap. For more information about the data, visit --> https://wiki.openstreetmap.org/wiki/Tag:waterway%3Driver features som_drainage_network_extracted_from_osm EPSG:4326 CRS:84 40.989100816752085 51.3211743 -1.329330978168852 11.9604277 other other other other other text/xml other geonode:som_fields_2025_2024_conf03_ha02 This dataset contains AI-derived agricultural field boundary polygons for Somalia, generated from the Fields of The World (FTW) Global Field Boundary Dataset using the PRUE field boundary segmentation model. The FTW global product provides 10 m agricultural field boundary predictions for 2024 and 2025, produced from Sentinel-2 imagery using machine-learning-based field boundary delineation methods. The PRUE model is designed for scalable agricultural field boundary extraction and aims to reduce common large-area mapping artefacts such as tiling effects and inconsistent boundary predictions. For Somalia, tile-based field boundary datasets for 2024 and 2025 were downloaded and merged into national-level datasets. The 2024 and 2025 layers were then combined where gaps existed between the two annual datasets, creating a more complete national field boundary layer. The merged dataset was clipped to the national boundary of Somalia, followed by random visual and spatial checks to assess general consistency and identify obvious artefacts. A confidence-based filtering step was applied to improve the suitability of the dataset for operational monitoring. Based on review of both mean and minimum confidence values, a confidence threshold of 0.3 was selected as a practical compromise between retaining useful field boundary features and removing lower-confidence predictions. All polygons below this confidence threshold were removed. In addition, polygons smaller than 0.2 hectares were excluded to reduce noise and improve suitability for national and sub-national agricultural monitoring purposes. The resulting dataset should be considered a screening, monitoring, and planning layer for agricultural analysis in Somalia. It may support crop monitoring, field-based agricultural statistics, seasonal assessments, land-use analysis, and further validation exercises. However, it is not an authoritative dataset, not a legal cadastre, and must not be used to determine land ownership, legal parcel boundaries, tenure rights, taxation, compensation, or any other cadastral or legal purpose. features som_fields_2025_2024_conf03_ha02 EPSG:4326 CRS:84 41.00064769408142 49.06129093976563 -1.64159876099201 10.77495928541019 other other other other text/xml other other other other other other text/xml other other geonode:som_flood_prone_areas_20200 This layer shows flood prone areas derived from radar images (Sentinel 1) and optical images (Sentinel 2, Landsat, and Maxar VHR images) acquired during the period 2018-2020. The analysis was performed by FAO Somalia Water and Land Information Management (SWALIM). river floods somalia shabelle features prone 2020 som_flood_prone_areas_20200 juba EPSG:4326 CRS:84 42.07852136906297 45.74236120600489 -0.267397575126267 5.019687921174807 other other other other text/xml other other geonode:som_flood_prone_areas_faoswalim2018 Somalia experiences two types of flooding: river floods and flash floods. River floods occur along the Juba and Shabelle rivers in Southern Somalia, whereas flash floods are common along the intermittent streams in the northern part of the country.in the recent past, the country has experienced an increasing severity and frequency of floods. The historically most recent severe floods were those of the Deyr in 1961, 1977, 1997, and 2006, and the floods of the Gu in 1981 and 2005. These floods resulted in human casualties and major economic damage.Whereas flash floods in Somalia result from localised rains, river flooding along the Juba and Shabelle rivers are primarily due to drainage from catchment areas located in the Ethiopian highlands, which normally experience heavier and more frequent rainfall than what occurs in Somalia. som_flood_prone_areas_faoswalim2018 somalia shabelle 2018 features prone river juba EPSG:4326 CRS:84 42.07852136900004 45.742361206000055 -0.105086470999936 5.011309427000072 other other other other text/xml other other geonode:som_flood_prone_areas_merge_of_historical0 This is a merge of historical flood extents. See "SOM Juba Shabelle River Floods" layers: Deyr 2023, Gu 2021, Gu 2020, Hagaa 2020, Gu 2019, Deyr 2019, Gu 2018, Deyr 2018, Gu 2016, Gu 2015, Deyr 2013 floods som_flood_prone_areas_merge_of_historical0 somalia features prone EPSG:4326 CRS:84 40.99564999904828 48.34046489723727 -1.623307531917021 6.010755708009583 other other other other text/xml other other geonode:som_flood_prone_areas_merge_of_historical0b4a617fc9d78 This is a merge of historical flood extents. See "SOM Juba Shabelle River Floods" layers: Deyr 2023, Gu 2021, Gu 2020, Hagaa 2020, Gu 2019, Deyr 2019, Gu 2018, Deyr 2018, Gu 2016, Gu 2015, Deyr 2013 floods somalia shabelle som_flood_prone_areas_merge_of_historical0b4a617fc9d78 features river juba EPSG:4326 CRS:84 40.99564999904828 48.34046489723727 -1.623307531917021 6.010755708009583 other other other other text/xml other other geonode:som_flooded_agriculture_areas_faoswalim2018 Somalia river floods occur along the Juba and Shabelle rivers in Southern Somalia. The layer shows the agricultural areas affected by floods in 2018. floods somalia agriculture shabelle som_flooded_agriculture_areas_faoswalim2018 2018 features river juba EPSG:4326 CRS:84 42.08466599800005 45.742361206000055 0.289786860000049 4.998042270000042 other other other other text/xml other other geonode:som_floods_elnino_deyr_2023 This data contains modified flood extent from:\r\n1. Global Flood Monitoring retrieved on 14/11/2023,\r\n2. World View 3 Image of 16/11/2023,UNOSAT Analysis 05 Nov - 03 Dec 2023. Sentinel 2 image of (15,20,30)/11 and (5,10) /12/ 2023. The Flood Extent may be smaller than the actual due to cloud cover on analysis images that hindered assessment in some areas and limitations of radar to detect flooding within urban areas 2023 floods somalia shabelle features river juba som_floods_elnino_deyr_2023 el nino EPSG:4326 CRS:84 40.99564999904828 48.34046489723727 -1.623307531917021 6.010755708009583 other other other other text/xml other other geonode:som_functioning_boreholes_2010 Somalia Functioning Boreholes as of 2010 som_functioning_boreholes_2010 somalia features EPSG:4326 CRS:84 41.33650000000006 51.07222200000007 0.950080000000071 11.814166000000057 other other other other text/xml other other geonode:som_gedo_temporary_water_points_fao_igad During the implementation of the FAO-IGAD partnership, SWALIM developed a trans-boundary land cover map of the Gedo region. In addition to this activity, SWALIM also produced a map of 1270 water ponds which are seasonal. features som_gedo_temporary_water_points_fao_igad EPSG:4326 CRS:84 40.99177461100004 42.734553756000025 2.075004162000028 4.242148429000054 other other other other text/xml other other geonode:som_hydro1k_gtopo30_basins HYDRO1k is a geographic database developed to provide comprehensive and consistent global coverage of topographically derived data sets, including streams, drainage basins and ancillary layers derived from the USGS' 30 arc-second digital elevation model of the world (GTOPO30). HYDRO1k provides a suite of geo-referenced data sets, both raster and vector, which will be of value for all users who need to organize, evaluate, or process hydrologic information on a continental scale developed at the U.S. Geological Survey's EROS Center, the HYDRO1k project's goal is to provide to users, on a continent by continent basis, hydrologically correct DEMs along with ancillary data sets for use in continental and regional scale modeling and analyses. features som_hydro1k_gtopo30_basins EPSG:4326 CRS:84 39.47467804000007 51.45048904400005 -2.078907012999934 11.996755600000029 other other other other other text/xml other geonode:som_hydro_crossborder_basins Somalia cross boundary basin data, is a geographic database developed to provide comprehensive and consistent global coverage of topographically derived data sets, including streams, drainage basins and ancillary layers derived from the USGS' 30 arc-second digital elevation model of the world (GTOPO30). HYDRO1k provides a suite of geo-referenced data sets, both raster and vector, which will be of value for all users who need to organize, evaluate, or process hydrologic information on a continental scale developed at the U.S. Geological Survey's EROS Center, the HYDRO1k project's goal is to provide to users, on a continent by continent basis, hydrologically correct DEMs along with ancillary data sets for use in continental and regional scale modeling and analyses. som_hydro_crossborder_basins features EPSG:4326 CRS:84 36.27611069400007 51.33075241800003 -1.810834270999976 11.996755415000052 other other other other text/xml other other geonode:som_idps_unhcr_2007_7f99446ce247d4f6f512eb44350f06ba Somalia IDPs camp locations compiled by UNHCR 2007 som_idps_unhcr_2007_7f99446ce247d4f6f512eb44350f06ba features EPSG:4326 CRS:84 43.63220000000007 49.19791900000007 2.001183000000026 11.286408000000051 other other other other text/xml other other geonode:som_irrigation_canals_faoswalim2018 In pre-war Somalia (before 1990), large-scale irrigation schemes existed along the Juba and Shabelle basins. These controlled irrigation systems consisting of barrages, canals and other infrastructure, were constructed in the middle and lower reaches of both rivers. The canal system comprised primary and secondary canals, and numerous tertiary canals, with water flow controlled by barrages or weirs. Pumped irrigation systems also existed, especially along the Juba river where large pumps were used to take water from the river to other network of canals. Before the collapse of the government, the Somali Ministry of Agriculture estimated that 112,950ha was under controlled irrigation, while 110,000ha was under flood recession irrigation (cultivation along the edge of rivers or other water bodies using water from receding floods), giving a total irrigated area in the country of 222,950ha. Currently, the majority of this infrastructure is not functioning, and the area under irrigation has been significantly reduced som_irrigation_canals_faoswalim2018 features EPSG:4326 CRS:84 42.73301826900007 45.68179011900003 0.164672852000024 4.969430761000069 other other other other text/xml other other geonode:som_irrigation_schemes_faoswalim0 In pre-war Somalia (before 1990), large-scale irrigation schemes existed along the Juba and Shabelle basins. These controlled irrigation systems consisting of barrages, canals and other infrastructure, were constructed in the middle and lower reaches of both rivers. Before the collapse of the government, the Somali Ministry of Agriculture estimated that 112,950ha features som_irrigation_schemes_faoswalim0 EPSG:4326 CRS:84 43.69811050700008 45.60011837600007 1.15576261800004 4.828188038000064 other other other other text/xml other other geonode:som_jilib_charcoal_production_faoswalim The data of charcoal production sites in Jilib - Somalia is produced by Somalia Water and Land Information Management (SWALIM) project. Very high resolution satelite images of 2011 - 2013 were used for mapping the charcoal production sites. features som_jilib_charcoal_production_faoswalim EPSG:4326 CRS:84 42.860742482000035 42.87975531400008 0.520925274000035 0.532836479000025 other other other other text/xml other other geonode:som_juba_river_flooding_as_at_10th_nov_2019 juba floods somalia features 2019 river som_juba_river_flooding_as_at_10th_nov_2019 EPSG:32638 CRS:84 42.11526662212712 42.80374668683539 -0.26743428823423593 4.165473062598729 other other other other text/xml other other geonode:som_juba_shabelle_flooding_gu_2020 This data was produced through visual interpretation of Sentinel 1 and Sentinel 2 satellite images acquired between April and June 2020 floods somalia som_juba_shabelle_flooding_gu_2020 shabelle features gu 2020 river juba EPSG:32638 CRS:84 42.13419985486067 45.58338056334624 -0.03518486123903071 5.01041723871916 other other other other text/xml other other geonode:som_juba_shabelle_floods_gu_2024 This data was produced through visual interpretation of Sentinel 2 and Airbus images.\r\nThe Flood Extent may be smaller than the actual due to cloud cover on analysis images that hindered assessment in some areas and limitations of radar to detect flooding within urban areas features som_juba_shabelle_floods_gu_2024 EPSG:4326 CRS:84 42.04390694745172 45.719604176212506 -0.168093853251503 5.010350753189595 other other other other text/xml other other geonode:som_juba_shabelle_river_breakages_august_2024 FAO-SWALIM has updated the status of the river breakages along the Juba and Shabelle Rivers using available Very High Resolution (VHR) satellite imagery and a Digital Elevation Model (DEM). Five types of breakages have been identified; Open, Overflow, Canal Breakage, Canal Intake Flooding and Closed with sandbags. The open breakages are those that are currently open as observed on the latest VHR image available. All the observations reported refers to the latest suitable VHR satellite image available, which is indicated in the online database. A legend/Key for further explanation of the different types of breakages is provided.\r\n\r\nAlong the Shabelle river, a total of 171 Open breakage points, 2 Canal Breakages, 51 Canal flooding points, 323 Overflow points and 17 points closed with sandbags have been identified while on the Juba river 104 Open points, 1 Canal Breakage, 16 Canal flooding points, 83 Overflow points and 1 point closed with sandbags have been identified. Users are advised that the methodology is biased towards Remote Sensing (RS) interpretation with only limited “ground truthing” due to access constraints. Open breakages might have been omitted in some cases where satellite images may not have been very clear (e.g. heavy cloud cover) or were not available. For questions or further clarifications related to the reports, you can contact us by sending an email to SWALIM@fao.org. features som_juba_shabelle_river_breakages_august_2024 EPSG:4326 CRS:84 42.06270900000004 45.67867000000007 -0.096365999999932 4.892940000000067 text/xml other other other other other other geonode:som_juba_shabelle_river_breakages_march_2025 FAO-SWALIM has updated the status of the river breakages along the Juba and Shabelle Rivers using available Very High Resolution (VHR) satellite imagery and a Digital Elevation Model (DEM). Five types of breakages have been identified; Open, Overflow, Canal Breakage, Canal Intake Flooding and Closed with sandbags. The open breakages are those that are currently open as observed on the latest VHR image available. All the observations reported refers to the latest suitable VHR satellite image available, which is indicated in the online database. A legend/Key for further explanation of the different types of breakages is provided.\r\n\r\nAlong the Shabelle river, a total of 98 Open breakage points, 2 Canal Breakages, 56 Canal flooding points, 94 Overflow points and 5 points closed with sandbags have been identified while on the Juba river 109 Open points, 1 Canal Breakage, 20 Canal flooding points, 87 Overflow points and 1 point closed with sandbags have been identified. Users are advised that the methodology is biased towards Remote Sensing (RS) interpretation with only limited “ground truthing” due to access constraints. Open breakages might have been omitted in some cases where satellite images may not have been very clear (e.g. heavy cloud cover) or were not available. For questions or further clarifications related to the reports, you can contact us by sending an email to SWALIM@fao.org. features som_juba_shabelle_river_breakages_march_2025 EPSG:4326 CRS:84 42.06270899 45.67867 -0.09636627 4.89294 other other other other text/xml other other geonode:som_juba_shabelle_river_floods_deyr_2013 This data was produced through visual interpretation of Landsat 8 satellite images acquired between 25th September 2013 – 28th November 2013 features som_juba_shabelle_river_floods_deyr_2013 EPSG:4326 CRS:84 42.08809447589613 45.69037808363544 -0.078708971304422 4.18193544803546 other other other other text/xml other other geonode:som_juba_shabelle_river_floods_deyr_20180_0rjpvzt This data was produced through visual interpretation of Sentinel 2 satellite images acquired between 20th October 2018– 04th November 2018 floods somalia shabelle som_juba_shabelle_river_floods_deyr_20180_0rjpvzt features river juba EPSG:4326 CRS:84 42.220535747233704 45.70990331307846 0.403686028704609 4.440846822141557 other other other other text/xml other other geonode:som_juba_shabelle_river_floods_deyr_2019 This data was produced through visual interpretation of Sentinel 2 satellite images acquired between 10th October 2019 to 16th November 2019. floods somalia shabelle deyr som_juba_shabelle_river_floods_deyr_2019 features 2019 river juba EPSG:4326 CRS:84 42.08899112364861 45.71781748826976 -0.08877573613637 5.01130942700081 other other other other text/xml other other geonode:som_juba_shabelle_river_floods_gu_2015 This data was produced through visual interpretation of Landsat 8 satellite images acquired between 8th April 2015– 26th May 2015 features som_juba_shabelle_river_floods_gu_2015 EPSG:4326 CRS:84 42.08992861188421 45.62557907256923 -0.231107933672496 4.668334960946742 other other other other text/xml other other geonode:som_juba_shabelle_river_floods_gu_2016 This data was produced through visual interpretation of Sentinel 2 satellite images acquired between 26th May 2016 -13th June 2016 features som_juba_shabelle_river_floods_gu_2016 EPSG:4326 CRS:84 42.05294953470028 45.72571732483375 -0.151985149430632 5.010727509187627 other other other other text/xml other other geonode:som_juba_shabelle_river_floods_gu_20180 This data was produced through visual interpretation of Sentinel 2 satellite images acquired between 23rd April 2018 to 10th May 2018 floods somalia shabelle som_juba_shabelle_river_floods_gu_20180 2018 features gu river juba EPSG:4326 CRS:84 42.078521369147836 45.74236120601893 -0.105086471241576 5.070241835791818 other other other other text/xml other other geonode:som_juba_shabelle_river_floods_gu_2019 This data was produced through visual interpretation of Sentinel 2 satellite images acquired between 3rd May 2019 to 14th June 2019. floods somalia shabelle features gu som_juba_shabelle_river_floods_gu_2019 2019 river juba EPSG:4326 CRS:84 42.232472919532825 45.60881497473275 -0.071370646999924 4.976355666613642 other other other other text/xml other other geonode:som_juba_shabelle_river_floods_gu_2021 This data was produced through visual interpretation of Sentinel 2 satellite images acquired between 1st May - 31st August 2021. Additionally, we complemented the data with Kompsat 5 satellite images images for the month of May 2021 floods somalia shabelle features river som_juba_shabelle_river_floods_gu_2021 juba EPSG:4326 CRS:84 42.68606331186561 45.67063194132099 0.105532956640212 4.808526984004745 other other other other text/xml other other geonode:som_juba_shabelle_river_floods_gu_2021a28bfef41306 This data was produced through visual interpretation of Sentinel 2 satellite images acquired between 1st May - 31st August 2021.Additionally, we complemented the data with Kompsat 5 satellite images images for the month of May 2021 floods somalia som_juba_shabelle_river_floods_gu_2021a28bfef41306 shabelle 2021 features gu river juba EPSG:4326 CRS:84 42.68606331186561 45.67063194132099 0.105532956640212 4.808526984004745 other other other other text/xml other other geonode:som_land_agrisuitability_citrus_s_faoswalim0 The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for Citrus in selected areas in southern part of Somalia (Juba and Shabelle riverine areas). features som_land_agrisuitability_citrus_s_faoswalim0 EPSG:4326 CRS:84 41.89169460000005 46.150032544000055 -0.266810086999953 5.060045358000025 other other other other text/xml other other geonode:som_land_agrisuitability_cowpea_n_faoswalim0 The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for Cowpea in selected areas inNorthern part of Somalia (Garbiley and Boroma areas in Somaliland) features som_land_agrisuitability_cowpea_n_faoswalim0 EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:som_land_agrisuitability_maize_n_faoswalim0 The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for Maize in selected areas in Northern part of Somalia (Garbiley and Boroma areas in Somali land) features som_land_agrisuitability_maize_n_faoswalim0 EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other other text/xml other geonode:som_land_agrisuitability_rice_s_faoswalim0 The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for Rice in selected areas inSouthern part of Somalia (Juba and Shabelle riverine areas). features som_land_agrisuitability_rice_s_faoswalim0 EPSG:4326 CRS:84 41.89169460000005 46.150032544000055 -0.266810086999953 5.060045358000025 other other other other text/xml other other geonode:som_land_agrisuitability_rice_s_faoswalim0da8c37a7f756 The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for Rice in selected areas inSouthern part of Somalia (Juba and Shabelle riverine areas). features som_land_agrisuitability_rice_s_faoswalim0da8c37a7f756 EPSG:4326 CRS:84 41.89169460000005 46.150032544000055 -0.266810086999953 5.060045358000025 other other other other text/xml other other geonode:som_land_agrisuitability_sorghumr1_n_faoswali The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for SorghumR1 in selected areas in Northern part of Somalia (Garbiley and Boroma areas in Somaliland) features som_land_agrisuitability_sorghumr1_n_faoswali EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:som_land_agrisuitability_sorghumr2_n_faoswali The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for SorghumR2in selected areas in northern part of Somalia (Garbiley and Boroma areas in Somaliland) features som_land_agrisuitability_sorghumr2_n_faoswali EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:som_land_agrisuitability_sugarcane_s_faoswali The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for Sugarcane in selected areas in southern part of Somalia (Juba and Shabelle riverine areas). features som_land_agrisuitability_sugarcane_s_faoswali EPSG:4326 CRS:84 41.89169460000005 46.150032544000055 -0.266810086999953 5.060045358000025 other other other other text/xml other other geonode:som_land_degradation_adeso_faoswalim2016 FAO-SWALIM has carried out a national assessment in Somalia to establish the types, extent, and causes of land degradation in the country. SWALIM also studied several control efforts carried out by Somalis and their development partners, documented opportunities for upscaling successful control measures, and made recommendations for implementing land degradation monitoring in the country. features som_land_degradation_adeso_faoswalim2016 EPSG:4326 CRS:84 46.16413400000005 51.166968000000054 6.880807000000061 11.958956000000057 other other other other text/xml other other geonode:som_land_degradation_care_faoswalim2015 FAO-SWALIM has carried out a national assessment in Somalia to establish the types, extent, and causes of land degradation in the country. SWALIM also studied several control efforts carried out by Somalis and their development partners, documented opportunities for upscaling successful control measures, and made recommendations for implementing land degradation monitoring in the country. features som_land_degradation_care_faoswalim2015 EPSG:4326 CRS:84 48.217400000000055 50.16444000000007 7.910690000000045 10.005573000000027 other other other other text/xml other other geonode:som_land_degradation_faoswalim The data of land degradation of Somalia is produced by The Food and Agriculture Organization’s Somalia Water and Land Information Management (FAO-SWALIM) project features som_land_degradation_faoswalim EPSG:4326 CRS:84 40.989507685000035 51.41412686700005 -1.652780052999958 11.988650282000037 other other other other text/xml other other geonode:som_land_forestsuitability_acacianilotica_s_f The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species Acacia Nilotica in selected areas in southernpart of Somalia (Juba and Shabelle riverine areas). features som_land_forestsuitability_acacianilotica_s_f EPSG:4326 CRS:84 41.891693115000066 46.15003204300007 -0.266810088999932 5.060045242000058 other other other other text/xml other other geonode:som_land_forestsuitability_acaciatortilis_n_f The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species Acacia Tortilis in selected areas in northern part of Somalia (Garbiley and Boroma areas in Somaliland). features som_land_forestsuitability_acaciatortilis_n_f EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other other text/xml other geonode:som_land_forestsuitability_azardirachtaindica The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species Azardirachta Indica in selected areas innorthern part of Somalia (Garbiley and Boroma areas in Somaliland). features som_land_forestsuitability_azardirachtaindica EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:som_land_forestsuitability_azardirachtaindica0 The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species Azardirachta Indicain selected areas in southern part of Somalia (Juba and Shabelle riverine areas). features som_land_forestsuitability_azardirachtaindica0 EPSG:4326 CRS:84 41.891693115000066 46.15003204300007 -0.266810088999932 5.060045242000058 other other other other text/xml other other geonode:som_land_forestsuitability_casuarinaequisetif The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species Casuarina Equisetifolia in selected areas in northern part of Somalia (Garbiley and Boroma areas in Somaliland). features som_land_forestsuitability_casuarinaequisetif EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:som_land_forestsuitability_conocarpuslancifol The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species Conocarpus Lancifolius in selected areas innorthern part of Somalia (Garbiley and Boroma areas in Somaliland). features som_land_forestsuitability_conocarpuslancifol EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:som_land_forestsuitability_conocarpuslancifol0 The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species Conocarpus Lancifoliusin selected areas in southern part of Somalia (Juba and Shabelle riverine areas). features som_land_forestsuitability_conocarpuslancifol0 EPSG:4326 CRS:84 41.891693115000066 46.15003204300007 -0.266810088999932 5.060045242000058 other other other other text/xml other other geonode:som_land_forestsuitability_doberaglabra_n_fao The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species Dobera Glabrain selected areas innorthern part of Somalia (Garbiley and Boroma areas in Somaliland). features som_land_forestsuitability_doberaglabra_n_fao EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:som_land_forestsuitability_faidherbiaalbida_n The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species Faidherbia Albidain selected areas innorthern part of Somalia (Garbiley and Boroma areas in Somaliland). features som_land_forestsuitability_faidherbiaalbida_n EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:som_land_forestsuitability_n_faoswalim The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species in selected areas innorthern part of Somalia (Garbiley and Boroma areas in Somaliland). features som_land_forestsuitability_n_faoswalim EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 other other other other text/xml other other geonode:som_land_forestsuitability_s_faoswalim The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for forestry species in selected areas in southern part of Somalia (Juba and Shabelle riverine areas). features som_land_forestsuitability_s_faoswalim EPSG:4326 CRS:84 41.89169460000005 46.15003254800007 -0.266810086999953 5.060045358000025 other other other other text/xml other other geonode:som_land_grazesuitability_camels_s_faoswalim The data defines the capacity of the study area to support specific land use types. It gives the suitable areas for animal grazing (Camels) in selected areas insouthern part of Somalia (Juba and Shabelle riverine areas). features som_land_grazesuitability_camels_s_faoswalim EPSG:4326 CRS:84 41.89169460000005 46.150032544000055 -0.266810086999953 5.060045358000025 other other other other text/xml other other geonode:som_landcover_oasisfarms_faoswalim Oasis farming is very common in the northern part of Somalia. Crop production by irrigation from springs and well popularly known as Oasis farming the main sources of livelihood in these areas. features som_landcover_oasisfarms_faoswalim EPSG:4326 CRS:84 47.504318271000045 51.07687740700004 7.977103795000062 11.37182647000003 other other other other text/xml other other geonode:som_landcover_prosopispoints_ne_faoswalim2017 GPS Points for Prosopis Tree collected from Somaliland.FAO SWALIM has been mapping and studying the spread of Prosopis in Somalia. More recently, a survey was carried in Januray 2017 together with the Somaliland Ministry of Environment and Rural Development to map out the extent of the spread of Proposis in Somaliland. Five areas of interest were selected covering the main landform units of Somaliland that include flat lying areas, plateaus, hills, mountain ranges and coastal areas. The climate of these landscapes vary from desert (annual rainfall of 100mm and temperature of 28-35 oC) in the coastal areas to semi humid (annual rainfall of 500 - 600 mm annual rainfall and temperature of 20-22 °C) in the mountain ranges.\r\nThe survey observed that despite the extremely dry condition; Prosopis plants were exceptionally green and resistant to drought and were often flowering and with pods in most of the areas. Prosopis was found growing as trees or shrubs and also forms pure stand of forest thickets in the invaded rangelands and cropland. It was also scattered as shrubs in stony or gravelly surfaces inter growing with cactus. In the wetter alluvial deposits flanking the watercourses in the northern escarpment of the Golis Mountain, it was found to form very dense impenetrable thickets. features som_landcover_prosopispoints_ne_faoswalim2017 EPSG:4326 CRS:84 43.19238888900003 45.76041666700007 9.364388889000054 10.432416667000041 other other other other other other text/xml geonode:som_landforms_faoswalim20080 Data of landforms have been produced from FAO Africover 2000, combined with geomorphometry. Data on topography from NASA SRTM 90 m. features som_landforms_faoswalim20080 EPSG:4326 CRS:84 40.99214172400008 51.41272354100005 -1.667189716999928 11.99218845400003 other other other other text/xml other other geonode:som_landsat8_imageindex_granule Image Index:it contains feature classes that contain information about the path/row, scene boundaries and the geographic coordinates of the imageries acquired by satellites for Somalia. These indices help in identifying the numbers of images covering Somaliaand are easy guides for identifying searching for the required images. features som_landsat8_imageindex_granule EPSG:4326 CRS:84 39.17280000000005 52.90050000000008 -2.326979999999935 12.450900000000047 other other other other text/xml other other geonode:som_landscape_nw_faoswalim20070 The landscape data of north western part of Somalia defines the classes of topography and landscape units based on SRTM 90 m. features som_landscape_nw_faoswalim20070 EPSG:4326 CRS:84 43.01092683100006 44.46210397400006 9.16651315200005 10.689748205000058 text/xml other other other other other other geonode:som_landscape_s_faoswalim20070 The landscape data of southern part of Somalia defines the classes of topography and landscape units based on SRTM 90 m. features som_landscape_s_faoswalim20070 EPSG:4326 CRS:84 41.89169460000005 46.150032544000055 -0.266810086999953 5.060045358000025 other other other other text/xml other other geonode:som_landuse_suitability_faoswalim0 Landusesuitability assessment is the process of estimating the potential of land for alternative kinds of landuse. SWALIM has undertaken detailed land suitability studies and produced a set of land suitability datafor different land usesin Somalia. features som_landuse_suitability_faoswalim0 EPSG:4326 CRS:84 40.989507685000035 51.41412686700005 -1.652780052999958 11.988650282000037 other other other other text/xml other other geonode:som_landuse_system_faoswalim2007 This landuse systems data is produced from FAO Landcover data for Somalia 2000. features som_landuse_system_faoswalim2007 EPSG:4326 CRS:84 40.989507685000035 51.41412686700005 -1.652780052999958 11.988650282000037 other other other other text/xml other other geonode:som_livestock_trade_routes_aug2022 The Livestock Trade Routes were prepared by combining field Livestock reports on livestock trade routes from the villages to the markets, with the Somalia Roads datasets retrieved from Open Street Maps and the Secondary roads authored by WFP and ADA 2010. The dataset contains a name column that indicates the route from and the the destination market e.g Tallex-Garoowe. In places where a primary road exist, the route was selected however in areas where it is non-existent, the secondary routes was selected instead. The routes are updated as new field data becomes available. features som_livestock_trade_routes_aug2022 EPSG:4326 CRS:84 40.994600000089974 50.81198699990017 -1.13716800030295 11.574416000398173 other other other other text/xml other other geonode:som_lower_juba_agrimask_29062021wgs_ This classification was done using LCCS3 legend as a framework for classifying agriculture. LCCS3 is the last version of the Land Cover Classification System (LCCS) developed by FAO and UNEP in 1998 to facilitate the understanding of theclasses of land cover regardless of the scale of mapping, the type of coverage,method of data collection, or geographic location.Sentinel 2 images were downloaded and segmented using ecognition software.The segments were then classified using LCCS legend.During the classification, photo keys of different agricultural classes created on google earth was used as visual verification of class types before classification, given that sentinel 2 images has a resolution of 30m and therefore not clear enough to visually detect differences between classes.In additon , High Resolution Google and Esri satellite basemaps were used for verification.The scale of editing and digitization of polygons was 1:10000 features som_lower_juba_agrimask_29062021wgs_ EPSG:4326 CRS:84 41.43766487200001 42.900848905000004 -1.661864938999972 0.892129105000014 other other other other text/xml other other geonode:som_major_towns DATA AND INFORMATION MANAGEMENT UNIT (DIMU) ORGANIZATION: UNITED NATIONS DEVELOPMENT PROGRAMME (UNDP SOMALIA) MODIFIED BY: DATA AND INFORMATION MANAGEMENT UNIT UNDP SOMALIA MODIFICATION DATES: 22/03/2001 The towns were extratced from settlements digitized from Somalia topographic maps at a scale of 1: 100,000. The maps were produced by stereo photography using aerial photography 1974.Printed 1976 by Bureau of cartography, Ministry of Defence, Somalia Democratic government. Reprinted by Canadian Forces Mapping and Charting Establishment from reprographic material of native Somalia mapping by the British Director of Military Survey. Other settlements were collated from gazetteer data ( Defense Mapping Agency USA) and UNDOS, populations surveys 1997/98 of N.W Somalia- Middle and lower Shabelle. STATUS COMPLETE TABLES SOURCE: DATA AND INFORMATION MANAGEMENT UNIT UNDP SOMALIA SOURCE PUBLICATION DATE: 2000 ATTRIBUTE RELIABILITY: Good STATUS: COMPLETE FIELDS DESCRIPTION SETT_ID Internal Feature Number HUTS Number of huts in a settlement HOUSES Number of houses in a settlement NAME Name of the settlement PCODE Alphanumeric coding system for coding the settlements based on the region and district they belong to. CODE Code assigned to the settlements to classify them. Code definition 1 = Settlement 5 = Other town 10 = District town 100 = Regional Capital 1000 = Capital town REG_CODE Codes assigned to the regions. From 1 to 17 REGION Name of the region DISTRICT Name of the district SOURCE Source of the settlement either gazetteer, topomap or survey. PPRWARES Population pre-war estimated using number of nomadic huts. PPRWANS Population pre-war estimated using number of houses. TOP_POP Population from the topomaps. SUR_POP Field Survey populations. X COOD X coordinate of the settlement or the easting Y COOD Y coordinate of the settlement or the northing. features som_major_towns EPSG:4326 CRS:84 40.99829101600005 50.81222915600006 -1.035369991999971 11.965310097000042 other other other other text/xml other other geonode:som_mogadishu_city_poi Digital city map of Mogadishu based on local city maps, NIMA city maps, Landsat ETM+ and QB-images etc. features som_mogadishu_city_poi EPSG:4326 CRS:84 45.235378265000065 45.39332629900008 1.980629563000036 2.083433151000065 other other other other text/xml other other geonode:som_neighbouring_countries Administrative boundaries of Somalia neighboring countires features som_neighbouring_countries EPSG:4326 CRS:84 32.99993896500007 54.53052902200005 -4.67804670299995 19.00233268700009 other other other other text/xml other other geonode:som_north_aquifers_2012 features som_north_aquifers_2012 EPSG:4326 CRS:84 42.660856684000066 51.40984340000006 6.728666892000092 11.981461138000043 other other other other text/xml other other geonode:som_police_stations_unsos2018 Somalia Police Stations location as of 2018 som_police_stations_unsos2018 features EPSG:4326 CRS:84 41.00699144400005 51.26101472300007 -0.531843008999942 11.914214513000047 other other other other text/xml other other geonode:som_population_pess_2014 Population Estimation Survey (PESS) gathered basic critical information on the Somalis living in urban, rural and nomadic areas (interviewed at water points during the peak of the long, dry season), and in settlements for internally displaced persons. One standard questionnaire was used in selected enumeration areas or pre-identified areas. Data was collected in three main phases: cartographic field mapping, household listing in the sampled areas, and the interviewing of households using the standard questionnaire.PESS report by UNFPA had only the population estimate at regional level (Admin level 1). With the demand to get this data disaggregated to district level to enhance assessment and in particular assessments of people in food insecure by FAO-FSNAU, the district data was interpolated using FSNAU livelihood information embedded in the 2005 UNDP district level population data   features som_population_pess_2014 EPSG:4326 CRS:84 40.98950576200008 51.415153485000076 -1.651552163999952 11.988532393000071 other other other other text/xml other other geonode:som_population_pess_2014_0c5a67e3b539796c9a10edca6262848e Population Estimation Survey (PESS) gathered basic critical information on the Somalis living in urban, rural and nomadic areas (interviewed at water points during the peak of the long, dry season), and in settlements for internally displaced persons. One standard questionnaire was used in selected enumeration areas or pre-identified areas. Data was collected in three main phases: cartographic field mapping, household listing in the sampled areas, and the interviewing of households using the standard questionnaire.PESS report by UNFPA had only the population estimate at regional level (Admin level 1). With the demand to get this data disaggregated to district level to enhance assessment and in particular assessments of people in food insecure by FAO-FSNAU, the district data was interpolated using FSNAU livelihood information embedded in the 2005 UNDP district level population data features som_population_pess_2014_0c5a67e3b539796c9a10edca6262848e EPSG:4326 CRS:84 40.98950576200008 51.415153485000076 -1.651552163999952 11.988532393000071 other other other other text/xml other other geonode:som_prewar_rain_stations_1963_1990_faoswalim The data is about pre-war 1963 - 1990 Somalia rainfall record stations. features som_prewar_rain_stations_1963_1990_faoswalim EPSG:4326 CRS:84 42.06000000000006 51.25000000000006 -0.359999999999957 11.960000000000036 other other other other text/xml other other geonode:som_primary_roads_unocha The layer contains primary roads data for Somalia. UNOCHA has collected this data from sources such as ICPAC_IGAD_UNOSAT, then UNOCHA has made some updates. features som_primary_roads_unocha EPSG:4326 CRS:84 40.93290329000007 51.13941574100005 -1.150308131999964 11.958604813000022 other other other other other text/xml other geonode:som_proposed_charcoal_production_areas This map shows the areas that are considered to be potential for charcoal production in Somalia. The selection of the areasis based on environmental aspects and FAO SWALIM accumulted field experience in Somalia. features som_proposed_charcoal_production_areas EPSG:4326 CRS:84 41.000005884000075 50.003887675000044 -1.651552163999952 10.603385160000073 other other other other text/xml other other geonode:som_rainfall_stations_faoswalim_2007 Currently, there are over 100 manual rainfall stations, eight synoptic weather stations and 11 automatic weather stations in all Somalia. The stations record a variety of weather elements, including rainfall, temperature, relative humidity, atmospheric pressure, wind speed, wind direction and solar radiation. Data from these automatic stations is received by SWALIM in near-real-time through satellite feeds every four hours. The Somalia rainfall performance layer is generated using data from these stations and other data sources. features som_rainfall_stations_faoswalim_2007 EPSG:4326 CRS:84 42.10000000000008 49.17605000000003 0.050000000000068 11.282650000000046 other other other other text/xml other other geonode:som_regional_capitals DATA AND INFORMATION MANAGEMENT UNIT (DIMU) ORGANIZATION: UNITED NATIONS DEVELOPMENT PROGRAMME (UNDP SOMALIA) MODIFIED BY: DATA AND INFORMATION MANAGEMENT UNIT UNDP SOMALIA MODIFICATION DATES: 22/03/2001 The settlements where digitized from Somalia topographic maps at a scale of 1: 100,000. The maps were produced by stereo photography using aerial photography 1974.Printed 1976 by Bureau of cartography, Ministry of Defence, Somalia Democratic government. Reprinted by Canadian Forces Mapping and Charting Establishment from reprographic material of native Somalia mapping by the British Director of Military Survey. Other settlements were collated from gazetteer data ( Defense Mapping Agency USA) and UNDOS, populations surveys 1997/98 of N.W Somalia- Middle and lower Shabelle. STATUS COMPLETE TABLES SOURCE: DATA AND INFORMATION MANAGEMENT UNIT UNDP SOMALIA SOURCE PUBLICATION DATE: 2000 ATTRIBUTE RELIABILITY: Good STATUS: COMPLETE FIELDS DESCRIPTION SETT_ID Internal Feature Number HUTS Number of huts in a settlement HOUSES Number of houses in a settlement NAME Name of the settlement PCODE Alphanumeric coding system for coding the settlements based on the region and district they belong to. CODE Code assigned to the settlements to classify them. Code definition 1 = Settlement 5 = Other town 10 = District town 100 = Regional Capital 1000 = Capital town REG_CODE Codes assigned to the regions. From 1 to 17 REGION Name of the region DISTRICT Name of the district SOURCE Source of the settlement either gazetteer, topomap or survey. PPRWARES Population pre-war estimated using number of nomadic huts. PPRWANS Population pre-war estimated using number of houses. TOP_POP Population from the topomaps. SUR_POP Field Survey populations. X COOD X coordinate of the settlement or the easting Y COOD Y coordinate of the settlement or the northing. features som_regional_capitals EPSG:4326 CRS:84 42.219879150000054 49.18062973000008 -0.360289990999945 11.28365993500006 other other other other text/xml other other geonode:som_relief_s_faoswalim This data is about Somalia relief and landscape which represents information about elevations and landforms of southern part of Somalia. Data on topography from NASA SRTM 90 m. som_relief_s_faoswalim features EPSG:4326 CRS:84 41.89169460000005 46.150032544000055 -0.266810086999953 5.060045358000025 text/xml other other other other other other geonode:som_river_barrage_bridge_faoswalim Data is collected and compiled by FAO Somalia Water and Land Information Management (SWALIM)In recent years, there have been several intervention activities going on in the irrigation sector in southern Somalia, mainly aiming to rehabilitate broken down barrages and clogged irrigation canals. To support these interventions, SWALIM has developed a well-structured tool, for collecting and managing past and present information on the irrigation infrastructure: the Irrigation Information Management System (IIMS), a stand-alone PC system which is available upon request. The IIMS provides information (both spatial and tabular) on ongoing and planned irrigation projects. It gives users of irrigation data a platform to discover what is available, querry the system for specific datasets and download data in different formats, such as .pdf documents, maps, spreadsheets, etc. features som_river_barrage_bridge_faoswalim EPSG:4326 CRS:84 42.28145333500004 45.596844616000055 0.748955086000024 4.73541652800003 other other other other text/xml other other geonode:som_river_culvert_faoswalim Locations of culverts along Juba and Shabelle rivers in Somalia. Data is collected and compiled by FAO Water and Land Information Management (SWALIM). features som_river_culvert_faoswalim EPSG:4326 CRS:84 44.231430878000026 44.37306150500007 1.60074154800003 1.666982159000042 other other other other text/xml other other geonode:som_river_gauging_stations_faoswalim3 River gauging stations along Shabelle and Juba Rivers to measure river water levels. Data is collected and compiled by FAO Somalia Water and Land Information Management (SWALIM). features som_river_gauging_stations_faoswalim3 EPSG:4326 CRS:84 42.22314514200008 45.567270000000065 1.244770000000074 4.73598000000004 other other other other text/xml other other geonode:som_river_shabelle_juba_poly_faoswalim A polygon layer data of Shabelle and Juba Rivers. Digitized and compiled from VHR satellite images by FAO Somalia Water and Land Information Management (SWALIM). features som_river_shabelle_juba_poly_faoswalim EPSG:4326 CRS:84 42.122141320000026 45.678607914000054 -0.253669431999924 4.972897068000066 other other other other text/xml other other geonode:som_rivers_faoswalim The Shuttle Radar Topography Mission (SRTM) obtained 90-meter (3 arc-second) resolution data on a near-global scale (between 56 degrees South and 60 degrees North latitude) and 30 meter (1 arc-second) resolution over United States, providing a valuable global topographic dataset. The SRTM data were collected during an 11-day mission in February of 2000 from a radar system onboard the Space Shuttle Endeavor. features som_rivers_faoswalim EPSG:4326 CRS:84 40.90907150600003 51.35527314300003 -1.329509721999955 11.978869720000034 other other other other text/xml other other geonode:som_rivers_juba_shabelle_line_faoswalim The Shuttle Radar Topography Mission (SRTM) obtained 90-meter (3 arc-second) resolution data on a near-global scale (between 56 degrees South and 60 degrees North latitude) and 30 meter (1 arc-second) resolution over United States, providing a valuable global topographic dataset. The SRTM data were collected during an 11-day mission in February of 2000 from a radar system onboard the Space Shuttle Endeavor. features som_rivers_juba_shabelle_line_faoswalim EPSG:4326 CRS:84 42.12213516200006 45.67823791500007 -0.25111558499998 4.953206862000059 other other other other text/xml other other geonode:som_rivers_juba_shabelle_line_faoswalim2f5c1f91650e The Shuttle Radar Topography Mission (SRTM) obtained 90-meter (3 arc-second) resolution data on a near-global scale (between 56 degrees South and 60 degrees North latitude) and 30 meter (1 arc-second) resolution over United States, providing a valuable global topographic dataset. The SRTM data were collected during an 11-day mission in February of 2000 from a radar system onboard the Space Shuttle Endeavor. features som_rivers_juba_shabelle_line_faoswalim2f5c1f91650e EPSG:4326 CRS:84 42.12213516200006 45.67823791500007 -0.25111558499998 4.953206862000059 other other other other text/xml other other geonode:som_secondary_roads_adc2010 This dataset is an extraction of roads from OpenStreetMap data made by WFP following UNSDI-T standards. The data is updated in near-real time from OSM servers and include all latest updates. NOTE: this dataset doesn't include streets and pathways that have been published on a separate dataset (streets and pathways). features som_secondary_roads_adc2010 EPSG:4326 CRS:84 40.99034037600006 51.25991378600003 -1.64603490199994 11.958599760000027 other other other other text/xml other other geonode:som_security_projected_risk_2018_faoswalim This dataset contains the administrative bundaries of Somalia (district, regions, zones).The boundaries were first created by USAID/FEWS and modified by UNDP - Data & Information Management Unit (DIMU) in 21/03/2001. This layer contains the first level (International) boundary at a 1:1,000,000 scale. The coverage is part of the Famine Early Warning System (FEWS)/Associates in Rural Development (ARD), African series.The coastline was digitized from LANDSAT TM images at a scale of 1:50000 by DIMU. This coastline was then added to the boundaries and the original coastline amended.Acknowledgement of USAID, FEWS, EDC-International Program, ADDS (Africa Data Dissemination Service), UNDP and the U.S Geological Survey would be appreciated in products derived from these data.The source of the second (region) and third (district) level boundaries are from the Digital Chart of the World (DCW).The names of the regions and districts have been agreed upon by the Statistical Working Group at very high levels by statistical focal points from UN agencies, and Ministries from within the Transitional Federal government of Somalia. The names have also been endorsed by the Somalia Interagency Mapping and Coordination group (SIMaC).This layer was compiled using the pre-war boundaries and the names adopted by this statistical working group.  Additional columns hold "alternate" spellings such as anglicized names. features som_security_projected_risk_2018_faoswalim EPSG:4326 CRS:84 40.98950576800007 51.41412735100005 -1.66006135899994 11.985942841000053 other other other other text/xml other other geonode:som_sentinel2_imageindex_granule Image Index: it contains feature classes that contain information about the path/row, scene boundaries and the geographic coordinates of the imageries acquired by satellites for Somalia. These indices help in identifying the numbers of images covering Somalia and are easy guides for identifying searching for the required images. features som_sentinel2_imageindex_granule EPSG:4326 CRS:84 40.796693520000076 52.01094843700008 -1.896817942999974 12.664549599000054 other other other other other text/xml other geonode:som_settlements_assorted This dataset contains districts and regional capitals, towns, settlements, and IDP camps. Below is a description of the fields in the attribute table: OBJECTID - unique ID for the dataset KEMRI_TEAM - team number assigned for the collection of the KEMRI settlements KEMRI_NO_H - number of houses identified by KEMRI surveys KEMRI_POP - population of settlement as identified by KEMRI surveys GTZ_LOCATO - GTZ unique ID for settlements identified in the GTZ survey GTZ_TYPE - type of settlement as identified by GTZ survey GTZ_ECONOM - type of economic activity in settlement as identified by GTZ survey GTZ_POP - population of settlement as identified by GTZ survey GTZ_MINE_A - settlement affected by mines according to GTZ survey DP97_HUTS - number of huts in settlement as identified by UNDP 1997 survey DP97_HOUSE - number of houses in settlement as identified by UNDP 1997 survey DP97_PCODE - place code as allocated by UNDP 1997 survey DP97_CODE - settlement code, identifying type of settlement. 1 = Settlement, 5 = Other town, 10 = District town, 100 = Regional Capital, 1000 = Capital town DP97_SOURC - source of the settlement for the UNDP 1997 survey DP97_PPRES - pre-war population estimate using number of huts for UNDP 1997 survey DP97_PPNRS - pre-war population estimate using number of houses for UNDP 1997 survey DP97_POP - population from topomaps for UNDP 1997 survey DP97_SPOP - surveyed population for UNDP 1997 survey ALT_NAME - Alternative names and spellings for settlement som_settlements_assorted settlements somalia features EPSG:4326 CRS:84 40.99315000000007 51.28266000000008 -1.600499987999967 11.960390000000075 other other other other text/xml other other geonode:som_settlements_unocha2011_p_coded Data is updated by Somalia Information and mapping coordination (SIMAC) working Group in 2016. Up to present in 2019 this is the settlement layer endorsed by UNOCHA and used by UN in Somalia.This file was updated on May 2018 to incorporate the P-codes. Some settlements fall outside the disputed territory due to positional error probably.For settlements classification use the field named: DEFINITION settlements somalia som_settlements_unocha2011_p_coded features EPSG:4326 CRS:84 40.992080000000044 51.28266000000008 -1.637539999999944 11.960390000000075 other other other other text/xml other other geonode:som_soil_250k To achieve the preliminary land unit classification, a set of updated multispectral satellite images was acquired . A set of Sentinel-2 (from January to February 2020 interval time) images covering integrally the complexes of the project area with a spatial resolution of 10m per pixel has been processed using Near infrared, green and blue spectral band combination) and analyzed using a GIS software. The analysis of the images helps to classify the areas at fourth levels: Soil Region (1:3M scale) - System (1:1M scale) - Subsystems (1:500k scale) - Land Unit (1:250k scale) Further based on the photointerpretation, the morphologic and physiographic analysis the homogenous land units are defined. First, a general overview of the study area done based on bibliographic material concerning existing soil surveys, geography, geology, climate, agriculture, vegetation and soil characteristics. Particularly, in this case a mixed descending and ascending building and interpretation methodology was applied. As shown in the following picture, the descending methodology has used where existing soil data are lacking, starting from morphology, lithology and land use. Homogeneous polygons with same morphology, lithology and land use/cover may have same soils. For large part of Somalia country this methodology was applied. The ascending methodology has applied where existing soil data was available, in Somalia some 1.50.000/1:100.000 soil maps was available in north and in south part of the country. Of course due the different scale of the final soil map, the details are different, so some existing Land Units at semidetailed scale has merged to each one relating to the extensions and soil typology. The photointerpretation has done mainly with the aid of the following: - Sentinel-2 satellite images (Jan-Feb 2020) 10m resolution (NIR-GB spectral bands) - SRTM Digital Elevation model 30x30 and 90x90 m resolution - “Sm-landform” SWALIM shapefile features som_soil_250k EPSG:32638 CRS:84 40.902916811703626 51.44900467641144 -1.6586869973246365 12.04750671521756 other other other other other other text/xml geonode:som_srtm_contours_100_usgs 100m resolution contours obtained from the U.S. Geological Survey features som_srtm_contours_100_usgs EPSG:4326 CRS:84 41.11066435400005 51.443515028000036 -1.666569275999962 11.963180289000036 other other other other other text/xml other geonode:som_srtm_spot_heights features som_srtm_spot_heights EPSG:4326 CRS:84 41.00208126500007 51.41229783000006 -1.616661368999928 11.96650088900003 other other other other text/xml other other geonode:som_strategic_water_sources_feb2018 The dataset contains the most common water source types in Somalia classified into five categories namely: boreholes, shallow wells, dams, springs and berkads. Other source types which do not fit in any of these five categories are classified as “Other” The data is periodically updated from field surveys carried out by FAO/SWALIM through government and NGO partners, or received from WASH Cluster partners.Modern technology has been adopted for field data collection, using mobile phones, building on the conventional paper based questionnaire first developed and adopted by WASH partners in Somalia back in 2006 features som_strategic_water_sources_feb2018 EPSG:4326 CRS:84 40.99125300000003 51.28286000000003 -1.056002699999965 11.953340000000026 other other other other text/xml other other geonode:som_topomapsindex The Topographic Maps are from varying sources and dates, but the legends are very similar and the index numbers have remained the same. Scanned legends can be found in the same folder as the topomaps in jpeg format. All versions have been supplied. Scale is 1:100,000 and contour interval is 20 metres. Maps have been scanned and georeferenced to Geographic WGS84. Supplied to SWALIM by UNDP Somalia and RCMRD (Regional Centre for Mapping of Resources for Development). 'British Maps' These were produced by stereo photography using aerial photography in the early 1970's. Originally printed by Bureau of Cartography, Ministry of Defense, Somalia Democratic Republic in the late 1970's. Reprinted by Canadian Forces Mapping and Charting Establishment from reprographic material of native Somalia mapping by the British Director General of Military Survey. Revisions were made by the Defense Mapping Agency Hydrographic/Topographic Centre, Bethesda, MD, in cooperation with the Canadian Canadian Forces Mapping and Charting Establishment in the early 1990's. 'Russian Maps' are also included but no information is provided in the metadata as there is no translation available at present. They are in the minority in the SWALIM archive and have only been included where there are gaps in the British/Canadian maps. The legend is similar to the British/Canadian maps. features som_topomapsindex EPSG:4326 CRS:84 40.99910078900007 51.499211270000046 -1.666267346999973 12.000566118000052 other other other other other text/xml other geonode:som_veryhighresolution_imageindex features som_veryhighresolution_imageindex EPSG:4326 CRS:84 -2.627777777999938 51.332011916000056 -2.334758453999939 36.70500000000004 other other other other text/xml other other geonode:som_water_sources_ground_faoswalim The the dataset contains Somali Water Catchments, and their rehabilitation status, for the period between 2013 and 2017 divided into phases 2a, 2b, 2c, 3, 4, 5, 6a, 6b, 6c and 7a.The status depicted could either be 'rehabilitated', 'not rehabilitated', 'partially rehabilitated', 'not clear' or 'not assessed'.The water catchments are managed by different Non-Governmental Organizations in Somali.This dataset was generated by taking photographs of the catchments using GPS enabled digital cameras. The geographical X and Y coordinates of the catchments were extracted from the photographs and plotted to generate a shapefile layer. The developed shapefile was overlaid on high resolution satellite images captured just before and immediately after the rehabilitation of the water catchments. The satellite images were then observed for rehabilitation status of different water catchments. sources somalia surface water features som_water_sources_ground_faoswalim EPSG:4326 CRS:84 40.99412667000007 51.28286000000003 -1.056002699999965 11.953340000000026 other other other other text/xml other other geonode:som_water_sources_ground_faoswalime805171a5d3d The the dataset contains Somali Water Catchments, and their rehabilitation status, for the period between 2013 and 2017 divided into phases 2a, 2b, 2c, 3, 4, 5, 6a, 6b, 6c and 7a.The status depicted could either be 'rehabilitated', 'not rehabilitated', 'partially rehabilitated', 'not clear' or 'not assessed'.The water catchments are managed by different Non-Governmental Organizations in Somali.This dataset was generated by taking photographs of the catchments using GPS enabled digital cameras. The geographical X and Y coordinates of the catchments were extracted from the photographs and plotted to generate a shapefile layer. The developed shapefile was overlaid on high resolution satellite images captured just before and immediately after the rehabilitation of the water catchments. The satellite images were then observed for rehabilitation status of different water catchments. sources surface somalia som_water_sources_ground_faoswalime805171a5d3d water features EPSG:4326 CRS:84 40.99412667000007 51.28286000000003 -1.056002699999965 11.953340000000026 other other other other text/xml other other geonode:somalia_agroecological_zones Agro-ecological zones (AEZ) are land resource mapping units, defined in terms of\r\nclimate, landform and soils, and/or land cover, having a specific range of\r\npotentials and constraints (FAO, 1996). The purpose of Agro-ecological zoning is to give an inventory and overview of the physical agricultural potential of an area.Agro-ecological zones for Somalia have been defined and mapped through a combination of information on soils, landform and climate. Information on soils and landform was mainly derived from the Soil and Terrain (SOTER) Database for\r\nnortheastern Africa (FAO, 1998), updated with recent information from the\r\nSWALIM study areas. Available data on rainfall and potential evapotranspiration (FAOCLIM, 2001) has been used to define Length of Growing Period Zones (LGP Zones), as described in the following sections. Read this report for more details -> https://www.faoswalim.org/resources/site_files/L-12%20Land%20Resources%20Report.pdf features somalia_agroecological_zones EPSG:4326 CRS:84 40.98872165385188 51.4133934330502 -1.659663170522937 11.986426973506097 other other other other text/xml other other geonode:somalia_coastal_mask Somalia coast mask at a scale of 1:250,000 features somalia_coastal_mask EPSG:4326 CRS:84 40.47221972800003 52.47144750700005 -4.98693925799995 13.521183288000032 other other other other text/xml other other geonode:somdotgrid2014 The Dot Grid was produced by applying the USGS Rapid Land Cover Mapper (RLCM) methodology that uses regularly spaced (in this case 500m spacing) dot grid statistical approach to generate land cover data. The principal aim was to produce an updated statistical assessment of Somalia's cultivable area. USGS EROS Data Center provided with ASTER satellite imagery of 15m resolution , acquired mainly in 2013. The average visual interpretation scale is 1:50,000. The joint Research Center(JRC) of the European Commission provided with additional additional LANDSAT ETM (2009-2011) satellite images and contributed to the definition and accuracy assessment of the methodology . LANDSAT imagery complemented the baseline images in areas where either cloud cover was present on ASTER images or when gaps occurred. Very high resolution satellite images were used to refine the interpretation of cultivable areas and to verify/validate the natural vegetation cover. \r\nStandardized FAO Land Cover Meta Language (LCML) methodology was utilized to create the legend for the analysis. The area covered by each land cover class was derived from the classified dots features somdotgrid2014 EPSG:4326 CRS:84 40.95917693043627 51.41341088090561 -1.650421622741815 11.987000054244614 other other other other text/xml other other geonode:strategic_water_sources_20225 strategic_water_sources_20225 water somalia features EPSG:4326 CRS:84 40.995668 51.2722594 -1.1400615 11.42396 other other other other other other text/xml geonode:strategic_water_sources_all_sept2020 The dataset contains the most common water source types in Somalia classified into five categories namely: boreholes, shallow wells, dams, springs and berkads. Other source types which do not fit in any of these five categories are classified as “Other” The data is periodically updated from field surveys carried out by FAO/SWALIM through government and NGO partners, or received from WASH Cluster partners.Modern technology has been adopted for field data collection, using mobile phones, building on the conventional paper based questionnaire first developed and adopted by WASH partners in Somalia back in 2006 strategic_water_sources_all_sept2020 sources somalia water features EPSG:4326 CRS:84 41.0187 51.2829 -0.3669 11.9533 other other other other text/xml other other geonode:strategic_water_sources_all_sept20206557d8d4e8bd The dataset contains the most common water source types in Somalia classified into five categories namely: boreholes, shallow wells, dams, springs and berkads. Other source types which do not fit in any of these five categories are classified as “Other” The data is periodically updated from field surveys carried out by FAO/SWALIM through government and NGO partners, or received from WASH Cluster partners.Modern technology has been adopted for field data collection, using mobile phones, building on the conventional paper based questionnaire first developed and adopted by WASH partners in Somalia back in 2006 sources somalia water features 2020 strategic_water_sources_all_sept20206557d8d4e8bd EPSG:4326 CRS:84 41.0187 51.2829 -0.3669 11.9533 other other other other text/xml other other geonode:swalim_river_breakages_august_2022 Four consecutive poor rainy seasons in most parts of the Horn of Africa region have resulted to current serious hydrological drought conditions in Somalia and neighboring countries.. Juba and Shabelle Rivers, with the headwaters in the Ethiopian highlands have remained below the long term average since the beginning of 2022, negatively impacting agriculture production, domestic and livestock water use for the riverine communities. The low river levels however provide an opportunity to fix the river breakages and weak embankments, ahead of the next rainy season. SWALIM has updated the status of the river breakages along the Juba and Shabelle Rivers using available Very High Resolution (VHR) satellite imagery and a Digital Elevation Model (DEM).Five types of breakages have been identified, namely; open, overflow, potential overflows, potential breakages and closed with sandbags. The open breakages are those that are currently open as observed on the latest VHR image available. All the observations reported refers to the latest suitable VHR satellite image available, which is indicated in the online database. 100 Open breakage points have been identified, 70 on the Shabelle River and 30 on the Juba River which require immediate action. 13 Overflows were also identified during this season. Jowhar district was worst affected along the Shabelle while Bu’aale and Jilib districts are worst affected along the Juba.\r\n\r\nUsers are advised that the methodology is biased towards Remote Sensing (RS) interpretation with only limited “ground truthing” due to access constraints. Open breakages might have been omitted in some cases where satellite images may not have been very clear (e.g. heavy cloud cover) or were not available. river swalim_river_breakages_august_2022 somalia shabelle features breakages juba 2022 EPSG:4326 CRS:84 42.06809008 45.6786699999998 -0.07097 4.89294 other other other other other other text/xml geonode:water_cathments_phases_2ato7b_sws Somalia surface water resources infrastructures rehabilitated by FAO Somalia under Cash for Work Programme. features water_cathments_phases_2ato7b_sws EPSG:4326 CRS:84 40.99125300000003 50.503013889000044 -0.496942999999931 11.229535000000055 other other other other text/xml other other