Afghanistan GIS data

**UNOSAT code: EQ20220622AFG** This map illustrates potentially damaged structures/buildings in the northern part of Spera district, Khost province of Afghanistan as detected by Worldview-3 image acquired on 23 June 2022. Within the analyzed area, UNOSAT has identified 170 damaged buildings and 3 road obstacles, amongst the 2800 buildings identified in the analyzed zone. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).

Afghanistan Current Situation FEWS NET Acute Food Insecurity Classifications Data from 2011

This layer represents irrigation schemes identified as locations of intervention for restoration activities made in Afghanistan among 2022 and 2023, in the framework of the FAO-WRI Emergency Food Security Project (EFSP), activity 2.1. **Data creation:** 2024-03-20 **Citation:** Spiller, D., Ikram, Q.D., Omid, H., Maziar, K., Sharif, S., Devale, K., and Henry, M. 2023. Irrigation schemes rehabilitation interventions under the Emergency Food Security Project in Afghanistan. Rome, FAO. **Contact points:** Resource Contact: [FAO-NSL, Matieu Henry](mailto:matieu.henry@fao.org) Resource Contact: [FAO-NSL, Dario Spiller](mailto:dario.spiller@fao.org) Resource Contact: [FAO-NSL, Qiyamud Ikram](mailto:qiyamud.ikram@fao.org) Metadata Contact: [FAO-Data](mailto:FAO-Data@fao.org) **Data lineage:** Data quality information not available **Resource constraints:** Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO **Online resources:** WMS of Locations of intervention of FAO-WRI restoration activities (Afghanistan - 2023)

The raster dataset represents top location score areas suitable for crop storage filtered by exclusive criteria: access to finance, distance to major roads and access to IT (mobile broadband connection). The location score is achieved by processing sub-model outputs characterizing logistical factors for crop warehouse siting: Supply, demand, Infrastructure/accessibility. The top score is selected/clipped using the exclusive criteria. Access to finance and roads are defined using a linear distance threshold: • Banks - approx. 20km (0.18 degree) buffer radius. • Major roads - approx. 2km (0.018 degree) buffer radius. Access to IT is characterized applying the mobile broadband coverage map. This 500m resolution raster dataset is produced under the scope 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:** 2022-12-08 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Maribel Elias](mailto:maribel.elias@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. 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. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0). **Online resources:** Zip raster for crop Storage Final Location: Cereal (Afghanistan - ~ 500 m)

The raster dataset represents top location score areas suitable for crop storage filtered by exclusive criteria: access to finance, distance to major roads and access to IT (mobile broadband connection). The location score is achieved by processing sub-model outputs characterizing logistical factors for crop warehouse siting: Supply, demand, Infrastructure/accessibility. The top score is selected/clipped using the exclusive criteria. Access to finance and roads are defined using a linear distance threshold: • Banks - approx. 20km (0.18 degree) buffer radius. • Major roads - approx. 2km (0.018 degree) buffer radius. Access to IT is characterized applying the mobile broadband coverage map. This 500m resolution raster dataset is produced under the scope 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:** 2022-12-08 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Maribel Elias](mailto:maribel.elias@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. 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. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0). **Online resources:** Zip raster TIF for crop Storage Final Location: Potato (Afghanistan - ~ 500 m)

The raster dataset represents top location score areas suitable for crop storage filtered by exclusive criteria: access to finance, distance to major roads and access to IT (mobile broadband connection). The location score is achieved by processing sub-model outputs characterizing logistical factors for crop warehouse siting: Supply, demand, Infrastructure/accessibility. The top score is selected/clipped using the exclusive criteria. Access to finance and roads are defined using a linear distance threshold: • Banks - approx. 20km (0.18 degree) buffer radius. • Major roads - approx. 2km (0.018 degree) buffer radius. Access to IT is characterized applying the mobile broadband coverage map. This 500m resolution raster dataset is produced under the scope 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:** 2022-12-08 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Maribel Elias](mailto:maribel.elias@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. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0). **Online resources:** Zip raster TIF for crop Storage Final Location: Tropical fruit (Afghanistan - ~ 500 m)

The raster dataset represents top location score areas suitable for crop storage filtered by exclusive criteria: access to finance, distance to major roads and access to IT (mobile broadband connection). The location score is achieved by processing sub-model outputs characterizing logistical factors for crop warehouse siting: Supply, demand, Infrastructure/accessibility. The top score is selected/clipped using the exclusive criteria. Access to finance and roads are defined using a linear distance threshold: • Banks - approx. 20km (0.18 degree) buffer radius. • Major roads - approx. 2km (0.018 degree) buffer radius. Access to IT is characterized applying the mobile broadband coverage map. This 500m resolution raster dataset is produced under the scope 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:** 2022-12-08 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Maribel Elias](mailto:maribel.elias@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. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0). **Online resources:** Zip raster TIF for crop Storage Final Location: Vegetables (Afghanistan - ~ 500 m)

The raster dataset represents top location score areas suitable for crop storage filtered by exclusive criteria: access to finance, distance to major roads and access to IT (mobile broadband connection). The location score is achieved by processing sub-model outputs characterizing logistical factors for crop warehouse siting: Supply, demand, Infrastructure/accessibility. The top score is selected/clipped using the exclusive criteria. Access to finance and roads are defined using a linear distance threshold: • Banks - approx. 20km (0.18 degree) buffer radius. • Major roads - approx. 2km (0.018 degree) buffer radius. Access to IT is characterized applying the mobile broadband coverage map. This 500m resolution raster dataset is produced under the scope 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:** 2022-12-07 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Maribel Elias](mailto:maribel.elias@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. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0). **Online resources:** Zip raster TIF for crop Storage Final Location: Wheat (Afghanistan - ~ 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. 10km buffer radius. • Major roads - approx. 2km buffer radius. • Access to IT is characterized by applying the mobile broadband coverage map. **Data publication:** 2023-01-30 **Contact points:** Resource Contact: [FAO-Data](mailto:fao-data@fao.org) Maintainer: [Maribel Elias](mailto:maribel.elias@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. Poverty rate. World Bank 2019. **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 Dairy Final Location Score (Afghanistan- ~ 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, electricity, 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 for the slaughterhouse facilities siting: Demand, Supply, Infrastructure/accessibility. Access to finance, distance to roads, and urban areas are defined using a linear distance threshold: • Banks - approx. 10km • Major roads - approx. 2km • Urban centers - 10km buffer radius • Access to IT and electricity is characterized by applying the mobile broadband coverage map. **Data publication:** 2023-01-27 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Maribel Elias](mailto:maribel.elias@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. Poverty rate. World Bank 2019. **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 Final Location Score (Afghanistan- ~ 500 m)

Gridded raster of population distribution for Afghanistan, published by WorldPop (University of Southampton). Each cell value measures the population count within that grid cell. The data cover Afghanistan for the year 2030.

A gridded raster showing the spatial distribution of population across Afghanistan, dated 2030. Cell values represent population counts. Published by WorldPop (University of Southampton).

AI-derived building footprint polygons for Afghanistan from Microsoft's Global ML Building Footprints, in 191 quadkey tiles of line-delimited GeoJSON, uploaded 2026-02-23.