My GeoServer WFSThis is a description of your Web Feature Server. The GeoServer is a full transactional Web Feature Server, you may wish to limit GeoServer to a Basic service level to prevent modificaiton of your geographic data.WFSWMSGEOSERVERWFS2.0.0NONENONE1.0.01.1.02.0.0text/xmlServiceIdentificationServiceProviderOperationsMetadataFeatureTypeListFilter_Capabilitiesapplication/gml+xml; version=3.2resultshitsapplication/gml+xml; version=3.2GML2KMLSHAPE-ZIPapplication/jsonapplication/vnd.google-earth.kml xmlapplication/vnd.google-earth.kml+xmlcsvexcelexcel2007gml3gml32jsontext/csvtext/xml; subtype=gml/2.1.2text/xml; subtype=gml/3.1.1text/xml; subtype=gml/3.2nonelocalFALSE1000000nonelocalapplication/gml+xml; version=3.2urn:ogc:def:queryLanguage:OGC-WFS::WFSQueryExpressionALLSOMEresultshitsapplication/gml+xml; version=3.2GML2KMLSHAPE-ZIPapplication/jsonapplication/vnd.google-earth.kml xmlapplication/vnd.google-earth.kml+xmlcsvexcelexcel2007gml3gml32jsontext/csvtext/xml; subtype=gml/2.1.2text/xml; subtype=gml/3.1.1text/xml; subtype=gml/3.2nonelocalapplication/gml+xml; version=3.2ALLSOMETRUETRUETRUETRUETRUETRUEFALSEFALSETRUETRUETRUETRUEFALSETRUEFALSEwfs:Querywfs:StoredQuerygeonode:mogadishu_districts_unochaDigital city map of Mogadishu based on local city maps, NIMA city maps, Landsat ETM+ and QB-imagesfeaturesmogadishu_districts_unochaurn:ogc:def:crs:EPSG::432645.22952244600003 1.97436993100006945.43303938300005 2.099879804000068geonode:som_adm3_districts_unochaSomalia country administrative boundary admin2 (Districts of Somalia). The source of this data is United Nation Development Programme (UNEP) 1998. UNOCHA is contributor.featuressom_adm3_districts_unochaurn:ogc:def:crs:EPSG::432640.994316999000034 -1.66491440199990851.413032532000045 11.985202789000084geonode:som_adm2_regions_unochaSomalia country administrative boundary admin2 (Regionsof Somalia). The source of this data is United Nation Development Programme (UNEP) 1998. UNOCHA is contributor.featuressom_adm2_regions_unochaurn:ogc:def:crs:EPSG::432640.994316999000034 -1.66491440199990851.413032532000045 11.985202789000084geonode:afgooye_potentialhigherground_forfloodevacuatDatasets 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.featuresafgooye_potentialhigherground_forfloodevacuaturn:ogc:def:crs:EPSG::432644.71230399386069 1.95874122829423245.342860406402956 2.261656408500807geonode:afgooye_final_soil_map_utm38nThis 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_utm38nfeaturesRiverine AgriculturesomaliashabelleSWALIMLand UnitsafgooyeSoil SurveySoil MapjubaSoil PropertiesWRB Classificationurn:ogc:def:crs:EPSG::3263844.646415213680655 1.725405201515518145.166210734033186 2.1889063752801454geonode:som_land_agrisuitability_citrus_s_faoswalim0The 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).featuressom_land_agrisuitability_citrus_s_faoswalim0urn:ogc:def:crs:EPSG::432641.89169460000005 -0.26681008699995346.150032544000055 5.060045358000025geonode:som_land_agrisuitability_cowpea_n_faoswalim0The 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)featuressom_land_agrisuitability_cowpea_n_faoswalim0urn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_agrisuitability_maize_n_faoswalim0The 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)featuressom_land_agrisuitability_maize_n_faoswalim0urn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_agrisuitability_rice_s_faoswalim0The 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).featuressom_land_agrisuitability_rice_s_faoswalim0urn:ogc:def:crs:EPSG::432641.89169460000005 -0.26681008699995346.150032544000055 5.060045358000025geonode:som_land_agrisuitability_rice_s_faoswalim0da8c37a7f756The 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).featuressom_land_agrisuitability_rice_s_faoswalim0da8c37a7f756urn:ogc:def:crs:EPSG::432641.89169460000005 -0.26681008699995346.150032544000055 5.060045358000025geonode:som_land_agrisuitability_sorghumr1_n_faoswaliThe 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)featuressom_land_agrisuitability_sorghumr1_n_faoswaliurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_agrisuitability_sorghumr2_n_faoswaliThe 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)featuressom_land_agrisuitability_sorghumr2_n_faoswaliurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_agrisuitability_sugarcane_s_faoswaliThe 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).featuressom_land_agrisuitability_sugarcane_s_faoswaliurn:ogc:def:crs:EPSG::432641.89169460000005 -0.26681008699995346.150032544000055 5.060045358000025geonode:somalia_agroecological_zonesAgro-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.pdffeaturessomalia_agroecological_zonesurn:ogc:def:crs:EPSG::432640.98872165385188 -1.65966317052293751.4133934330502 11.986426973506097geonode:aquifer_of_somaliland_puntlandfeaturesaquifer_of_somaliland_puntlandurn:ogc:def:crs:EPSG::432642.660856684000066 6.72866689200009251.40984340000006 11.981461138000043geonode:baardheere_potential_highergroundssuitableforDatasets 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.floodsgroundsevacuationhighersomaliabaardheere_potential_highergroundssuitableforshabellefeaturesriverjubaurn:ogc:def:crs:EPSG::3263842.12119319335759 1.953416332569221542.42570436324285 2.57992951358917geonode:afgooye_banana_suitability_map_v1This 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 suitabilitycrop suitabilityfeaturesSoilagriculturebananaSWALIMafgooyeafgooye_banana_suitability_map_v1somaliaClimateFAOurn:ogc:def:crs:EPSG::3263844.646415213680655 1.725405201515518145.166210734033186 2.1889063752801454geonode:belet_weyne_banana_suitability_v1This 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 weyneland suitabilitycrop suitabilityfeaturesSoilagriculturebelet_weyne_banana_suitability_v1bananaSWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::3263845.00259092982955 4.59854693011817645.28620156080992 5.007539076935439geonode:jowhar_suitability_bananaThis 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 suitabilitycrop suitabilityfeaturesSoilagriculturejowhar_suitability_bananabananajowharSWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:kismaayo_banana_suit_v2This 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 suitabilitycrop suitabilitykismaayofeaturesSoilagriculturebananakismaayo_banana_suit_v2SWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:beletweyne_potential_suitable_higher_grounds_0_rlngr0fDatasets 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.evacuationbeletweyne_potential_suitable_higher_grounds_0_rlngr0ffeaturesurn:ogc:def:crs:EPSG::432644.845503797016534 4.34055069157221845.41536693283746 5.065590305508806geonode:belet_weine_25k_final_luThis 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 weyneSoil Mapbelet_weine_25k_final_lufeaturesRiverine AgricultureshabelleSWALIMLand UnitsSoil PropertiesSoil SurveysomaliajubaWRB Classificationurn:ogc:def:crs:EPSG::3263845.00259092982955 4.59854693011817645.28620156080992 5.007539076935439geonode:afgooye_citrus_suitability_map_v1This 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 suitabilitycrop suitabilityfeaturesSoilagricultureSWALIMafgooyesomaliaafgooye_citrus_suitability_map_v1ClimateCitrusFAOurn:ogc:def:crs:EPSG::3263844.646415213680655 1.725405201515518145.166210734033186 2.1889063752801454geonode:belet_weyne_citrus_suitability_v1This 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 weyneland suitabilitycrop suitabilityfeaturesbelet_weyne_citrus_suitability_v1SoilagricultureSWALIMsomaliaClimateCitrusFAOurn:ogc:def:crs:EPSG::3263845.00259092982955 4.59854693011817645.28620156080992 5.007539076935439geonode:jowhar_suitability_citrusThis 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 suitabilitycrop suitabilityfeaturesSoilagriculturejowharSWALIMsomaliaClimateCitrusFAOjowhar_suitability_citrusurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:kismaayo_citrus_suit_v2This 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_v2crop suitabilitykismaayofeaturesland suitabilitySoilagricultureSWALIMsomaliaClimateCitrusFAOurn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:sm_citrus_suit_v3_1This 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: 1:1,500,000irrigated agriculturesm_citrus_suit_v3_1land suitabilitycrop suitabilityfeaturesSoilGridsSWALIMsoil suitabilitysomaliaCitrusurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:climate_zones_in_somaliaData 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.featuresclimate_zones_in_somaliaurn:ogc:def:crs:EPSG::432640.989505766000036 -1.6600613589999451.414127345000054 11.985942840000064geonode:som_neighbouring_countriesAdministrative boundaries of Somalia neighboring countiresfeaturessom_neighbouring_countriesurn:ogc:def:crs:EPSG::432632.99993896500007 -4.6780467029999554.53052902200005 19.00233268700009geonode:som_river_culvert_faoswalimLocations of culverts along Juba and Shabelle rivers in Somalia. Data is collected and compiled by FAO Water and Land Information Management (SWALIM).featuressom_river_culvert_faoswalimurn:ogc:def:crs:EPSG::432644.231430878000026 1.6007415480000344.37306150500007 1.666982159000042geonode:floods_gu_2025This 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 areasfeaturesfloods_gu_2025urn:ogc:def:crs:EPSG::432645.411623311211365 2.42927969791190245.59944702148437 2.876478139269138geonode:river_juba_breakage_aug_2025FAO-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. featuresriver_juba_breakage_aug_2025urn:ogc:def:crs:EPSG::385742.062708985935565 -0.096366269427650642.778638664845076 4.179544681127806geonode:river_breakages_juba_shabelle_march2026FAO-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.shabelleriver breakagesriver_breakages_juba_shabelle_march2026FAOSWALIMfeaturessomaliafloodsjubaurn:ogc:def:crs:EPSG::432642.06187852925861 -0.09596127385973145.67792175611577 4.893462037080062geonode:river_breakage_shabell_aug_2025FAO-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. featuresriver_breakage_shabell_aug_2025urn:ogc:def:crs:EPSG::432644.12800000000004 1.55100000000004545.67867000000007 4.892940000000067geonode:afgooye__darte_palm_suitability_map_v1This 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 suitabilitycrop suitabilityfeaturesSoilagricultureSWALIMafgooye__darte_palm_suitability_map_v1Date PalmsomaliaafgooyeClimateFAOurn:ogc:def:crs:EPSG::3263844.646415213680655 1.725405201515518145.166210734033186 2.1889063752801454geonode:jowhar_date_palm_suitabilityThis 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 suitabilitycrop suitabilityfeaturesSoilagriculturejowharSWALIMjowhar_date_palm_suitabilityDate PalmsomaliaClimateFAOurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:kismaayo_date_palm_suit_v2This 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_v2land suitabilitycrop suitabilitykismaayofeaturesSoilagricultureSWALIMDate PalmsomaliaClimateFAOurn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:dollow_potentialsuitablehigherground_evacuatiDatasets 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 providedfloodsgroundsevacuationhighersomaliashabellefeaturesdollow_potentialsuitablehigherground_evacuatipotentialriverjubaurn:ogc:def:crs:EPSG::432641.86316236027364 3.89865062872018742.341364946848856 4.179330379725302geonode:sm_drip_suit_v3_1This 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.featuresIrrigation SuitabilityDrip Irrigationsm_drip_suit_v3_1SWALIMsoil suitabilitysomaliaLand Evaluationurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:landcover_2000The 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/ITAfeatureslandcover_2000urn:ogc:def:crs:EPSG::432640.98862838700006 -1.66718971699992851.41272354100005 11.99218845400003geonode:som_flood_prone_areas_20200This 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).riverfloodssomaliashabellefeaturesprone2020som_flood_prone_areas_20200jubaurn:ogc:def:crs:EPSG::432642.07852136906297 -0.26739757512626745.74236120600489 5.019687921174807geonode:som_flooded_agriculture_areas_faoswalim2018Somalia river floods occur along the Juba and Shabelle rivers in Southern Somalia. The layer shows the agricultural areas affected by floods in 2018.floodssomaliaagricultureshabellesom_flooded_agriculture_areas_faoswalim20182018featuresriverjubaurn:ogc:def:crs:EPSG::432642.08466599800005 0.28978686000004945.742361206000055 4.998042270000042geonode:belet_weyne_forage_pasture_suitability_v1This 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 weyneland suitabilitycrop suitabilityfeaturespastureSoilagricultureforagebelet_weyne_forage_pasture_suitability_v1SWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::3263845.00259092982955 4.59854693011817645.28620156080992 5.007539076935439geonode:afgooye__forage_suitability_map_v1This 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 suitabilitycrop suitabilityfeaturespastureSoilagriculturerangelandforageSWALIMafgooye__forage_suitability_map_v1afgooyesomaliaClimateFAOurn:ogc:def:crs:EPSG::3263844.646415213680655 1.725405201515518145.166210734033186 2.1889063752801454geonode:jowhar_forage_suitabilityThis 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 suitabilitycrop suitabilityfeaturespastureSoilagricultureforagejowharSWALIMsomaliajowhar_forage_suitabilityClimateFAOurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:sm_forage_suit_v2This 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: 1:1,500,000land suitabilityfeaturespastureSoilGridsrangelandforagegrazingSWALIMsomaliaresiliencesm_forage_suit_v2livestockurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:forestsuitability_tamarindusindica_northThe 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).featuresforestsuitability_tamarindusindica_northurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_forestsuitability_n_faoswalimThe 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).featuressom_land_forestsuitability_n_faoswalimurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_forestsuitability_s_faoswalimThe 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).featuressom_land_forestsuitability_s_faoswalimurn:ogc:def:crs:EPSG::432641.89169460000005 -0.26681008699995346.15003254800007 5.060045358000025geonode:land_forestsuitability_acacianilotica_nThe 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).featuresland_forestsuitability_acacianilotica_nurn:ogc:def:crs:EPSG::432643.01092679300007 9.16651313100004544.46210394500008 10.689748208000026geonode:som_land_forestsuitability_acacianilotica_s_fThe 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).featuressom_land_forestsuitability_acacianilotica_s_furn:ogc:def:crs:EPSG::432641.891693115000066 -0.26681008899993246.15003204300007 5.060045242000058geonode:som_land_forestsuitability_acaciatortilis_n_fThe 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).featuressom_land_forestsuitability_acaciatortilis_n_furn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_forestsuitability_azardirachtaindicaThe 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).featuressom_land_forestsuitability_azardirachtaindicaurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_forestsuitability_azardirachtaindica0The 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).featuressom_land_forestsuitability_azardirachtaindica0urn:ogc:def:crs:EPSG::432641.891693115000066 -0.26681008899993246.15003204300007 5.060045242000058geonode:land_forestsuitability_balanitesaegyptiaca_nThe 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).featuresland_forestsuitability_balanitesaegyptiaca_nurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_forestsuitability_casuarinaequisetifThe 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).featuressom_land_forestsuitability_casuarinaequisetifurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_forestsuitability_conocarpuslancifolThe 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).featuressom_land_forestsuitability_conocarpuslancifolurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_forestsuitability_conocarpuslancifol0The 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).featuressom_land_forestsuitability_conocarpuslancifol0urn:ogc:def:crs:EPSG::432641.891693115000066 -0.26681008899993246.15003204300007 5.060045242000058geonode:som_land_forestsuitability_doberaglabra_n_faoThe 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).featuressom_land_forestsuitability_doberaglabra_n_faourn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_forestsuitability_faidherbiaalbida_nThe 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).featuressom_land_forestsuitability_faidherbiaalbida_nurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:sm_franckincense_suit_v3This 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 Agricultureland suitabilitycrop suitabilityfeaturesSoilGridssm_franckincense_suit_v3SWALIMFranckincensesoil suitabilitysomaliaurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:som_functioning_boreholes_2010Somalia Functioning Boreholes as of 2010som_functioning_boreholes_2010somaliafeaturesurn:ogc:def:crs:EPSG::432641.33650000000006 0.95008000000007151.07222200000007 11.814166000000057geonode:gcf_analysis_subwatersheds_selectedlandscapes_07112025_updatedfeaturesgcf_analysis_subwatersheds_selectedlandscapes_07112025_updatedurn:ogc:def:crs:EPSG::432642.157037968445024 -0.61093264773506450.05080386458849 9.672775640927147geonode:geology_abbate_et_al_1993General geological map of Somaliafeaturesgeology_abbate_et_al_1993urn:ogc:def:crs:EPSG::432640.99123540700003 -1.71470077399993751.409296391000055 11.981956052000044geonode:kismaayo_grazing_suit_v2This 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 suitabilitycrop suitabilitykismaayofeaturespastureSoilagriculturerangelandkismaayo_grazing_suit_v2grazingSWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:sm_camel_grazing_suit_v2This 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: 1:1,500,000land suitabilityfeaturespasturerangelandforagegrazingSWALIMcamelsomaliasm_camel_grazing_suit_v2livestockurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:sm_cattle_suit_v2This 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: 1:1,500,000land suitabilityfeaturespastureSoilGridsrangelandforagegrazingsomaliaSWALIMsm_cattle_suit_v2resiliencelivestockurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:sm_goats_suit_v2This 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: 1:1,500,000land suitabilitysm_goats_suit_v2featurespastureSoilGridsrangelandforagegrazingSWALIMsomaliaresiliencelivestockurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:sm_sheep_suit_v2This 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: 1:1,500,000land suitabilityfeaturespastureSoilGridsrangelandforagegrazingSWALIMsm_sheep_suit_v2somaliaresiliencelivestockurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:growing_period_lengthSomalia Crops Growing Length Periods based on the two rainy seasons in Somalia GU and Deyr.featuresgrowing_period_lengthurn:ogc:def:crs:EPSG::432640.98994827100006 -1.64919951599995351.41412734900007 11.985942840000064geonode:gedo_acquifersThis 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 mapgedo_acquifersfeaturesurn:ogc:def:crs:EPSG::3263840.98121671328216 1.232662241020965843.144298889537644 4.307583854094412geonode:sm_irrtigated_rice_suit_v2This 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: 1:1,500,000Irrigated Ricecrop suitabilitysm_irrtigated_rice_suit_v2featuresland suitabilityagricultureSWALIMsoil suitabilitysomaliaurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:som_irrigation_canals_faoswalim2018In 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 reducedsom_irrigation_canals_faoswalim2018featuresurn:ogc:def:crs:EPSG::432642.73301826900007 0.16467285200002445.68179011900003 4.969430761000069geonode: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.floodsgroundsevacuationhighersomaliajowhar_potential_suitable_higher_grounds_for_shabellefeaturespotentialriverjubaurn:ogc:def:crs:EPSG::432645.129924716631606 2.73575501409405145.93873155424707 3.238304687052858geonode:soil_jowhar_faoswalim_248b1dc54593c5f1150f61ba26597ce9This 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)featuressoil_jowhar_faoswalim_248b1dc54593c5f1150f61ba26597ce9urn:ogc:def:crs:EPSG::432645.49910802100004 2.68884734200003145.602213807000055 2.803132805000075geonode:jowhar_lu_soil_map_v2This 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 Mapjowhar_lu_soil_map_v2featuresRiverine AgriculturejowharshabelleSWALIMLand UnitsSoil PropertiesSoil SurveysomaliajubaWRB Classificationurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:som_juba_river_flooding_as_at_10th_nov_2019jubafloodssomaliafeatures2019riversom_juba_river_flooding_as_at_10th_nov_2019urn:ogc:def:crs:EPSG::3263842.11526662212712 -0.2674342882342359342.80374668683539 4.165473062598729geonode:som_juba_shabelle_river_floods_deyr_2013This data was produced through visual interpretation of Landsat 8 satellite images acquired between 25th September 2013 – 28th November 2013featuressom_juba_shabelle_river_floods_deyr_2013urn:ogc:def:crs:EPSG::432642.08809447589613 -0.07870897130442245.69037808363544 4.18193544803546geonode:som_juba_shabelle_river_floods_deyr_20180_0rjpvztThis data was produced through visual interpretation of Sentinel 2 satellite images acquired between 20th October 2018– 04th November 2018floodssomaliashabellesom_juba_shabelle_river_floods_deyr_20180_0rjpvztfeaturesriverjubaurn:ogc:def:crs:EPSG::432642.220535747233704 0.40368602870460945.70990331307846 4.440846822141557geonode:som_juba_shabelle_river_floods_deyr_2019This data was produced through visual interpretation of Sentinel 2 satellite images acquired between 10th October 2019 to 16th November 2019.floodssomaliashabelledeyrsom_juba_shabelle_river_floods_deyr_2019features2019riverjubaurn:ogc:def:crs:EPSG::432642.08899112364861 -0.0887757361363745.71781748826976 5.01130942700081geonode:som_floods_elnino_deyr_2023This 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 areas2023floodssomaliashabellefeaturesriverjubasom_floods_elnino_deyr_2023el ninourn:ogc:def:crs:EPSG::432640.99564999904828 -1.62330753191702148.34046489723727 6.010755708009583geonode:som_juba_shabelle_river_floods_gu_2015This data was produced through visual interpretation of Landsat 8 satellite images acquired between 8th April 2015– 26th May 2015featuressom_juba_shabelle_river_floods_gu_2015urn:ogc:def:crs:EPSG::432642.08992861188421 -0.23110793367249645.62557907256923 4.668334960946742geonode:som_juba_shabelle_river_floods_gu_2016This data was produced through visual interpretation of Sentinel 2 satellite images acquired between 26th May 2016 -13th June 2016featuressom_juba_shabelle_river_floods_gu_2016urn:ogc:def:crs:EPSG::432642.05294953470028 -0.15198514943063245.72571732483375 5.010727509187627geonode:som_juba_shabelle_river_floods_gu_20180This data was produced through visual interpretation of Sentinel 2 satellite images acquired between 23rd April 2018 to 10th May 2018floodssomaliashabellesom_juba_shabelle_river_floods_gu_201802018featuresguriverjubaurn:ogc:def:crs:EPSG::432642.078521369147836 -0.10508647124157645.74236120601893 5.070241835791818geonode:som_juba_shabelle_river_floods_gu_2019This data was produced through visual interpretation of Sentinel 2 satellite images acquired between 3rd May 2019 to 14th June 2019.floodssomaliashabellefeaturesgusom_juba_shabelle_river_floods_gu_20192019riverjubaurn:ogc:def:crs:EPSG::432642.232472919532825 -0.07137064699992445.60881497473275 4.976355666613642geonode:som_juba_shabelle_flooding_gu_2020This data was produced through visual interpretation of Sentinel 1 and Sentinel 2 satellite images acquired between April and June 2020floodssomaliasom_juba_shabelle_flooding_gu_2020shabellefeaturesgu2020riverjubaurn:ogc:def:crs:EPSG::3263842.13419985486067 -0.0351848612390307145.58338056334624 5.01041723871916geonode:som_juba_shabelle_river_floods_gu_2021This 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 2021floodssomaliashabellefeaturesriversom_juba_shabelle_river_floods_gu_2021jubaurn:ogc:def:crs:EPSG::432642.68606331186561 0.10553295664021245.67063194132099 4.808526984004745geonode:som_juba_shabelle_river_floods_gu_2021a28bfef41306This 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 2021floodssomaliasom_juba_shabelle_river_floods_gu_2021a28bfef41306shabelle2021featuresguriverjubaurn:ogc:def:crs:EPSG::432642.68606331186561 0.10553295664021245.67063194132099 4.808526984004745geonode:juba_shabelle_river_floods_gu_2023This 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 areas2023floodsjuba_shabelle_river_floods_gu_2023somaliashabellefeaturesguriverjubaurn:ogc:def:crs:EPSG::432641.69500491500003 -0.25156933799996845.758267285000045 5.011365984000065geonode:som_juba_shabelle_floods_gu_2024This 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 areasfeaturessom_juba_shabelle_floods_gu_2024urn:ogc:def:crs:EPSG::432642.04390694745172 -0.16809385325150345.719604176212506 5.010350753189595geonode:kismaayo_soilmap_soildata_v2This 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 MapkismaayofeaturesRiverine AgricultureshabelleSWALIMLand UnitsSoil PropertiesSoil SurveysomaliajubaWRB Classificationkismaayo_soilmap_soildata_v2urn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:land_covernorthThe 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.featuresland_covernorthurn:ogc:def:crs:EPSG::3263843.007251089913694 9.16294787631493344.46284752986155 10.691058244859452geonode:som_land_degradation_adeso_faoswalim2016FAO-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.featuressom_land_degradation_adeso_faoswalim2016urn:ogc:def:crs:EPSG::432646.16413400000005 6.88080700000006151.166968000000054 11.958956000000057geonode:grazesuitabilitycattle_nThe 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).featuresgrazesuitabilitycattle_nurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:grazesuitabilitygoats_nThe 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).featuresgrazesuitabilitygoats_nurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:grazesuitabilitysheep_northThe 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).featuresgrazesuitabilitysheep_northurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_land_grazesuitability_camels_s_faoswalimThe 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).featuressom_land_grazesuitability_camels_s_faoswalimurn:ogc:def:crs:EPSG::432641.89169460000005 -0.26681008699995346.150032544000055 5.060045358000025geonode:grazesuitabilitycamels_northThe 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).featuresgrazesuitabilitycamels_northurn:ogc:def:crs:EPSG::432643.01092679300007 9.16651313100004544.46210394500008 10.689748208000026geonode:grazesuitabilitycattle_southThe 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).featuresgrazesuitabilitycattle_southurn:ogc:def:crs:EPSG::432641.89169460000005 -0.26681008699995346.15003254800007 5.060045358000025geonode:som_land_degradation_care_faoswalim2015FAO-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.featuressom_land_degradation_care_faoswalim2015urn:ogc:def:crs:EPSG::432648.217400000000055 7.91069000000004550.16444000000007 10.005573000000027geonode:landcover_ne_1988The land cover has been produced from visual interpretation of LANDSAT images.featureslandcover_ne_1988urn:ogc:def:crs:EPSG::432648.01002975000006 7.05845892000002149.41157533000006 9.907768245000057geonode:landcover_ne_2007Land cover classes were created using the Land Cover Classification System (LCSS) of FAO, Landsat satellite image interpretation, and field validation.featureslandcover_ne_2007urn:ogc:def:crs:EPSG::432648.01002796000006 7.05845892000002149.411575320000054 9.907768245000057geonode:landcover_nw_2007Land cover classes were created using the Land Cover Classification System (LCSS) of FAO, Landsat satellite image interpretation, and field validation.landcover_nw_2007featuresurn:ogc:def:crs:EPSG::432643.011011490000044 9.1665131520000544.46210397400006 10.689748205000058geonode:landcover_riverine_2007Land 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.featureslandcover_riverine_2007urn:ogc:def:crs:EPSG::432641.28020095800008 -0.51021897299995146.150032544000055 5.060045358000025geonode:som_landsat8_imageindex_granuleImage 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.featuressom_landsat8_imageindex_granuleurn:ogc:def:crs:EPSG::432639.17280000000005 -2.32697999999993552.90050000000008 12.450900000000047geonode:som_landscape_nw_faoswalim20070The landscape data of north western part of Somalia defines the classes of topography and landscape units based on SRTM 90 m.featuressom_landscape_nw_faoswalim20070urn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:som_landscape_s_faoswalim20070The landscape data of southern part of Somalia defines the classes of topography and landscape units based on SRTM 90 m.featuressom_landscape_s_faoswalim20070urn:ogc:def:crs:EPSG::432641.89169460000005 -0.26681008699995346.150032544000055 5.060045358000025geonode:som_landuse_suitability_faoswalim0Landusesuitability 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.featuressom_landuse_suitability_faoswalim0urn:ogc:def:crs:EPSG::432640.989507685000035 -1.65278005299995851.41412686700005 11.988650282000037geonode:luuq_potentialsuitablehigherground_forevacuatDatasets 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 providedsomaliashabelleluuq_potentialsuitablehigherground_forevacuatfeaturesriverjubaurn:ogc:def:crs:EPSG::432642.33214392765078 3.48064089111026442.67775912689938 4.083094438539265geonode:afgooye__maize_suitability_map_v1This 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 suitabilitycrop suitabilityafgooye__maize_suitability_map_v1featuresSoilagricultureSWALIMafgooyesomaliamaizeClimateFAOurn:ogc:def:crs:EPSG::3263844.646415213680655 1.725405201515518145.166210734033186 2.1889063752801454geonode:belet_weyne_maize_suitability_v1This 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 weyneland suitabilitycrop suitabilityfeaturesSoilagricultureSWALIMbelet_weyne_maize_suitability_v1somaliamaizeClimateFAOurn:ogc:def:crs:EPSG::3263845.00259092982955 4.59854693011817645.28620156080992 5.007539076935439geonode:jowhar_maize_suitabilityThis 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 suitabilitycrop suitabilityfeaturesSoiljowhar_maize_suitabilityagriculturejowharSWALIMsomaliamaizeClimateFAOurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:kismaayo_maize_suit_v2This 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 suitabilitycrop suitabilitykismaayofeaturesSoilagriculturekismaayo_maize_suit_v2SWALIMsomaliamaizeClimateFAOurn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:sm_maize_suit_v2This 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 agricultureland suitabilitysm_maize_suit_v2crop suitabilityfeaturesrainfed agricultureSoilGridsSWALIMsoil suitabilitysomaliamaizeurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:afgooye__mango_suitability_map_v1This 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 suitabilitycrop suitabilityfeaturesafgooye__mango_suitability_map_v1SoilagricultureMangoSWALIMafgooyesomaliaClimateFAOurn:ogc:def:crs:EPSG::3263844.646415213680655 1.725405201515518145.166210734033186 2.1889063752801454geonode:belet_weyne_mango_suitability_v1This 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 weyneland suitabilitycrop suitabilityfeaturesSoilbelet_weyne_mango_suitability_v1agricultureMangoSWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::3263845.00259092982955 4.59854693011817645.28620156080992 5.007539076935439geonode:jowhar_mango_suitabilityThis 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 suitabilitycrop suitabilityfeaturesSoilagricultureMangojowhar_mango_suitabilityjowharSWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:kismaayo_mango_suit_v2This 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 suitabilitycrop suitabilitykismaayofeaturesSoilagricultureMangokismaayo_mango_suit_v2SWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:sm_mango_suit_v3_1This 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 suitabilityfeaturesSoilagricultureMangoFAOSWALIMClimatesm_mango_suit_v3_1somaliaIrrigationRainfedurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:landcover_mangroveforest0Patches 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.featureslandcover_mangroveforest0urn:ogc:def:crs:EPSG::432641.95973096000006 -1.01547584999997350.80897644000004 11.987464120000027geonode:som_mogadishu_city_poiDigital city map of Mogadishu based on local city maps, NIMA city maps, Landsat ETM+ and QB-images etc.featuressom_mogadishu_city_poiurn:ogc:def:crs:EPSG::432645.235378265000065 1.98062956300003645.39332629900008 2.083433151000065geonode:som_landcover_prosopispoints_ne_faoswalim2017GPS 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.featuressom_landcover_prosopispoints_ne_faoswalim2017urn:ogc:def:crs:EPSG::432643.19238888900003 9.36438888900005445.76041666700007 10.432416667000041geonode:som_landcover_oasisfarms_faoswalimOasis 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.featuressom_landcover_oasisfarms_faoswalimurn:ogc:def:crs:EPSG::432647.504318271000045 7.97710379500006251.07687740700004 11.37182647000003geonode:afgooye__onion_suitability_map_v1This 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 suitabilitycrop suitabilityfeaturesSoilagricultureOnionSWALIMafgooye__onion_suitability_map_v1ClimateafgooyesomaliaFAOurn:ogc:def:crs:EPSG::3263844.646415213680655 1.725405201515518145.166210734033186 2.1889063752801454geonode:belet_weyne_onion_suitability_v1This 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 weyneland suitabilitycrop suitabilityfeaturesSoilagricultureOnionbelet_weyne_onion_suitability_v1SWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::3263845.00259092982955 4.59854693011817645.28620156080992 5.007539076935439geonode:jowhar_onion_suitabilityThis 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 suitabilitycrop suitabilityjowhar_onion_suitabilityfeaturesSoilagricultureOnionjowharSWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:kismaayo_onion_suit_v2This 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 suitabilitycrop suitabilitykismaayofeaturesSoilagriculturekismaayo_onion_suit_v2OnionSWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:sm_onion_suit_v2This 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 evaluationland suitabilitycrop suitabilityfeaturesSoilagricultureOnionSWALIMClimatesomaliasm_onion_suit_v2IrrigationFAOurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:jowhar_paddy_rice_suitabilityThis 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 suitabilitycrop suitabilitypaddy ricefeaturesjowhar_paddy_rice_suitabilitySoilagriculturejowharSWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:kismaayo_paddy_rice_suit_v2This 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_v2land suitabilitycrop suitabilitypaddy ricekismaayofeaturesSoilagricultureSWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:sm_paddy_rice_suit_v3This 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: 1:1,500,000irrigated agricultureland suitabilitycrop suitabilityfeaturesricesm_paddy_rice_suit_v3SoilGridsSWALIMsoil suitabilitysomaliapaddyurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:som_police_stations_unsos2018Somalia Police Stations location as of 2018som_police_stations_unsos2018featuresurn:ogc:def:crs:EPSG::432641.00699144400005 -0.53184300899994251.26101472300007 11.914214513000047geonode:som_security_projected_risk_2018_faoswalimThis 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.featuressom_security_projected_risk_2018_faoswalimurn:ogc:def:crs:EPSG::432640.98950576800007 -1.6600613589999451.41412735100005 11.985942841000053geonode:som_rainfall_stations_faoswalim_2007Currently, 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.featuressom_rainfall_stations_faoswalim_2007urn:ogc:def:crs:EPSG::432642.10000000000008 0.05000000000006849.17605000000003 11.282650000000046geonode:water_cathments_phases_2ato7b_swsSomalia surface water resources infrastructures rehabilitated by FAO Somalia under Cash for Work Programme.featureswater_cathments_phases_2ato7b_swsurn:ogc:def:crs:EPSG::432640.99125300000003 -0.49694299999993150.503013889000044 11.229535000000055geonode:relief_nw_faoswalimThis 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.featuresrelief_nw_faoswalimurn:ogc:def:crs:EPSG::432643.01092683100006 9.1665131520000544.46210397400006 10.689748205000058geonode:belet_weyne_rice_suitability_v1This 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 weyneland suitabilitycrop suitabilityricefeaturesSoilagriculturebelet_weyne_rice_suitability_v1SWALIMsomaliaClimateFAOurn:ogc:def:crs:EPSG::3263845.00259092982955 4.59854693011817645.28620156080992 5.007539076935439geonode:som_rivers_juba_shabelle_line_faoswalimThe 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.featuressom_rivers_juba_shabelle_line_faoswalimurn:ogc:def:crs:EPSG::432642.12213516200006 -0.2511155849999845.67823791500007 4.953206862000059geonode:som_rivers_juba_shabelle_line_faoswalim2f5c1f91650eThe 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.featuressom_rivers_juba_shabelle_line_faoswalim2f5c1f91650eurn:ogc:def:crs:EPSG::432642.12213516200006 -0.2511155849999845.67823791500007 4.953206862000059geonode:som_river_shabelle_juba_poly_faoswalimA polygon layer data of Shabelle and Juba Rivers. Digitized and compiled from VHR satellite images by FAO Somalia Water and Land Information Management (SWALIM).featuressom_river_shabelle_juba_poly_faoswalimurn:ogc:def:crs:EPSG::432642.122141320000026 -0.25366943199992445.678607914000054 4.972897068000066geonode:mogadishu_city_roadsDigital city map of Mogadishu based on local citymaps, NIMA citymaps, Landsat ETM+ and QB-imagesfeaturesmogadishu_city_roadsurn:ogc:def:crs:EPSG::432645.22171107400004 1.99745707400006745.47246052700007 2.135359390000076geonode:som_flood_prone_areas_merge_of_historical0This 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 2013floodssom_flood_prone_areas_merge_of_historical0somaliafeaturesproneurn:ogc:def:crs:EPSG::432640.99564999904828 -1.62330753191702148.34046489723727 6.010755708009583geonode:som_flood_prone_areas_merge_of_historical0b4a617fc9d78This 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 2013floodssomaliashabellesom_flood_prone_areas_merge_of_historical0b4a617fc9d78featuresriverjubaurn:ogc:def:crs:EPSG::432640.99564999904828 -1.62330753191702148.34046489723727 6.010755708009583geonode:som_gedo_temporary_water_points_fao_igadDuring 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.featuressom_gedo_temporary_water_points_fao_igadurn:ogc:def:crs:EPSG::432640.99177461100004 2.07500416200002842.734553756000025 4.242148429000054geonode:som_relief_s_faoswalimThis 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_faoswalimfeaturesurn:ogc:def:crs:EPSG::432641.89169460000005 -0.26681008699995346.150032544000055 5.060045358000025geonode:som_srtm_contours_100_usgs100m resolution contours obtained from the U.S. Geological Surveyfeaturessom_srtm_contours_100_usgsurn:ogc:def:crs:EPSG::432641.11066435400005 -1.66656927599996251.443515028000036 11.963180289000036geonode:som_srtm_spot_heightsfeaturessom_srtm_spot_heightsurn:ogc:def:crs:EPSG::432641.00208126500007 -1.61666136899992851.41229783000006 11.96650088900003geonode:salty_ground_water_sourcesThis data contains areas with Salty ground waterfeaturessalty_ground_water_sourcesurn:ogc:def:crs:EPSG::432645.90456756800006 3.30184584600004948.66227248700005 6.605074081000055geonode:som_sentinel2_imageindex_granuleImage 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.featuressom_sentinel2_imageindex_granuleurn:ogc:def:crs:EPSG::432640.796693520000076 -1.89681794299997452.01094843700008 12.664549599000054geonode:afgooye_sesame_suitability_map_v1This 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 suitabilitycrop suitabilityafgooye_sesame_suitability_map_v1featuresSoilagricultureSWALIMafgooyesomaliasesameClimateFAOurn:ogc:def:crs:EPSG::3263844.646415213680655 1.725405201515518145.166210734033186 2.1889063752801454geonode:belet_weyne_sesame_suitability_v1This 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 weyneland suitabilitycrop suitabilityfeaturesSoilagricultureFAOSWALIMsomaliasesameClimatebelet_weyne_sesame_suitability_v1urn:ogc:def:crs:EPSG::3263845.00259092982955 4.59854693011817645.28620156080992 5.007539076935439geonode:jowhar_sesame_suitabilityThis 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 suitabilitycrop suitabilityfeaturesSoilagriculturejowharSWALIMsomaliasesameClimateFAOjowhar_sesame_suitabilityurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:kismaayo_sesame_suit_v2This 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 suitabilitycrop suitabilitykismaayofeaturesSoilagricultureSWALIMsomaliasesameClimateFAOkismaayo_sesame_suit_v2urn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:sm_sesame_suit_v2This 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: 1:1,500,000land suitabilitycrop suitabilityfeaturesrainfed agricultureSoilGridsSWALIMsm_sesame_suit_v2soil suitabilitysomaliasesameurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:shabelle_river_flooding_30th_oct_2019floodssomaliashabellefeatures2019rivershabelle_river_flooding_30th_oct_2019urn:ogc:def:crs:EPSG::3263844.99717216789348 2.33527355027397145.71956338915466 5.0196905090468205geonode:shabelle_hagaa_floods_11092020This data was produced through visual interpretation of Sentinel 1 and Sentinel 2 satellite images acquired between August and Septemberfloodssomaliashabellefeatures2020rivershabelle_hagaa_floods_11092020hagaaurn:ogc:def:crs:EPSG::3263844.58523412846264 1.75425061961823845.7159422715063 5.0100251749227604geonode:sm_surface_suit_v3_1This 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 mSurface Farmingfeaturesagriculturesm_surface_suit_v3_1SWALIMsoil suitabilitysomaliaFAOLand Evaluationurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:soil_100k_n_faoswalimThis dataset is about a semi detailed soil map at a scale of 1:100,000 for Dur Dur and Gibeley areas in north Somaliafeaturessoil_100k_n_faoswalimurn:ogc:def:crs:EPSG::432643.01101391000003 9.16652724400006544.46210107700006 10.689734255000076geonode:soil_100k_s_faoswalimThis datasets shows a semi detailed soil map at a scale of 1:100,000 for for Juba and Shabelle Riverine Areas in south Somalia.featuressoil_100k_s_faoswalimurn:ogc:def:crs:EPSG::432641.89169460000005 -0.26681008699995346.150032544000055 5.060045358000025geonode: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 1:10000featuressom_lower_juba_agrimask_29062021wgs_urn:ogc:def:crs:EPSG::432641.43766487200001 -1.66186493899997242.900848905000004 0.892129105000014geonode:international_disputed_borderSomalia International Disputed Bordersfeaturesinternational_disputed_borderurn:ogc:def:crs:EPSG::432632.99993896500007 -4.67648509099996154.53052902200005 19.00233268700009geonode:som_adm0_country_boundary_unochaSomalia administrative boundary , admin 0 (Country of Somalia). The source of this data is United Nation Development Programme (UNEP) 1998. UNOCHA is a contributor.featuressom_adm0_country_boundary_unochaurn:ogc:def:crs:EPSG::432640.994316999000034 -1.66491440199990851.413032532000045 11.985202789000084geonode:som_fields_2025_2024_conf03_ha02This 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.featuressom_fields_2025_2024_conf03_ha02urn:ogc:def:crs:EPSG::432641.00064769408142 -1.6415987609920149.06129093976563 10.77495928541019geonode:airfields_unsosThis layer contains data about airfields locations in Somalia. The layer is updated by the United Nations Support Office in Somalia (UNSOS)featuresairfields_unsosurn:ogc:def:crs:EPSG::432641.02911118700007 -0.38933299999996551.32642710300007 11.947440000000029geonode:som_settlements_assortedThis 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 settlementsom_settlements_assortedsettlementssomaliafeaturesurn:ogc:def:crs:EPSG::432640.99315000000007 -1.60049998799996751.28266000000008 11.960390000000075geonode:som_hydro1k_gtopo30_basinsHYDRO1k 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.featuressom_hydro1k_gtopo30_basinsurn:ogc:def:crs:EPSG::432639.47467804000007 -2.07890701299993451.45048904400005 11.996755600000029geonode:somalia_coastal_maskSomalia coast mask at a scale of 1:250,000featuressomalia_coastal_maskurn:ogc:def:crs:EPSG::432640.47221972800003 -4.9869392579999552.47144750700005 13.521183288000032geonode:som_cropland_gfsad_30m_2015The 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 2017featuressom_cropland_gfsad_30m_2015urn:ogc:def:crs:EPSG::432641.005362880000064 -1.62801678899995850.40051309200004 11.284860871000035geonode:som_hydro_crossborder_basinsSomalia 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_basinsfeaturesurn:ogc:def:crs:EPSG::432636.27611069400007 -1.81083427099997651.33075241800003 11.996755415000052geonode:somdotgrid2014The 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 dotsfeaturessomdotgrid2014urn:ogc:def:crs:EPSG::432640.95917693043627 -1.65042162274181551.41341088090561 11.987000054244614geonode:som_drainage_network_extracted_from_osmDrainage network extracted from OpenStreetMap. For more information about the data, visit --> https://wiki.openstreetmap.org/wiki/Tag:waterway%3Driverfeaturessom_drainage_network_extracted_from_osmurn:ogc:def:crs:EPSG::432640.989100816752085 -1.32933097816885251.3211743 11.9604277geonode:som_flood_prone_areas_faoswalim2018Somalia 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_faoswalim2018somaliashabelle2018featuresproneriverjubaurn:ogc:def:crs:EPSG::432642.07852136900004 -0.10508647099993645.742361206000055 5.011309427000072geonode:harbors_unsosThe source of this data is United Nations Support Office in Somalia (UNSOS)featuresharbors_unsosurn:ogc:def:crs:EPSG::432642.54626100000007 -0.36028999999996449.81773000000004 11.283660000000054geonode:harmonised_settlement_14112022OCHA Somalia Harmonised settlement 14 11 2022somaliapopulationharmonised_settlement_14112022featuressettlementsurn:ogc:def:crs:EPSG::432640.99208 -1.6375451.28266 11.96039geonode:hydromet_stations_july_2021There 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_2021somaliashabelle2021featuresbreakgesriverjubaurn:ogc:def:crs:EPSG::432642.079382 -0.35004333688383750.811797 11.96532geonode:som_idps_unhcr_2007_7f99446ce247d4f6f512eb44350f06baSomalia IDPs camp locations compiled by UNHCR 2007som_idps_unhcr_2007_7f99446ce247d4f6f512eb44350f06bafeaturesurn:ogc:def:crs:EPSG::432643.63220000000007 2.00118300000002649.19791900000007 11.286408000000051geonode:som_irrigation_schemes_faoswalim0In 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 112,950hafeaturessom_irrigation_schemes_faoswalim0urn:ogc:def:crs:EPSG::432643.69811050700008 1.1557626180000445.60011837600007 4.828188038000064geonode:som_land_degradation_faoswalimThe data of land degradation of Somalia is produced by The Food and Agriculture Organization’s Somalia Water and Land Information Management (FAO-SWALIM) projectfeaturessom_land_degradation_faoswalimurn:ogc:def:crs:EPSG::432640.989507685000035 -1.65278005299995851.41412686700005 11.988650282000037geonode:som_landforms_faoswalim20080Data of landforms have been produced from FAO Africover 2000, combined with geomorphometry. Data on topography from NASA SRTM 90 m.featuressom_landforms_faoswalim20080urn:ogc:def:crs:EPSG::432640.99214172400008 -1.66718971699992851.41272354100005 11.99218845400003geonode:som_landuse_system_faoswalim2007This landuse systems data is produced from FAO Landcover data for Somalia 2000.featuressom_landuse_system_faoswalim2007urn:ogc:def:crs:EPSG::432640.989507685000035 -1.65278005299995851.41412686700005 11.988650282000037geonode:som_livestock_trade_routes_aug2022The 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.featuressom_livestock_trade_routes_aug2022urn:ogc:def:crs:EPSG::432640.994600000089974 -1.1371680003029550.81198699990017 11.574416000398173geonode:som_major_townsDATA 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.featuressom_major_townsurn:ogc:def:crs:EPSG::432640.99829101600005 -1.03536999199997150.81222915600006 11.965310097000042geonode:labsoilData 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=0featureslabsoilurn:ogc:def:crs:EPSG::432642.25800000000004 0.03944440000003645.79119999900007 10.628200001000039geonode:som_north_aquifers_2012featuressom_north_aquifers_2012urn:ogc:def:crs:EPSG::432642.660856684000066 6.72866689200009251.40984340000006 11.981461138000043geonode:som_population_pess_2014Population 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  featuressom_population_pess_2014urn:ogc:def:crs:EPSG::432640.98950576200008 -1.65155216399995251.415153485000076 11.988532393000071geonode:som_population_pess_2014_0c5a67e3b539796c9a10edca6262848ePopulation 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 datafeaturessom_population_pess_2014_0c5a67e3b539796c9a10edca6262848eurn:ogc:def:crs:EPSG::432640.98950576200008 -1.65155216399995251.415153485000076 11.988532393000071geonode:som_prewar_rain_stations_1963_1990_faoswalimThe data is about pre-war 1963 - 1990 Somalia rainfall record stations.featuressom_prewar_rain_stations_1963_1990_faoswalimurn:ogc:def:crs:EPSG::432642.06000000000006 -0.35999999999995751.25000000000006 11.960000000000036geonode:som_primary_roads_unochaThe 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.featuressom_primary_roads_unochaurn:ogc:def:crs:EPSG::432640.93290329000007 -1.15030813199996451.13941574100005 11.958604813000022geonode:som_regional_capitalsDATA 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.featuressom_regional_capitalsurn:ogc:def:crs:EPSG::432642.219879150000054 -0.36028999099994549.18062973000008 11.28365993500006geonode:som_river_barrage_bridge_faoswalimData 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.featuressom_river_barrage_bridge_faoswalimurn:ogc:def:crs:EPSG::432642.28145333500004 0.74895508600002445.596844616000055 4.73541652800003geonode:som_river_gauging_stations_faoswalim3River 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).featuressom_river_gauging_stations_faoswalim3urn:ogc:def:crs:EPSG::432642.22314514200008 1.24477000000007445.567270000000065 4.73598000000004geonode:som_rivers_faoswalimThe 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.featuressom_rivers_faoswalimurn:ogc:def:crs:EPSG::432640.90907150600003 -1.32950972199995551.35527314300003 11.978869720000034geonode:horn_of_africa_roads_unsosThe 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.featureshorn_of_africa_roads_unsosurn:ogc:def:crs:EPSG::432634.09901703700007 -1.6547076389999851.36650595700007 11.964393999000038geonode:som_secondary_roads_adc2010This 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).featuressom_secondary_roads_adc2010urn:ogc:def:crs:EPSG::432640.99034037600006 -1.6460349019999451.25991378600003 11.958599760000027geonode:som_settlements_unocha2011_p_codedData 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: DEFINITIONsettlementssomaliasom_settlements_unocha2011_p_codedfeaturesurn:ogc:def:crs:EPSG::432640.992080000000044 -1.63753999999994451.28266000000008 11.960390000000075geonode:som_adm1_states_unochafeaturessom_adm1_states_unochaurn:ogc:def:crs:EPSG::432640.98863224200005 -1.6542382279999451.415153485000076 11.988364065000042geonode:som_water_sources_ground_faoswalimThe 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.sourcessomaliasurfacewaterfeaturessom_water_sources_ground_faoswalimurn:ogc:def:crs:EPSG::432640.99412667000007 -1.05600269999996551.28286000000003 11.953340000000026geonode:som_water_sources_ground_faoswalime805171a5d3dThe 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.sourcessurfacesomaliasom_water_sources_ground_faoswalime805171a5d3dwaterfeaturesurn:ogc:def:crs:EPSG::432640.99412667000007 -1.05600269999996551.28286000000003 11.953340000000026geonode:afgooye_sorghum_suitability_map_v1This 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 suitabilitycrop suitabilityfeaturesSoilagricultureafgooye_sorghum_suitability_map_v1SWALIMafgooyesomaliaClimatesorghumFAOurn:ogc:def:crs:EPSG::3263844.646415213680655 1.725405201515518145.166210734033186 2.1889063752801454geonode:belet_weyne_sorghum_suitability_v1This 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 weyneland suitabilitycrop suitabilityfeaturesrainfed agricultureSoilGridsbelet_weyne_sorghum_suitability_v1SWALIMsoil suitabilitysomaliasorghumurn:ogc:def:crs:EPSG::3263845.00259092982955 4.59854693011817645.28620156080992 5.007539076935439geonode:jowhar_sorghum_suitabilityThis 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 suitabilitycrop suitabilityfeaturesSoilagriculturejowharSWALIMsomaliajowhar_sorghum_suitabilityClimatesorghumFAOurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:kismaayo_sorghum_suit_v2This 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 suitabilitycrop suitabilitykismaayofeaturesSoilagriculturekismaayo_sorghum_suit_v2SWALIMsomaliaClimatesorghumFAOurn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:sm_sorghum_suit_v2This 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: 1:1,500,000land suitabilityfeaturesrainfed agricultureSoilGridssorghumsm_sorghum_suit_v2SWALIMclimate suitabilitysomaliasoil suitabilityfood securityurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:shabelle_juba_river_breakages_aug2019Breakages 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.riversomaliashabellefeaturesbreakagesjubashabelle_juba_river_breakages_aug20192019urn:ogc:def:crs:EPSG::432642.06818600000008 -0.07096999999998845.678670000000125 4.864156999999977geonode:shabelle_juba_aug_2020frrmis__w9i4apiFAO 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.riversomaliashabellefeaturesbreakagesjubashabelle_juba_aug_2020frrmis__w9i4api2020urn:ogc:def:crs:EPSG::432642.068186 -0.0709745.67867 4.89294geonode:river_juba_shabelle_breakage_aug2021_26082021SWALIM 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 2021.2021riversomaliashabellefeaturesjubariver_juba_shabelle_breakage_aug2021_26082021breakgesurn:ogc:def:crs:EPSG::432642.0680900799999 -0.0709745.6786699999999 4.89294geonode:shabelle_juba_river_breakages_feb2017A 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.featuresshabelle_juba_river_breakages_feb2017urn:ogc:def:crs:EPSG::432642.06818600000008 -0.07096999999998845.678670000000125 4.864156999999977geonode:shabelle_juba_river_breakages_feb_2018A 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.riversomaliashabelle2018breakagesfeaturesjubashabelle_juba_river_breakages_feb_2018urn:ogc:def:crs:EPSG::432642.06818600000008 -0.07096999999998845.677561622644134 4.854544026805797geonode:shabelle_juba_river_breakages_feb2019Four 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.rivershabelle_juba_river_breakages_feb2019somaliashabellefeaturesbreakagesjuba2019urn:ogc:def:crs:EPSG::432642.06818600000008 -0.07096999999998845.678670000000125 4.864156999999977geonode:shabelle_juba_breakages_feb_2022Three 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_2022rivershabellefeaturessomaliabreakagesjuba2022urn:ogc:def:crs:EPSG::432642.06809008 -0.0709745.67867 4.89294geonode:shabelle_juba_river_breakages_july2018A 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.featuresshabelle_juba_river_breakages_july2018urn:ogc:def:crs:EPSG::432642.06818600000008 -0.07096999999998845.678670000000125 4.864156999999977geonode:shabelle_juba_feb_2020frrmis_vxt8mgwFAO 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.riversomaliashabellefeaturesbreakagesjuba2020shabelle_juba_feb_2020frrmis_vxt8mgwurn:ogc:def:crs:EPSG::432642.068186 -0.0709745.67867 4.864157geonode:river_juba_shabelle_breakages_feb_2021Along 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.2021riversomaliashabellefeaturesjubariver_juba_shabelle_breakages_feb_2021breakgesurn:ogc:def:crs:EPSG::432642.06809008 -0.0709745.6786699999998 4.89294geonode:swalim_river_breakages_august_2022Four 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.riverswalim_river_breakages_august_2022somaliashabellefeaturesbreakagesjuba2022urn:ogc:def:crs:EPSG::432642.06809008 -0.0709745.6786699999998 4.89294geonode:som_juba_shabelle_river_breakages_august_2024FAO-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.featuressom_juba_shabelle_river_breakages_august_2024urn:ogc:def:crs:EPSG::432642.06270900000004 -0.09636599999993245.67867000000007 4.892940000000067geonode:river_juba_shabelle_breakage_apr2023_18042022SWALIM 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.2023river_juba_shabelle_breakage_apr2023_18042022rivershabellesomaliafeaturesbreakagesjubaurn:ogc:def:crs:EPSG::432642.06809008 -0.0709745.67867 4.89294geonode:pre_gu_2024_frmmis_march_2024FAO-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_2024riversomaliashabellefeaturesjubabreakgesurn:ogc:def:crs:EPSG::432642.06809 -0.0963745.67867 4.89294geonode:som_juba_shabelle_river_breakages_march_2025FAO-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.featuressom_juba_shabelle_river_breakages_march_2025urn:ogc:def:crs:EPSG::432642.06270899 -0.0963662745.67867 4.89294geonode:river_juba_shabelle_breakage_september_2023FAO-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.2023rivershabellefeaturessomaliabreakagesjubariver_juba_shabelle_breakage_september_2023urn:ogc:def:crs:EPSG::432642.0680900803 -0.070970000065445.67867 4.89294geonode:all_watersourcesNo abstract providedfeaturesall_watersourcesurn:ogc:def:crs:EPSG::4326-180.0 -90.0180.0 90.0geonode:strategic_water_sources_20225strategic_water_sources_20225watersomaliafeaturesurn:ogc:def:crs:EPSG::432640.995668 -1.140061551.2722594 11.42396geonode:som_strategic_water_sources_feb2018The 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 2006featuressom_strategic_water_sources_feb2018urn:ogc:def:crs:EPSG::432640.99125300000003 -1.05600269999996551.28286000000003 11.953340000000026geonode:strategic_water_sources_all_sept2020The 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 2006strategic_water_sources_all_sept2020sourcessomaliawaterfeaturesurn:ogc:def:crs:EPSG::432641.0187 -0.366951.2829 11.9533geonode:strategic_water_sources_all_sept20206557d8d4e8bdThe 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 2006sourcessomaliawaterfeatures2020strategic_water_sources_all_sept20206557d8d4e8bdurn:ogc:def:crs:EPSG::432641.0187 -0.366951.2829 11.9533geonode:reservoirsThis 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.featuresreservoirsurn:ogc:def:crs:EPSG::4326-180.0 -90.0180.0 90.0geonode:afgooye_tomato_suitability_map_v1This 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 suitabilitycrop suitabilityfeaturesSoilagricultureafgooye_tomato_suitability_map_v1ClimateSWALIMafgooyesomaliatomatoFAOurn:ogc:def:crs:EPSG::3263844.646415213680655 1.725405201515518145.166210734033186 2.1889063752801454geonode:belet_weyne_tomato_suitability_v1This 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 weyneland suitabilitycrop suitabilityfeaturesSoilagricultureSWALIMClimatesomaliatomatoFAObelet_weyne_tomato_suitability_v1urn:ogc:def:crs:EPSG::3263845.00259092982955 4.59854693011817645.28620156080992 5.007539076935439geonode:jowhar_tomato_suitabilityThis 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 suitabilitycrop suitabilityfeaturesjowhar_tomato_suitabilitySoilagriculturejowharSWALIMClimatesomaliatomatoFAOurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:kismaayo_tomato_suit_v2This 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 suitabilitycrop suitabilitykismaayofeatureskismaayo_tomato_suit_v2SoilagricultureSWALIMClimatesomaliatomatoFAOurn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:sm_tomato_suit_v2This 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: 1:1,500,000land suitabilitysm_tomato_suit_v2featuresSoilGridsirrigation agricultureSWALIMclimate suitabilitysomaliasoil suitabilitytomatourn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:som_topomapsindexThe 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.featuressom_topomapsindexurn:ogc:def:crs:EPSG::432640.99910078900007 -1.66626734699997351.499211270000046 12.000566118000052geonode:som_veryhighresolution_imageindexfeaturessom_veryhighresolution_imageindexurn:ogc:def:crs:EPSG::4326-2.627777777999938 -2.33475845399993951.332011916000056 36.70500000000004geonode:sm_vetiveria_suit_v2This 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: 1:1,500,000Vetiver grassland suitabilityfeaturesSoilGridsforagesoil conservationSWALIMerosion controlsomaliasm_vetiveria_suit_v2Vetiveriaurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:afgooye_watermelon_suitability_map_v1This 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 suitabilitycrop suitabilityfeaturesSoilagriculturewater melonSWALIMafgooyesomaliaafgooye_watermelon_suitability_map_v1ClimateFAOurn:ogc:def:crs:EPSG::3263844.646415213680655 1.725405201515518145.166210734033186 2.1889063752801454geonode:belet_weyne_watermelon_suitability_v1This 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)beletweyneland suitabilitycrop suitabilityfeaturesSoilagriculturewater melonSWALIMsomaliabelet_weyne_watermelon_suitability_v1ClimateFAOurn:ogc:def:crs:EPSG::3263845.00259092982955 4.59854693011817645.28620156080992 5.007539076935439geonode:jowhar_watermelon_suitabilityThis 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 suitabilitycrop suitabilityfeaturesSoilagriculturejowharwater melonSWALIMsomaliajowhar_watermelon_suitabilityClimateFAOurn:ogc:def:crs:EPSG::3263845.38002527814642 2.505966941617743245.75322635132957 3.0265576012996753geonode:kismaayo_watermelon_suit_v2This 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 suitabilitycrop suitabilitykismaayofeaturesSoilagricultureSWALIMClimatesomaliakismaayo_watermelon_suit_v2water melonFAOurn:ogc:def:crs:EPSG::432642.45840657117793 -0.29141377929806942.6226803822845 0.005215557978834geonode:sm_watermelon_suit_v2This 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 suitabilityfeaturesSoilGridsagriculturesm_watermelon_suit_v2cropsuitabilitySWALIMclimate suitabilitysomalia1:250000watermelonurn:ogc:def:crs:EPSG::3263840.902916811703626 -1.658686997324636551.44900467641144 12.04750671521756geonode:canal_irrigation_samplefeaturescanal_irrigation_sampleurn:ogc:def:crs:EPSG::432642.011425 -0.23206945.5976 4.892604geonode:jowhar_profile_locationfeaturesjowhar_profile_locationurn:ogc:def:crs:EPSG::3263845.43875623866943 2.680396604763231545.655300714580974 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