Sudan GIS data
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Sudan Current Situation FEWS NET Acute Food Insecurity Classifications Data from 2018
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:** 2021-10-18 **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 OpenStreetMap data for roads, railways, rivers; UN Map country border; The HydroSHEDS 15' resolution GRID for the DEM, 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 (Sudan ~ 500m)
Accessibility to major maritime ports is modeled as raster-based travel time/cost analysis. The following ports are included: Port of Sudan 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:** 2021-10-18 **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 OpenStreetMap data for roads, railways, rivers; UN Map country border; The HydroSHEDS 15' resolution GRID for the DEM, 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 (Sudan ~ 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 Addis Ababa, Ethiopia - 5 153 002 Asmara, Eritrea - 1 258 001 Sohag, Egypt - 979 800 Wau, South Sudan - 328 651 Abeche, Chad - 83 155 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:** 2021-10-18 **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 OpenStreetMap data for roads, railways, rivers; UN Map country border; The HydroSHEDS 15' resolution GRID for the DEM, 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 (Sudan ~ 500m)
The raster dataset consists of a 500m score grid for the groundnut 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 logistical factors for selected crop warehouse locations: • Supply: Crop. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + (“Major Cities Accessibility” * 0.1) + (”Regional Cities Accessibility” * 0.1) + (“Port Accessibility” * 0.1) + (”Asset Wealth” * 0.1) **Data publication:** 2021-10-15 **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. 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. 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 TIF raster file for groundnut location score (Sudan - ~ 500 m)
The raster dataset consists of a 500m score grid for sesame seed 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 logistical factors for selected crop warehouse locations: • Supply: Crop. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + (“Major Cities Accessibility” * 0.1) + (”Regional Cities Accessibility” * 0.1) + (“Port Accessibility” * 0.1) + (”Asset Wealth” * 0.1) **Data publication:** 2021-10-15 **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. 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. 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 TIF raster file for sesame seed location score (Sudan - ~ 500 m)
The raster dataset consists of a 500m score grid for sorghum 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 logistical factors for selected crop warehouse locations: • Supply: Crop. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + (“Major Cities Accessibility” * 0.1) + (”Regional Cities Accessibility” * 0.1) + (“Port Accessibility” * 0.1) + (”Asset Wealth” * 0.1) **Data publication:** 2021-10-15 **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. 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. 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 TIF raster file for sorghum location score (Sudan - ~ 500 m)
The raster dataset consists of a 500m score grid for wheat 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 logistical factors for selected crop warehouse locations: • Supply: Crop. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + (“Major Cities Accessibility” * 0.1) + (”Regional Cities Accessibility” * 0.1) + (“Port Accessibility” * 0.1) + (”Asset Wealth” * 0.1) **Data publication:** 2021-10-15 **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. 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. 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 TIF raster file for wheat location score (Sudan - ~ 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 location score is achieved by processing sub-model outputs characterizing logistical factors dairy processing facilities siting: Supply, demand, Infrastructure/accessibility. 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. 10km buffer radius. • Major roads - approx. 2km buffer radius. Access to IT is characterized by applying the mobile broadband coverage map. **Data publication:** 2021-10-15 **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. 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. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 and GLW 2 4. Global Livestock Production Systems v.5 2011. 5. OpenStreetMap. 6. Mobile Broadband Coverage produced based on: Coverage Data © Collins Bartholomew and GSMA 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 (UHT/powder) final location (Sudan - ~ 500m)
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 dairy production intensification potential, defined using crop production, livestock production systems, and cattle distribution. The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed, livestock production systems, livestock distribution. 2. Demand - Human population density, large cities, urban areas. 3. Infrastructure - Transportation network (accessibility) It consists of an arithmetic weighted sum of normalized grids (0 to 100): (”Dairy Intensification” * 0.4) + ("Crop Production" * 0.3) + (“Major Cities Accessibility” * 0.2) + (“Population Density” * 0.1) **Data publication:** 2021-10-15 **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. 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. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 and GLW 2 4. Global Livestock Production Systems v.5 2011. 5. OpenStreetMap. **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 (UHT/powder) location score (Sudan - ~ 500m)
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 goat dairy production intensification potential, defined using crop production, livestock production systems, and goat distribution. The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed, livestock production systems, livestock distribution. 2. Demand - Human population density, large cities, urban areas. 3. Infrastructure - Transportation network (accessibility) It consists of an arithmetic weighted sum of normalized grids (0 to 100): (”Dairy Intensification” * 0.4) + ("Crop Production" * 0.3) + (“Major Cities Accessibility” * 0.2) + (“Population Density” * 0.1) **Data publication:** 2021-10-15 **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. 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. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 and GLW 2 4. Global Livestock Production Systems v.5 2011. 5. OpenStreetMap. **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 (UHT/powder) location score (Sudan - ~ 500m)
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 dairy production intensification potential, defined using crop production, livestock production systems, and sheep distribution. The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed, livestock production systems, livestock distribution. 2. Demand - Human population density, large cities, urban areas. 3. Infrastructure - Transportation network (accessibility) It consists of an arithmetic weighted sum of normalized grids (0 to 100): (”Dairy Intensification” * 0.4) + ("Crop Production" * 0.3) + (“Major Cities Accessibility” * 0.2) + (“Population Density” * 0.1) **Data publication:** 2021-10-15 **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. 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. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 and GLW 2 4. Global Livestock Production Systems v.5 2011. 5. OpenStreetMap. **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 (UHT/powder) location score (Sudan - ~ 500m)
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 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): (”Livestock Density” * 0.4) + ("Asset Wealth" * 0.3) + (“Major Cities Accessibility” * 0.2) + ("Crop Production" * 0.1) **Data publication:** 2021-10-15 **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 TIF raster file for slaughterhouse location score (Sudan - ~ 500m)
The raster dataset consists of a 500m score grid for sugarcane 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 logistical factors for selected crop warehouse locations: • Supply: Crop. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + (“Major Cities Accessibility” * 0.1) + (”Regional Cities Accessibility” * 0.1) + (“Port Accessibility” * 0.1) + (”Asset Wealth” * 0.1) **Data publication:** 2021-10-15 **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. 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. 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 TIF raster file for sugar cane location score (Sudan - ~ 500 m)
Retirement Notice: This item is in mature support as of October 2025 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Sudan Wilayah Boundaries provides a 2023 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2023 boundaries are provided by Michael Bauer Research GmbH. These were published in October 2023. Other administrative boundaries for this country are also available: Country
GLIDEnumbers are GLobal unique IDEntifiers for Disasters. Each disaster is registered in a record that contains a GLIDEnumber that uniquely identifies it and allows information to be interoperable across multiple disaster information sources, both structured and textual. Accessing disaster information can be a time consuming and laborious task. Not only is data scattered but frequently identification of the disaster can be confusing in countries with many disaster events and across borders. To address both of these issues, Asian Disaster Reduction Center (ADRC) proposed a globally common Unique ID code for disasters. Among the institutions using actively GLIDEnumbers are UN-OCHA (ReliefWeb, FSCC, HDX), UNDRR, UNDP, WMO, IFRC, FAO, the European Commission and the Centre for Research on the Epidemiology of Disasters (CRED), among many others. Country datasets are only produced for countries with at least one GLIDE event since 1 January 2022. The global dataset contains all events available from the GLIDE API, including those not assigned to a country.
The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Sudan Medium Term Projection FEWS NET Acute Food Insecurity Classifications Geographic data for 2018
July precipitation anomalies from 2013–2016 for Sudan and South Sudan, which may have negatively affected agrarian populations during the lean season, are generated from NASA TRMM/TMPA 3P43 (Tropical Rainfall Measuring Mission/Multi-Satellite Precipitation Analysis). These anomalies are available to analyze in relation local population estimates (WorldPop), reported conflict events and fatalities (Armed Conflict Locations and Events Data Project), food security classification (Integrated Phase Classification, Famine Early Warning Systems Network), and other sources for measuring crop access to water (Climate Hazards Group InfraRed Precipitation with Station data). Data were compiled by Maimouna Kante and Lisa Jordan.
The FEWS NET Data Warehouse is **currently unavailable**. Datasets on HDX that refer to the Data Warehouse have been archived. Sudan Current Situation FEWS NET Acute Food Insecurity Classifications Geographic data for 2018
Line features representing administrative boundary lines of Sudan, with each row giving the administrative level, validity dates and version. Published by Orion Terrametrics.
Rainfall and precipitation data for Sudan showing the spatial distribution of annual or seasonal rainfall. Use this layer for agricultural planning, drought monitoring, flood risk assessment, water resource management, and climate analysis.
Retirement Notice: This item is in mature support as of October 2025 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Sudan Country Boundary provides a 2023 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2023 boundaries are provided by Michael Bauer Research GmbH. These were published in October 2023. Other administrative boundaries for this country are also available: Wilayah
A raster of population density for Sudan, published by Orion Terrametrics. Each cell value represents the population density at that location.
The settlements dataset contains the location of cities, towns and villages in Sudan.
**UNOSAT code: FL20210812SDN** This map illustrates satellite detected waters and the related potentially affected croplands as deduced using a satellite Sentinel-2 image acquired on 10 August 2021 over the Aj Jazirah, Gedaref and Sennar states, Sudan. In this area, about 220 km2 of croplands appear to be likely affected by the flood waters. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
WFP Food for Education (FFE) Supported Schools in Sudan. The Microsoft Excel spread sheet contains consolidated record of FFE in in the states of Kassala, Gadaref, Gazeira, North Kordofan, Red Sea, Sennar and South Kordofan. It includes state names, locality names, locations, school names, XY coordinates (in Decimal Degrees) and education by type.
This data sets contains a shapefile with the building footprint of Wad Sherifey Refugee Settlement, Kassala, Sudan. Wad Sherifey is a refugee camp located in the East of Sudan along the Mareb River. During the past year refugees fleeing from conflict have arrived and settled in the area, partly within flood prone areas of the Mareb River. Already vulnerable and displaced, now additionally facing the risk of floods. Actors like the Red Cross Red Crescent Climate Centre and MFS manage projects in this region, and OSM data sets like this support the expansion of anticipatory action (acting before a disaster happens www.anticipation-hub.org/) to those most affected by conflict and climate. The area was selected for OSM mapping through a methodology to identify & prioritize high-risk and unmapped areas within a country for OSM mapping (StoryMap: https://arcg.is/1eqOXj) The data was collected through an HOT OSM task (https://tasks.hotosm.org/projects/11685), which was created in collaboration with MFS and led by the Netherland Red Cross’ Missing Maps Team. The task was completed (mapped & validated) in April 2022. The satellite imagery used for the mapping was from late August 2021 and provided by MFS.
The Sudan River Nile Line is a line shape file showing both the White and Blue Nile passing Sudan.
This layer contains information about the numbers of food insecure people - by first-level administrative unit - estimated for the purposes of the Integrated Context Analysis (ICA) run in Mali in 2017. It should be noted that estimates of food insecure people were available only starting from 2014 onwards and, due to access constraints, some of the states were not covered by the survey. Data source: Integrated Phase Classification (IPC), 2014-2017. The main indicators used for the analysis were the percentage of food insecure population for long-term planning and the additional population figures in case of a major shock.
This layer contains information about the flood risk - by second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Sudan in 2018. Data sources: UNEP/UNISDR, GAR 2013. The main indicators used for the analysis were the percentage of district surface at flood risk and the maximum expected frequency of flood events with a 100-year return period.
This layer contains information about the most predominant livelihood zones - by second-level administrative area - identified during the Integrated Context Analysis (ICA) run in Sudan in 2018.
This layer contains information about the natural shock risk (floods and droughts) estimated during the Integrated Context Analysis (ICA) performed in Sudan in 2018. Data sources: UNEP/UNISDR GAR 2013, HQ VAM Analysis of CHIRPS Rainfall Estimates (RFE) 1982-2017.
This layer contains information about the land degradation phenomenon - by second-level administrative area - observed for the purposes of the Integrated Context Analysis (ICA) run in Sudan in 2018. Data sources: HQ OSEP GIS Analysis of NASA MODIS 2001-2012, WorldClim 1970-2000, FAO and NASA SRTM Digital Elevation Model data. The main indicators used for the analysis were the average ecological changes observed between 2001-2005 and 2009-2013 and the percentage of erosion-prone surface.