Congo GIS data

The raster dataset consists of a 500 m score grid for 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 logistical factors for selected crop warehouse locations: • Supply: Cereal. • 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" * 0.3) + (“Major Cities Accessibility” * 0.2) + (”Poverty” * 0.1) + ("Human Population Density" * 0.1) + (“Regional Cities Accessibility” * 0.1) +(“Port Accessibility” * 0.2) **Data publication:** 2021-10-15 **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. 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:** Crop Storage Location Score: Cereal (Congo, Rep.- ~ 500 m)

The raster dataset consists of a 500 m score grid for 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 logistical factors for selected crop warehouse locations: • Supply: Fruits. • 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" * 0.3) + (“Major Cities Accessibility” * 0.2) + (”Poverty” * 0.1) + ("Human Population Density" * 0.1) + (“Regional Cities Accessibility” * 0.1) +(“Port Accessibility” * 0.2) **Data publication:** 2021-10-15 **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. 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:** Crop Storage Location Score: Fruits (Congo, Rep.- ~ 500 m)

The raster dataset consists of a 500 m score grid for 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 logistical factors for selected crop warehouse locations: • Supply: Vegetables. • 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" * 0.3) + (“Major Cities Accessibility” * 0.2) + (”Poverty” * 0.1) + ("Human Population Density" * 0.1) + (“Regional Cities Accessibility” * 0.1) +(“Port Accessibility” * 0.2) **Data publication:** 2021-10-15 **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. 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:** Crop Storage Location Score: Vegetables (Congo, Rep.- ~ 500 m)

The raster dataset consists of a 500m 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, dairy 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): (”dairyIntensification” * 0.4) + ("Crop Production" * 0.3) + (“Major Cities Accessibility” * 0.1) + ("Cost to port" * 0.1) + ("Poverty" * 0.1) **Data publication:** 2021-10-18 **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. 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:** Dairy Processing Location Score: Cattle (Congo, Rep. - ~ 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, sheep and pigs. 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:** 2021-10-18 **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. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 and GLW 2 3. OpenStreetMap. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Slaughterhouse Location Score (Congo, Rep. - ~ 500 m)

The raster dataset consists of a 500 m score grid for 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 logistical factors for selected crop warehouse locations: • Supply: Sugar cane. • 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" * 0.3) + (“Major Cities Accessibility” * 0.2) + (”Poverty” * 0.1) + ("Human Population Density" * 0.1) + (“Regional Cities Accessibility” * 0.1) +(“Port Accessibility” * 0.2) **Data publication:** 2021-10-15 **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. 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:** Crop Storage Location Score: Sugar Cane (Congo, Rep. - ~ 500m)

Spatial distribution of estimated births across Congo 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.

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. Congo 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: Department

Point locations of airports, airstrips and airfields in Congo. Each feature includes the facility name, type, elevation and runway information where available. Use this layer for aviation planning, accessibility analysis, emergency response logistics, and transport network mapping.

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. Congo Department 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

A 1 km population raster for Congo published by Orion Terrametrics. Each cell holds a population value for the year 2020.

Flood impact data for districts in Congo, recording flooded area, cropland flooding, and directly affected population, children, and elderly. Each feature represents an administrative district with totals for the November 2023 event. Published by Orion Terrametrics.

Spatial distribution of estimated pregnancies across Congo 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.

Locations of refugee camps, IDP sites and displacement settlements in Central African Republic. Use this layer for humanitarian response planning, protection monitoring, service delivery to displaced populations, and humanitarian needs assessment.

**UNOSAT code: FL20240102COG** This map illustrates satellite-detected surface waters and landslides/mudflow extent in Brazzaville and Pool Departments, Republic of Congo, as observed from a Sentinel-2 image acquired on 28 December 2023, at 10:21 local time. Within the analysed area of 30,000 ha, approximately 190 ha of landslide scars/mudflow extent are observed and about 230 ha of land appear to be flooded. Based on Worldpop population data, the detected surface waters and the landslide scar/mudflow extent, about 15,000 people are potentially exposed or living close to landslide and flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please provide ground feedback to the United Nations Satellite Centre (UNOSAT).

**UNOSAT code: FL20240102COG** This map illustrates cumulative satellite-detected minimum floodwater using VIIRS in Republic of Congo between 29 December 2023 and 2 January 2024. Within the cloud free analysed area of about 330,000 km2, a total of about 1,000 km2 of lands appear to be affected with flood waters. Based on Worldpop population data and the minimum flood water coverage, ~114,000 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please provide ground feedback to the United Nations Satellite Centre (UNOSAT). Important note: Minimum floodwater extent indicates the portion of the pixel (375m) covered by 80 to 100% of flood water.

OpenStreetMap contains roughly 313.9 thousand buildings in this region. Based on AI-mapped estimates, this is approximately 97% of the total buildings.The average age of data for this region is 1 year, 5 months ( Last edited 2 months ago ) and 32% buildings were added or updated in the last 6 months. Read about what this summary means : indicators , metrics OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['building'] IS NOT NULL Features may have these attributes: - name - name:en - building - building:levels - building:materials - addr:full - addr:housenumber - addr:street - addr:city - office - source This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

**UNOSAT code: FL20211208COG** This map illustrates cumulative satellite-detected water using VIIRS in Republic of Congo between 03 to 07 December 2021 compared with the period between 26 to 30 November 2021. Within the cloud free analyzed areas of about 335,000 km2, a total of about 3,500 km2 of lands appear to be affected with flood waters. Water extent appears to have decreased of about 300 km2 since the period between 26 to 30 November 2021. Based on HRSL population data and the detected surface waters, the potentially exposed population of ~190,000 people is mainly located in department of Likouala with ~ 94,000 people, Brazzaville with ~ 70,000 people and Plateaux with ~10,000 people. 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).

OpenStreetMap exports for use in GIS applications. 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 This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['waterway'] IS NOT NULL OR tags['water'] IS NOT NULL OR tags['natural'] IN ('water','wetland','bay') Features may have these attributes: - name - name:en - waterway - covered - width - depth - layer - blockage - tunnel - natural - water - source This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes: - macroregion (admin-1 including region) - region (admin-2 including state, province, department, governorate) - macrocounty (admin-3 including arrondissement) - county (admin-4 including prefecture, sub-prefecture, regency, canton, commune) - localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb) The dataset also contains human settlement points and polygons for: - localities (city, town, and village) - neighbourhoods (borough, macrohood, neighbourhood, microhood) The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the README.md file for complete data source metadata. Refer to our blog post for explanation of field names. Data corrections can be proposed using Write Field, an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

**UNOSAT code: FL20191205COG** This map illustrates satellite-detected flood waters along the Congo River over, Loukoléla, Loukoléla District, Cuvette Department in Republic of Congo as observed from Pleiades-1 imagery acquired on 29 November 2019. 136 ha of potential flood waters and 168 potentially flooded structures have been identified in Loukoléla and its vicinity. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR -UNOSAT.

**UNOSAT code: FL20191205COG** This map illustrates satellite-detected waters in Epéna District, Likouala Department in Republic of Congo, as observed from Sentinel-1 imagery acquired on 10 December 2019. Within the analysed area of about 30,500 km2, based on Worldpop population data and the detected surface waters, about 7,000 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT. Important note: Flood analysis from SAR Sentinel-1 images may significantly underestimate the presence of standing waters in built up and/or densely vegetated areas due to backscattering of the radar signal.

**UNOSAT code: FL20240102COG** This map illustrates satellite-detected surface waters and landslides/mudflow extent in the Brazzaville Department, Republic of Congo, as observed from a WorldView-2 image acquired on 8 February 2024, at 10:31 local time. Within the analyzed area of 30,000 hectares, approximately 190 hectares of landslide scars/ mudflow extent are observed, and about 400 hectares of land appear to be flooded. Based on Worldpop population data, the detected surface waters and the extent of landslides/mudflows indicate that about 30,000 people are potentially exposed or living close to landslide and flooded areas. UNOSAT identified a total of 458 structures potentially affected by landslide and flood, along with 19 affected road. This is a preliminary analysis and has not yet been validated in the field. Please provide ground feedback to the United Nations Satellite Centre (UNOSAT).

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Vector dataset showcasing optimal locations for Nile tilapia cage farming systems in the Republic of the Congo. Developed under FAO’s Hand-in-Hand Initiative, geographic information systems multi-criteria evaluation suitability assessments. Intensive systems are characterized by high fish densities and the use of artificial feed. Recommended locations require the presence of permanent waters with a surface area larger than 5 acres. The score is determined by processing outputs from sub-models that describe biophysical, infrastructure, and demand factors: Criteria considered: a. Market accessibility, considering the weighted population and AWI in urban areas. b. Crop input the availability of agricultural by-products. c. Livestock input - based on the weighted animal density aggregation. The score is calculated as a simple arithmetic weighted sum of normalized or scaled grids, theoretically ranging from 0 to 100: (“Accessibility MajorUrbanAreas” X 0.50) + (“CropsInput” X 0.25) + (“LivestockInput” X 0.25) **Data publication:** 2025-03-07 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement Data sources, FAO Hand-in-Hand Geospatial Platform and OpenStreetMap (open data) including the following datasets a. Market Accessibility (urban areas) - OpenStreetMap and Atlas AI - Population Density and Asset wealth Index (Africa, 2020) - Estimated total number of people per grid-cell 1km. (Urban areas = pop density>1500 habitants/km² AND area>25km² b. Input crops - IFPRI Global Spatially-Disaggregated Crop Production Statistics Data for 2017 (MAPSPAM c. Input livestock – GLW4 : weighted animal density aggregate **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 represents top location score areas suitable for cassava 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:** 2021-10-18 **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:** Crop Storage Final Location: Cassava (Congo, Rep. - ~ 500m)

The raster dataset represents top location score areas suitable for cereal 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:** 2021-10-18 **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:** Crop Storage Final Location: Cereal (Congo, Rep. - ~ 500m)

The raster dataset represents top location score areas suitable for fruit 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:** 2021-10-18 **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:** Crop Storage Final Location: Fruits (Congo, Rep. - ~ 500m)

The raster dataset represents top location score areas suitable for vegetables 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:** 2021-10-18 **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:** Crop Storage Final Location: Vegetables (Congo, Rep. - ~ 500m)

The 500m 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 for 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. 20km (0.18 degree) buffer radius. • Major roads - approx. 2km (0.018 degree) buffer radius. • Peri urban areas are defined as being less than approx. 10 km (0.09 degree) from urban (WHERE PopDens>1500 AND area larger than 25 km²). Access to IT is characterized applying the mobile broadband coverage map. **Data publication:** 2021-11-05 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Maribel Elias](mailto:Maribel.Elias@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. 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:** Dairy Processing Final Location: Cattle (Congo, Rep. - ~ 500Km)