Somalia GIS data

This map illustrates satellite-detected flood water extent and IDP distribtuion within the town of Belet Weyne in Belet Weyne District,Hiiran Region, Somalia. The analysis was conducted analyzing GeoEye-1 & WorldView-3 images acquired on the 30 April & 1 May 2018. As observed from the satellite image, the town of Belet Weyne is completely affected by the floods. Around 70% of the extension of the town is totally inundated, being the districts of Bulahabley, Bundaweyn, Dhagahjebis, Hilac, Hindab and Lamagalay Regional Military Based, Radar and Kutimbo completely submerged in water. The flood waters inside areas of partially flooded districts are receding. More than 110 IDP sites are located inside the town, and 50% of them are inside areas completly flooded. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.

**UNOSAT code: FL20191030SOM** This map illustrates the extent of surface waters detected over Jowhar District, Middle Shabelle Region located in Somalia, as detect by VIIRS-NOAA satellite between 30 October & 3 November 2019. In the analysed area, a total of about 700 km2 are likely flooded and about 70,000 people may be affected, based on WorldPop population estimates. The 10 km of roads seem to be affected. This is a preliminary analysis and has not been validated in the field yet. Please send ground feedback to UNITAR-UNOSAT.

A 100 m spatial resolution geotiff of walking travel time in seconds to nearest health facility in Somalia. The data was generated using the Child Poverty and Access to Services (CPAS) software (10.5281/zenodo.4638563) and was created as part of the CPAS project within the Data for Children Collaborative. The travel time is calculated assuming walking speeds on all roads, tracks, paths and land cover types. A full description is available here a video description of the data is also available here Projection system is: GCS_WGS_1984 EPSG 4326 for all

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Somalia Medium Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2011

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Somalia Current Situation FEWS NET Acute Food Insecurity Classifications Geographic data for 2011

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Somalia Near Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2011

Summary: The settlement data was derived from both the UNDP 1998 and UNDP 2005 datasets along with that of GTZ 2002, FSNAU, KEMRI and OCHA.. This data was cleaned by FAO-SWALIM and OCHA and was updated in 2022. Abstract: Point data of over 10,000 settlements within Somalia, not including IDP settlements. This dataset was compiled by various sources, GTZ, FSNAU, OCHA, Kemri and UNDP and is maintained and updated by OCHA Somalia.

This dataset provides detailed information on road surfaces from OpenStreetMap (OSM), distinguishing between **paved** and **unpaved** roads across the region. Surface classification is derived using a hybrid deep learning approach. For methodological details, see: http://arxiv.org/abs/2410.19874 Recently, we also published a new country-level dataset based on PlanetScope satellite imagery with near-complete coverage of all arterial roads. It is available on HDX under the name Somalia **Planet** Road Surface. The corresponding paper is available at: https://arxiv.org/abs/2512.04092 Road Surface Statistics Approximately 0.4947 million km of roads are mapped in OSM in this region. Based on AI-derived estimates: - Paved roads: 0.0029 million km (0.5881%) - Unpaved roads: 0.3665 million km (74.094%) About 0.1252 million km (25.3179%) of road surface information is missing in OSM. To reduce this gap, the Mapillary-derived road surface dataset provides an additional 0.0 million km (0.0006%) of the missing surface information. Intended Use This dataset supports transportation planning, infrastructure analysis, climate emissions assessment, and GIS applications. AI Features - **pred_class**: Model-predicted surface class ("paved" or "unpaved") - **pred_label**: Binary label (0 = paved, 1 = unpaved) - **osm_surface_class**: Surface classification derived from OSM tags - **combined_surface_osm_priority**: Combined classification prioritizing OSM - **combined_surface_DL_priority**: Combined classification prioritizing DL prediction - **n_of_predictions_used**: Number of predictions used for estimation - **predicted_length**: Predicted length based on DL estimation (meters) - **DL_mean_timestamp**: Mean timestamp of predictions used OSM Attributes - **name** - **name:en** - **name:* (local language)** - **highway** - **surface** - **smoothness** - **width** - **lanes** - **oneway** - **bridge** - **layer** - **source** Urban Classification Attributes - **continent** - **country_iso_a2** - **urban** (0 = rural, 1 = urban) - **urban_area** - **osm_id** - **osm_type** Data Sources The dataset originates from OpenStreetMap (OSM) and is augmented with deep learning predictions based on Mapillary street-level imagery, combined with the GHSU Global Human Settlement Urban Layer 2019 and AFRICAPOLIS 2020 urban layer. More HeiGIT datasets: https://data.humdata.org/organization/heidelberg-institute-for-geoinformation-technology More information: https://heigit.org/ Contact: communications@heigit.org

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The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Somalia Current Situation FEWS NET Acute Food Insecurity Classifications Geographic data for 2012

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Somalia Near Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2012

The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Somalia Medium Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2012

Somalia Medium Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2020

Somalia Current Situation FEWS NET Acute Food Insecurity Classifications Geographic data for 2020

Somalia Current Situation FEWS NET Acute Food Insecurity Classifications Geographic data for 2021

Somalia Current Situation FEWS NET Acute Food Insecurity Classifications Geographic data for 2022

Somalia Near Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2021

This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['railway'] IN ('rail','station') Features may have these attributes: - name - name:en - railway - ele - operator:type - layer - addr:full - addr:city - source - name:so - name:so This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

Building footprints across the area: every feature tagged `building=*`, from residential homes to hospitals, schools, and places of worship. Useful for population estimation, damage assessment, and urban planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: building - Part of the country exports on HDX by HOT

Financial services: banks, ATMs, post offices, money transfer agents, and microfinance branches tagged via `amenity`. Useful for financial-inclusion mapping, cash-distribution planning, and economic analysis. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity - Part of the country exports on HDX by HOT

On November 2, 2015 Cyclone Chapala entered the Gulf of Aden as the strongest tropical cyclone on record. The storm dropped heavy rainfall in Puntland and Somaliland. This layer shows the occurence of TC Chapala in two Somalia regions: Bari and Woqooyi Galbeed Provinces. TC Chapala first made a landfall in Yemen; however, its effects were also felt across the Gulf of Aden in Somalia where extensive rainfall was experienced in the Northern Bari region in Bosaso district, Puntland. TC Chapala was characterized by heavy rainfall that had adverse impacts in the regions. It resulted to death of over 25,000 animals and left thousands of people homeless, leaving some local nomadic tribes without any food. Impacts recorded included: Number of people affected: up to 80% of the population. Number of people worst hit: 500 families(4000ppl) Number of people displaced: 4000 Livestock destroyed: 3,000 sheep and goats and 200 camels

Global Disaster Alert and Coordination System described Cyclone Sagar as one of the strongest storms ever recorded in Somalia. This was a very rare cyclone in the Gulf of Aden that made landfall in north-western Somaliland on 19 May, 2018. This layer shows the occurence of TC Sagar in some regions of Somalia,including Awdal, Togdheer, Sool, Sanaag, Bari, Hiraan, Gedo and Lower Juba.The TC Sagar moved with wind gusts of up to 120 km/hour that delivered a year’s worth of rain to some areas in the north, that is between 150 and 200mm. TC Sagar was reported to have adverse impacts on Somalia regions. The United Nations Office for the Coordination of Humanitarian Affairs (OCHA) reported heavy rainfall, strong winds and dangerous flash floods hitting coastal areas of Puntland and Somaliland. This resulted in the loss of lives, crops and livestock as well as the destruction of property and infrastructure. Recored impacts according to regions included: Awdal, Bari, Sanaag, Sool, Togdheer Number of people affected: 228,000 Number of people displaced: 9,000 Awdal, Hiraan, Gedo, Lower Juba  Number of people affected:830,000 Number of people worst hit:170,000 Number of people displaced: 290,000 Number of people death: 50 Infrusructure destroyed:(20-40)schools and 21 health facilities

2020 Tropical Cyclone Gati struck a couple of Somalia Districts including Ceerigaabo, Ceel Afweyn, Laasqoray, Bossaso, Bandarbeyla, Caluula, Qandala and Qardho District. On November 22-23, 2020 TC Gati made landfall in northern Somalia, becoming the first hurricane-equivalent storm to hit the Horn of Africa. TC Gati originated from the Bay of Bengal. It made landfall at Ras Hafun (Northeast of Somalia) with maximum sustained winds of 170Km/hr. By 25 November 2020, TC GATI had dissipated but it left trail of destruction across Bari and Sanaag regions. Somalia villages struck by the storm included Bargaal, Gumbax, Caluula, Qandala, Lasqoray, Hadaaftimo, Badhan, Qardho, Waaciye, Ceel Dofaar, Iskushuban, Bilke, Bandarbyla, Baar-Madobe, Xaafuun, Hordio, Handa, Itaageer, Ahable, Dhaankadus, Dul Xaafuun, Dardaare, Garan, Baarmadowe, Hurdiya, Foocaar, Afdhicin, Haluula, Kurduush, , Taageer and Xandha. Tropical Cyclone Gati was the strongest storm ever recorded in the northern Indian Ocean and wreaked unimaginable damage on people and property. GATI left a trail of destruction across Bari and Sanaag regions of Somalia, disproportionately affecting coastal communities. Authorities estimated 180,000 people (30,000 households) had been affected in Puntland Regional State, with 42,000 people (7,000 households) displaced and at least eight people killed and unknown number injured, with considerable damage reported to infrastructure, livelihoods, and social services (telecommunication, electricity, roads, schools). Resultant flooding burst sewerage system and increased the risk of diseases among the affected population. The worst hit areas were Baargaal, Foocaar, Garduush, Hurdiya, and Xaafuun, Foocaar, Garduush and Garan Hoose were worst hit villages in the Indian Ocean, Bosaso and Qandala in the Gulf of Aden, and Baarmadowe.

In December 24, 1992 Tropical Cyclone 12A struck southern Bari region,bringing beneficial rainfall to the normally arid areas. This was the fourth cyclone in the Arabian Sea and the twelfth in the North Indian Ocean in 1992. The tropical disturbance that became TC12A first formed in the Maldives near the equatorial trough.  The peak intensity reached by this cyclone was 50 kt (26 m/s) just prior to landfall. TC12A weakened rapidly after making landfall in Somalia, bringing much needed rain to a dry country. It dissipated over land. Bari region was the most affected region by this storm.

This layer shows the movement path of 2018 Tropical Cyclone Sagar. Cyclone Sagar made landfall in north-western Somaliland on 19 May, 2018. It was a very rare cyclone in the Gulf of Aden. The storm moved with wind gusts of up to 120 km/hour that delivered a year’s worth of rain to some areas, that is between 150 and 200mm in some parts of the north. UNICEF was among the first to respond following the powerful tropical cyclone which caused death and widespread destruction in Hargeisa, Somaliland. As per UNICEF reports, some 170,000 were affected by Cyclone Sagar which hit the coast of north-western Somaliland and Djibouti on 18th May 2018 bringing heavy rains leading to flooding and adverse impacts. On 19th May 2018, Cyclone Sagar made landfall in western Somaliland, impacting close to 170,000 people, mainly in Awdal region. The floods in the south and the cyclone in the north destroyed crops, destroyed shelters and social service infrastructure, including water, health, nutrition, and education facilities. The Somaliland authorities estimated 50 people died and seven were still missing. In Somaliland, at least 16 people died in Galbeed and Awdal, where the cyclone made landfall. Three quarters of the livestock were killed along with major damage of water systems and health facilities and 39 schools were damaged or destroyed with a major impact on children.   By the end of 2018, more than 5.7 million people required basic health services, including critical needs in maternal and child health.

The raster dataset represents top location score areas suitable for sorghum storage, filtered by exclusive criteria: access to finance, distance to major roads, and access to IT (mobile broadband connection). Access to finance and roads are defined using a linear distance threshold: • Banks - approx. 15km buffer radius. • Major roads - approx. 5km buffer radius. • Access to IT is characterized by applying the mobile broadband coverage map - approx. 5km buffer radius. The score is achieved by processing sub-model outputs that characterize production, logistical, and socio-economic factors. The location score from 0 to 100 is then obtained through a simple arithmetic weighted sum of the normalized/scaled grids. This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (optimal location). **Data publication:** 2022-07-05 **Contact points:** Resource Contact: [FAO-Data](mailto:fao-data@fao.org) Maintainer: [Justeen De Ocampo](mailto:justeen.deocampo@fao.org) **Data lineage:** lineage statement Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets 1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. 2. Mapspam Production – IFPRI's Spatial Production Allocation Model (SPAM) estimates crop distribution within disaggregated units. 3. OpenStreetMap. 4. Altas AI - Asset Wealth Index 2020. 5. Mobile Broadband Coverage produced based on: Coverage Data © Collins Bartholomew and GSMA 2021. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Zipped raster TIF file for Crop Storage Final Location: Sorghum (Somalia - ~ 500 m)

The raster dataset represents top location score areas suitable for vegetable storage, filtered by exclusive criteria: access to finance, distance to major roads, and access to IT (mobile broadband connection). Access to finance and roads are defined using a linear distance threshold: • Banks - approx. 15km buffer radius. • Major roads - approx. 5km buffer radius. • Access to IT is characterized by applying the mobile broadband coverage map - approx. 5km buffer radius. • Access to electricity is characterized by applying the Atlas AI electricification coverage map - approx. 5km buffer radius. The score is achieved by processing sub-model outputs that characterize production, logistical, and socio-economic factors. The location score from 0 to 100 is then obtained through a simple arithmetic weighted sum of the normalized/scaled grids. This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (optimal location). **Data publication:** 2022-07-05 **Contact points:** Resource Contact: [FAO-Data](mailto:fao-data@fao.org) Maintainer: [Justeen De Ocampo](mailto:justeen.deocampo@fao.org) **Data lineage:** lineage statement Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets 1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. 2. Mapspam Production – IFPRI's Spatial Production Allocation Model (SPAM) estimates crop distribution within disaggregated units. 3. OpenStreetMap. 4. Altas AI - Asset Wealth Index 2020 and Electrification 2021. 5. Mobile Broadband Coverage produced based on: Coverage Data © Collins Bartholomew and GSMA 2021. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Zipped raster TIF file for Crop Storage Final Location: Vegetables (Somalia - ~ 500 m)

The 500 m raster dataset represents selected top location score areas filtered by exclusive criteria: access to finance, distance to major roads, access to IT, and distance to urban areas. The layer was produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The score is achieved by processing sub-model outputs that characterize production, logistical, and socio-economic factors. The top score is selected/clipped using the exclusive criteria. Access to finance, distance to roads, and urban areas are defined using a linear distance threshold: • Banks - approx. 15km buffer radius. • Major roads - approx. 5km buffer radius. • Access to IT - approx. 5km buffer radius. • Electrification - approx. 5km buffer radius. Access to IT and electricity is characterized by applying the mobile broadband coverage map and the Atlas AI Electrification map. **Data publication:** 2022-07-05 **Contact points:** Resource Contact: [FAO-Data](mailto:fao-data@fao.org) Maintainer: [Justeen De Ocampo](mailto:justeen.deocampo@fao.org) **Data lineage:** lineage statement Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets 1. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 and GLW 2). 2. OpenStreetMap. 3. Mobile Broadband Coverage produced based on: Coverage Data © Collins Bartholomew and GSMA 2021. 4. Atlas AI - Asset Wealth Index 2020 and Electrification 2021. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Zipped raster TIF file for Dairy Processing Final Location: Cattle (Somalia - ~ 500 m)

The 500 m raster dataset represents selected top location score areas filtered by exclusive criteria: access to finance, distance to major roads, access to IT, and distance to urban areas. The layer was produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The score is achieved by processing sub-model outputs that characterize production, logistical, and socio-economic factors. The top score is selected/clipped using the exclusive criteria. Access to finance, distance to roads, and urban areas are defined using a linear distance threshold: • Banks - approx. 15km buffer radius. • Major roads - approx. 5km buffer radius. • Access to IT - approx. 5km buffer radius. • Electrification - approx. 5km buffer radius. Access to IT and electricity is characterized by applying the mobile broadband coverage map and the Atlas AI Electrification map. **Data publication:** 2022-07-05 **Contact points:** Resource Contact: [FAO-Data](mailto:fao-data@fao.org) Maintainer: [Justeen De Ocampo](mailto:justeen.deocampo@fao.org) **Data lineage:** lineage statement Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets 1. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 and GLW 2). 2. OpenStreetMap. 3. Mobile Broadband Coverage produced based on: Coverage Data © Collins Bartholomew and GSMA 2021. 4. Atlas AI - Asset Wealth Index 2020 and Electrification 2021. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Zipped raster TIF file for Dairy Processing Final Location: Sheep (Somalia - ~ 500 m)

The 500 m raster dataset represents selected top location score areas filtered by exclusive criteria: access to finance, distance to major roads, access to IT, and distance to urban areas. The layer was produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The score is achieved by processing sub-model outputs that characterize production, logistical, and socio-economic factors. Access to finance, distance to roads, and urban areas are defined using a linear distance threshold: • Banks - approx. 15km buffer radius. • Major roads - approx. 5km buffer radius. • Access to IT - approx. 5km buffer radius. • Electrification - approx. 5km buffer radius. Access to IT and electricity is characterized by applying the mobile broadband coverage map and the Atlas AI Electrification map. **Data publication:** 2022-07-05 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Justeen De Ocampo](mailto:justeen.deocampo@fao.org) **Data lineage:** lineage statement Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets 1. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 and GLW 2 2. Mapspam Production – IFPRI's Spatial Production Allocation Model (SPAM) estimates of crop distribution within disaggregated units. 3. OpenStreetMap. 4. Mobile Broadband Coverage produced based on: Coverage Data © Collins Bartholomew and GSMA 2021. 5. Atlas AI - Asset Wealth Index 2020 and Electrification 2021. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Zipped raster TIF file for Slaughterhouse Final Location: Cattle, Goat, and Sheep (Somalia - ~ 500 m)