Somalia GIS data
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This layer shows movement path of 2019 Tropical Cyclone Pawan in Somalia. A Tropical Storm initially named 06A formed in the northern Indian Ocean and later developed into a Tropical Cyclone named Pawan after sustaining wind speeds of more than 39mph (48kph) and heavy rain for two days. TC Pawan spread its clouds as far northwest as Oman and Yemen on its way to Somalia. It made landfall in Somalia on 7th December 2019 on the Coastal side of Puntland (Bossaso, Garowe). The worst hit areas by 2019 TC Pawan included Nugaal Region (Eyl and Dangorayo Districts), Karkaar (Qardho District) and Bari Region (Alula, Iskushuban, and Baargaal Districts) who are under Garowe Somalia Red Crescent Society (SRCS) Branch) and the Coastal villages of Hafun, Iskushuban, Baargaal, Quandala and Alula Districts in Bari Region (under Bosasso SRCS Branch). Other areas affected include the coastal villages in Bari Region including Hafun, Iskushuban, Baargaal, Quandala and Alula districts. Most affected households needed urgent humanitarian assistance as they were already living in dire conditions prior to the crisis. The destruction and flooding caused by TC Pawan increased the vulnerability of communities and heightened the impact of the ever -challenging climatic extremes. The assessment estimated that 35,600 households, representing a population of 213,600 people had been affected. The assessment further estimated the affected population to represented 60-70% of the entire Bari and Nugaal Regions.
This layer shows the movement path of 2012 TC Murjan. The cyclonic storm, Murjan formed over the south Arabian Sea in association with an active inter tropical convergence zone during last week of October 2012. It was the first cyclone over the north Indian Ocean during this year. Moving west southwestwards, it crossed Somalia's coast between 1700 and 1800 UTC of 25th October near lat. 9.80N and 50.80E. Though the Ocean Heat Content was less over the southwest Arabian Sea (50-80 KJ/cm2) and further less near Somalia's coast (less than 50 KJ/cm2) as well as SST (26-280C), the system could maintain its intensity of cyclonic storm till landfall, basically due to low to moderate vertical wind shear. After the landfall, due to land interaction, it weakened into a deep depression over coastal Somalia at 1800 UTC of 25th October. It further weakened into a depression over Somalia in the morning of 26th October while moving west-southwest wards.
1984 Tropical Cyclone 04B was a weak storm that struck eastern Somalia in Mudug province, and quickly dissipated. The storm had a maximunm windspeed of 18m/s before dessipating. The cyclone was detected on 23/11/1984. Mudug landfall was on 7/12/1984. There were no reports of damages or injuries from this storm.
Tropical Cyclone 1A became the first documented tropical cyclone to move through the Gulf of Aden. The tropical storm struck about 65 km (40 mi) west of Berbera District, Somalia and quickly dissipated. TC1A had a windspeed of 23m/s before dissipating. TC1A is the only tropical cyclone to develop in the North Indian Ocean during the Spring transition season. After developing in the western Arabian Sea, the cyclone turned to the west-southwest and transited through the Gulf of Aden rather than moving to the north or northwest along the climatologically favored track and making landfall along the east coast of the Arabian Peninsula. The disturbance which eventually developed into TC1A was first detected on 23rd May,1984 as an area of strong convection centered approximately 180 nm (333 km) southeast of Socotra. This layer shows Districts hit by 1984 Tropical Cyclone 1A. This was a weak storm and no damages were reported.
A disturbance which became Tropical Cyclone 05A was first noted on the 7th November,1994 by Significant Tropical Weather Advisory (ABIO) at 9N 54E. It was embedded within a widespread area of convection associated with broad troughing. This layer shows TC05A hitting two Somalia Districts, Bossaso and Eyl, on 20thNovember, 1994. The storm produced a maximum wind speed of 104Km/hr(65mph). The storm's high winds and rainfall were catastrophic to the districts. It killed 30 people and injured hundreds of others. Several boats and homes were washed away.
Tropical cyclones hitting Somalia Districts for the period between 1984 to 2020. This layer indicates the frequency of cyclone occurence within specific regions. The cyclones recorded include: 1984 Tropical Cyclone 1A 1984 Tropical Cyclone 4B 1992 Tropical Cyclone 12A 1994 Tropical Cyclone 05A 1997 Tropical Cyclone 03A 2004 Tropical Cyclone Agni 2010 Tropical Cyclone Bandu 2012 Tropical Cyclone Murjan 2013 Tropical Cyclone 3A 2015 Tropical Cyclone Chapala 2015 Tropical Cyclone Megh 2018 Tropical Cyclone Sagar 2019 Tropical Cyclone Pawan 2020 Tropical Cyclone Gati
Tropical Cyclone Bandu was named after Tropical Storm 02A moving into the Gulf of Aden. This layer shows TC Bandu hitting Bossaso District on May 21, 2010. Bandu had maximum sustained winds near 45 knots (52 mph) and was 50 miles north-northwest of Cape Guardafui, Somalia. Tropical Storm Bandu resulted in flooding, and displaced approximately 12,000 people in Bari,17000 along Shabelle River and 2,000 people in Jamaame town, Lower Juba Region, as well as Afgooye and Kurtunwaarey districts, Lower Shabelle Region. In response to identified humanitarian needs, the U.N. Children’s Fund (UNICEF) and non-governmental organization (NGO) partners provided support for garbage collection and WASH activities. In addition, UNHCR distributed blankets and plastic sheeting to flood-affected residents of Bossaso town, Bari Region.
2019 Tropical Cyclone Pawan struck Eyl and Qurdho Districts in Somalia. TC Pawan was intially named Tropical Storm 06A which originated from northern Indian Ocean. TC Pawan spread its clouds as far northwest as Oman and Yemen on its way to Somalia as observed by NASA Worldview, Earth Observing System Data and Information System (EOSDIS). It made landfall in Somalia on 7th December 2019 on the Coastal side of Puntland. The storm influenced Somalia's weather patterns. Heavy rain and wind gusts of 80 km/h were reported in the region. Somali Water and Land Information Management (SWALIM) said some areas in Puntland recorded more than 3 times their long term mean annual rainfall during the storm. Eyl District recorded a total of 260mm in two days. Villages struck by the storm include Dangorayo, Karkaar, Hafun, Iskushuban, Baargaal, Quandala and Alula in Bari Region. 2019 TC Pawan had adverse impacts on Somalia. It was reported that 35,600 households, representing a population of 213,600 people had been affected. 2 people died following floods in Las Qoray (Sanaag Region). Roads connecting the town to the rest of the region were damaged. In central Somalia, River Shabelle flooded displacing over 1,500 people. Summary of impacts according to affected districts: Eyl,Qardho, Qandala: People Affected: 213600 (35600 HH) i.e. pastoralists 15,000 HH, fishing communities 7500 HH, rural-urban settlements 11600 HH including IDPs, farmers 1500 HH Household destroyed: 31500 (5250 households)
2018 Tropical Cyclone Saga struck several districts in Somalia. These include Bai, Lughaye, Zeylac, Laasqoray, Bossaso, Caluula, Iskushuban, Qardho and Garoowe District. TC Sagar originated from Yemen where it had caused flooding and wind damage. On 19 May, 2018 TC Sagar made landfall in north-western Somaliland. It 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. Villages struck by the storm include Lughaya, Zeila, Baki, Bareeda, Caluula, Murcanyo, Gumbax and Xaabo. On 19 May, TC Sagar made landfall in western Somaliland, impacting close to 170,000 people, mainly in Awdal region. The storm destroyed crops, 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. Summary of the storm's impacts according to districts: Galbeed, Laasqoray, Qardho, Ishkushban, Bossaso, Garowe People displaced: 1,780 families People affected: 669,000 Houses destroyed: 80 families Death: 52 People Injured: 12 Missing persons: 27(Mainland) and 4(Fishermen) Disrupted services: 5 in Bossaso and Garoowe Bareeda, Caluula, Murcanyo, Gumbax, and some parts of Xaabo People Missing: In Puntland 35 houses, 15 small boats. In Tawakal, 220 improvised houses for IDPS were washed away. 30 boats in Caluula and 20 small boats in Bosaso seaport. In Berber 125 families. In Ceel Sheekh, 15 shelters destroyed. Livestock lost: In Puntland 56 camels, nearly 1,260 goats and sheep and 19 donkeys died.
On October 25, 2012 Cyclonic Storm Murjan struck Bayla District of eastern Somalia, bringing heavy rainfall of over 40 mm (1.6 in) and gusty winds to the country and neighboring Ethiopia. This layer shows the occurence of TC Murjan in Bari Region. TC Murjan formed over the south Arabian Sea in association with an active inter tropical convergence zone during last week of October 2012. It was the first cyclone over the north Indian Ocean during that year. Moving west southwestwards, it crossed Somalia coast between 1700 and 1800 UTC of 25th October near lat. 9.80N and long. 50.80E. Though the Ocean Heat Content was less over the southwest Arabian Sea (50-80 KJ/cm2) and further less near Somalia coast (less than 50 KJ/cm2) as well as SST (26-280C), the system could maintain its intensity of cyclonic storm till landfall, basically due to low to moderate vertical wind shear. TC Murjan brougt heavy rainfalls to Somalia. This resulted to flash flooding which washed away livestock and bridges in Bari region, causing some fatalities. A total of 100,000 livestock died. Districts impacted in the region included Bossasso, Ishkushban, Bandar Beyla, Garowe and Eyl Districts.
This layer shows the movement path of Tropical Cyclone 03A. 2013 TC03A formed off the north-east coast of Somalia across the Indian Ocean, moving directly towards the coast of the country in the following days. The storm produced a wind speed of 74 kph (46 mph) and (100-200)mm of rain. It caused heavy rains with flooding and gale force winds in the Somali region of Puntland. The cyclone caused loss of human lives and the destruction of assets including livestock and fishing boats, destroyed numerous settlements, service centers, roads, schools, communication and electrical installations. The most affected areas included, Dangorayo, Bandar Beyla, Garowe and Eyl districts. Other areas affected include the coastal villages in Bari region including Hafun, Iskushuban, Bargal, Qandala and Allula districts. It was estimated that overall, 142,380 persons were affected by the disasters, with 8,523 households being worst hit and 1,435 households having lost all their livestock. It was also reported that there were approximately 80 deaths mostly of children and the elderly who were most vulnerable to hypothermia and exposure. Makeshift structures for pastoralists were conspicuously absent or just frames, likely destroyed or damaged by high winds and rains. Numerous water sources were flooded, no longer serviceable or contaminated in some areas. There were unconfirmed disease outbreaks and contamination of water sources from decaying animal remains. Thousands of livestock were reported dead as a consequence of icy rain, which was noted in the aerial assessment. FAO estimated 800,000 livestock were in the affected area. Anecdotal evidence suggested a less than 10 per cent survival rate for livestock in the hardest hit areas.
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is a biophysical dimensionless quantity (its values range from 0/no absorption to 1/total absorption) used to assess the greenness and health of vegetation. FAPAR anomalies can be used as an indicator to detect and monitor the impacts of agricultural drought on the growth and productivity of vegetation. The data is presented in 10-day time composite of the Visible Infrared Imaging Radiometer Suite (VIIRS).
Accessibility to major cities dataset is modeled as raster-based travel time/cost analysis, computed for the largest cities (>50k habitants) in the country. 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 (or optimal location). **Data publication:** 2022-06-28 **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 Produced using 1. OpenStreetMap data for roads, railways, and rivers; 2. UN Map country border. 3. The HydroSHEDS 15' resolution GRID for the DEM. 4. GHSL - Global Human Settlement Layer. **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 accessibility to major cities (Somalia ~ 500m)
Accessibility to major maritime ports is modelled as raster-based travel time/cost analysis. The following ports are included: Port of Mogadishu Port of Kismayo Port of Bassaso Port of Berbera 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:** 2022-06-28 **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 Produced using 1. OpenStreetMap data for roads, railways, and rivers; 2. UN Map country border. 3. The HydroSHEDS 15' resolution GRID for the DEM. 4. GHSL - Global Human Settlement Layer. **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 accessibility to ports (Somalia ~ 500m)
Accessibility to regional cities dataset is modeled as raster-based travel time/cost analysis, computed for the largest cities surrounding the country. The following cities are included: City - Population Djibouti, Djibouti - 567 602 Addis Ababa, Ethiopia - 5 153 002 Nairobi, Kenya - 7 626 752 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 (or optimal location). **Data publication:** 2022-06-28 **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 Produced using 1. OpenStreetMap data for roads, railways, and rivers; 2. UN Map country border. 3. The HydroSHEDS 15' resolution GRID for the DEM. 4. GHSL - Global Human Settlement Layer. **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 accessibility to regional cities (Somalia ~ 500m)
The raster dataset consists of a 500 m score grid for the crop storage location, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The location score is achieved by processing sub-model outputs that characterize considered factors for crop warehouse location: • Supply: Sorghum. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. • Socio-economic/poverty: Asset wealth index. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + (”Asset Wealth” * 0.1) + (“Major Cities Accessibility” * 0.1) + (“Regional Cities Accessibility” * 0.1) + (“Port Accessibility” * 0.1). **Data publication:** 2022-07-04 **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 of crop distribution within disaggregated units. 3. OpenStreetMap. 4. Poverty – Atlas AI 2020. **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 Location Score: Sorghum (Somalia - ~ 500 m)
The raster dataset consists of a 500 m score grid for the crop storage location, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The location score is achieved by processing sub-model outputs that characterize considered factors for crop warehouse location: • Supply: Vegetables. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. • Socio-economic/poverty: Asset wealth index. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + (”Asset Wealth” * 0.1) + (“Major Cities Accessibility” * 0.1) + (“Regional Cities Accessibility” * 0.1) + (“Port Accessibility” * 0.1). **Data publication:** 2022-07-04 **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 of crop distribution within disaggregated units. 3. OpenStreetMap. 4. Poverty – Atlas AI 2020. **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 Location Score: Vegetables (Somalia - ~ 500 m)
The raster dataset consists of a 500 m score grid for dairy processing industry facilities siting, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The analysis is based on cattle production potential using proximity to cities and cattle density. The score is achieved by processing sub-model outputs that characterize production, logistical, and socio-economic factors. 1. Supply - Feed and livestock distribution. 2. Infrastructure - Transportation network (accessibility). 3. Atlas AI Asset Wealth Index. It consists of an arithmetic weighted sum of normalized grids (0 to 100): (”Cattle Density” * 0.4) + (“Major Cities Accessibility” * 0.4) + (”Asset Wealth” *0.2 ) **Data publication:** 2022-07-04 **Contact points:** Resource Contact: [FAO-Data](mailto:fao-data@fao.org) Maintainer: [Justeen De Ocampo](mailto:justeen.deocampo@fao.org) **Data lineage:** lineage statement 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. Altas AI - Asset Wealth Index 2020. **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 Location Score: Cattle (Somalia - ~ 500 m)
The raster dataset consists of a 500 m score grid for dairy processing industry facilities siting, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The analysis is based on sheep production potential using proximity to cities and sheep density. The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed and livestock distribution. 2. Infrastructure - Transportation network (accessibility). 3. Atlas AI Asset Wealth Index. It consists of an arithmetic weighted sum of normalized grids (0 to 100): (”Sheep Density” * 0.4) + (“Major Cities Accessibility” * 0.4) + (”Asset Wealth” *0.2 ) **Data publication:** 2022-07-04 **Contact points:** Resource Contact: [FAO-Data](mailto:fao-data@fao.org) Maintainer: [Justeen De Ocampo](mailto:justeen.deocampo@fao.org) **Data lineage:** lineage statement 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. Altas AI - Asset Wealth Index 2020. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:**
The raster dataset consists of a 500 m score grid for slaughterhouse industry facilities, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The analysis is based on livestock production potential using proximity to cities, crop production, and aggregated density of cattle, goats, and sheep. The score is achieved by processing sub-model outputs that characterize production, logistical, and socio-economic factors. 1. Supply - Feed and livestock distribution. 2. Infrastructure - Transportation network (accessibility) 3. Atlas AI Asset Wealth Index. It consists of an arithmetic weighted sum of normalized grids (0 to 100): (”Livestock Density” * 0.4) + ("Asset Wealth" * 0.3) + (“Major Cities Accessibility” * 0.2) + ("Crop Production" * 0.1) **Data publication:** 2022-07-04 **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 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. Altas AI - Asset Wealth Index 2020. **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 Location Score: Cattle, Goat, and Sheep (Somalia - ~ 500 m)
Line features representing undetermined boundaries in Somalia, each tagged with an administrative level and validity dates. Published by Orion Terrametrics.
A 1-kilometre raster of population for Somalia for 2020, where each cell value represents the number of people. Published by Orion Terrametrics.
Point locations of educational facilities across Somalia, including primary schools, secondary schools and other learning institutions. Each feature records the facility name, type and administrative location. Use this layer to map education access, identify underserved areas, plan school placement, and analyse catchment areas and travel distances to schools.
Polygon boundaries of land plots and districts in Somalia. Each polygon represents a named plot with its district, registration year and month, area and source. Published by Orion Terrametrics.
Line features representing administrative boundaries of Somalia, published by Orion Terrametrics. Each feature is a boundary line with an administrative level and validity dates. The version is v03, valid from 8 January 2025.
Polygon boundary of Somalia at administrative level 0, with a single feature representing the country and including ISO codes, area in square kilometers, center coordinates, and validity dates. Published by Orion Terrametrics.
Polygon boundaries of operational zone level 2 (OPZ2) areas in Somalia, with each feature representing an OPZ2 area and including names and codes for OPZ1, adm2, adm1, and adm0, area in square kilometers, and validity dates. Published by Orion Terrametrics.
Line features representing administrative boundaries in Somalia, with each line having an administrative level and validity dates. Published by Orion Terrametrics.
Point features marking second-level operational zones in Somalia, such as MOG-1, MOG-2 and MOG-3 in Daynile district of Banadir. Each point carries coordinates, zone and parent zone names and identifiers, district, region and country names and codes, and validity dates. Published by Orion Terrametrics.
Spatial distribution of estimated pregnancies across Somalia at 1km resolution. Each grid cell shows the estimated number of pregnancies including live births, stillbirths and abortions. Use this layer for maternal health planning, antenatal care programme design, health facility placement, and reproductive health analysis.
Polygon features covering second-level operational zones in Somalia, such as MOG-1, MOG-2 and MOG-3 in Daynile district of Banadir. Each feature records zone names and identifiers, parent district, region and country names and codes, area in square kilometres, and validity dates. Published by Orion Terrametrics.
Point features marking administrative places in Somalia, from national level down through named regions such as Awdal and Bakool. Each point carries coordinates, administrative names and codes, and a validity date of 8 January 2025. Published by Orion Terrametrics.
Spatial distribution of estimated births across Somalia at 1km resolution. Each grid cell shows the estimated number of live births. Use this layer for maternal health planning, antenatal care facility siting, health resource allocation, and reproductive health programme design.
Water resources and water infrastructure in Somalia including rivers, lakes, boreholes, wells and water points. Use this layer for water access analysis, WASH programme planning, drought monitoring, flood risk assessment, and water resource management.