Ghana GIS data
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Railway and rail transport network of Ghana showing the extent and classification of rail infrastructure. Includes passenger and freight lines. Use this layer for rail transport planning, freight logistics analysis, infrastructure assessment, and multimodal transport mapping.
geoBoundaries ADM2 boundaries for Ghana: 260 units, representing 2019. Source: USAID Ghana HPNO, Ghana Statistical Service.
uav imagery by Western North LUSPA RCC, acquired 2025-06-26 to 2025-06-26, 45.0 cm per pixel, published on OpenAerialMap.
Administrative level 2 boundaries for Ghana, published by Orion Terrametrics. Each polygon represents a district, with attributes including district name, area, and validity dates. The dataset covers Ghana and includes 260 features.
Road and transport network of Ghana showing the classification and extent of road infrastructure. Includes primary roads, secondary roads, tracks and footpaths where available. Use this layer for route planning, accessibility analysis, transport modelling, and logistics planning.
A raster of population for Ghana, published by Orion Terrametrics. Each cell value represents the population at that location.
Spatial distribution of estimated pregnancies across Ghana 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.
Administrative boundary lines for Ghana, published by Orion Terrametrics. Each line feature represents a boundary segment with attributes for administrative level, validity dates, and version. The dataset covers Ghana and includes 790 features.
Administrative level 1 boundaries for Ghana, published by Orion Terrametrics. Each polygon represents an administrative region, with attributes including region name, area, and validity dates. The dataset covers Ghana and includes 16 features.
Point locations of named places in Burkina Faso, including streams, with coordinates, administrative codes, population and timezone. Published by Orion Terrametrics.
Polygon features representing administrative boundaries in Ghana, with names and codes for national, regional, district and local levels. Each feature carries a validity date and coordinate values. Published by Orion Terrametrics.
Point locations of educational facilities across Ghana, 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.
Spatial distribution of estimated births across Ghana 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.
A raster of population density for Ghana, published by Orion Terrametrics. Each cell value represents the population density at that location.
Point locations of health facilities in Ghana including hospitals, health centres, clinics, dispensaries and health posts. Each feature records the facility name, type and ownership. Use this layer to map healthcare coverage, identify service gaps, plan facility distribution, and support health sector analysis.
Point locations of named places in Burkina Faso, including streams, with coordinates, administrative codes, population and timezone. Published by Orion Terrametrics.
Ghana administrative level 0-2 edge-matched gazetteer, shapefiles, geodatabase, and geoservice. COD-EM datasets do not replace the authoritative COD-AB available here; however COD-EM datasets may be preferred for cartographic purposes. See caveats. These layers are suitable for database or GIS linkage to the Ghana - Subnational Population Statistics tables using the ADM0, ADM1, or ADM2_PCODE fields. Vetting by Information Technology Outreach Services (ITOS) with funding from USAID.
**UNOSAT code FL20231018GHA** This map illustrates cumulative satellite-detected water extent as observed from a Sentinel-1 imagery acquired on the 23 October 2023 at 18:10 local time. Within the analysed area of about 4,300 km², a total of about 53 km² of lands appear to be affected with flood waters. Based on Worldpop population data and the detected surface waters, about 12,000 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 the United Nations Satellite Centre (UNOSAT). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to the backscattering properties of the radar signal.
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.
A 100 m spatial resolution geotiff of walking travel time in seconds to nearest health facility in Ghana. The data was generated using the Child Poverty and Access to Services (CPAS) software (10.5281/zenodo.4638563) and was created as part of the CPAS project within the Data for Children Collaborative. The travel time is calculated assuming walking speeds on all roads, tracks, paths and land cover types. A full description is available here a video description of the data is also available here Projection system is: GCS_WGS_1984 EPSG 4326 for all
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Crop Storage Final Location: Aggregated Production, consists of a 0.01 decimal degree grid produced under the scope of the Covid-19 sub-Saharan African Corridor project pilot case, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA), for the identification and definition of recommended mobile storage locations (movable warehouses). Top10% aggregated production score grids are computed and filtered by exclusive criteria: Access to finance - Banks - 10km (0.09 degree) buffer radius; Distance from major roads - 2km (0.18 degree) buffer radius; Access to IT - Mobile broadband coverage. **Data publication:** 2020-08-03 **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 used, FAO GIS platform Hand-in-Hand, OpenStreetMap (open data), Collins Bartholomew's Mobile Coverage Explorer, 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 - Production (mt) for selected major crops (cass, yams, pltn, maiz, orts, coco, rice, grou, oilp). 3. OpenStreetMap - Roads, railways, places, points-of-interest; 4. FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports; 5. World mobile broadband coverage - derived from Collins Bartholomew's mobile coverage explorer. **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: Aggregated Production consists of a raster grid covering the country with 0.01 decimal degrees resolution, produced under the scope of the sub-Saharan Covid-19 African Corridor project pilot case, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) for the identification and definition of mobile storage recommended locations (movable warehouses). The modeling variables characterize supply, demand and accessibility, main logistical factors for warehousing facilities location. These variables are, major crops (supply), human population density (demand) and main transportation network infrastructure (accessibility). Crops included in the production aggregate are the coutry's major crops (FAOStat data):Cassava, Yams, Plantains and cooking Bananas, Maize (corn), Taro, Cocoa beans, Rice, Groundnuts, Oil palm fruit. The location score results of a simple arithmetic weighted sum calculation (cell statistics) of normalized grids, generating a location score varying from 0 to 100. The assumed weight for each of the criteria is as follows: ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + ("Port Accessibility" * 0.2) + ("Cities Accessibility" * 0.1) + ("Regional Cities Accessibility" * 0.1) **Data publication:** 2020-08-03 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement Two major sources were used, 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 • Production (mt), Crops: cass, yams, pltn, maiz, orts, coco, rice, grou, oilp; 3. OpenStreetMap - Map of the world built by volunteers and released with open-content license. Community mapping using wiki-style collaborative editing software. The data was downloaded in ESRI SHP file format for the selected countries. 4.FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports; **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0). **Online resources:**
Ghana Crop Storage Location Score: Cassava (Ghana - ~1km) consists of a raster grid covering the country with 0.01 decimal degrees resolution, produced under the scope of the sub-Saharan Covid-19 African Corridor project pilot case, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) for the identification and definition of mobile storage (movable warehouses) recommended locations. The modelling variables characterize supply, demand and accessibility, main logistical factors for warehousing facilities location. The location score for cassava variables: cassava (supply), human population density (demand) and main transportation network infrastructure (accessibility). Considered root crops were selected using FAOStat data: Cassava is the country top production in weight and a major staple. The location score (0 to 100) results from an arithmetic weighted sum calculation of normalized grids (cell statistics). The assumed weight for each of the criteria is as follows: ("Cassava Production" * 0.4) + ("Human Population Density" * 0.2) + ("Port Accessibility" * 0.2) + ("Cities Accessibility" * 0.1) + ("Regional Cities Accessibility" * 0.1) **Data publication:** 2020-08-05 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement Two major sources were used, 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 - Production (mt): cass. 3. OpenStreetMap - roads, railways and places layers. 4. FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports; **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0). **Online resources:**
Ghana crop storage location score for cereal crops, consists a raster grid covering the country with 0.01 decimal degrees resolution, produced under the scope of the sub-Saharan Covid-19 African Corridor project pilot case, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) for the identification and definition of mobile storage (movable warehouses) recommended locations. The modelling variables characterize supply, demand and accessibility, main logistical factors for warehousing facilities location. These variables are, cereal crops (supply), human population density (demand) and main transportation network infrastructure (accessibility). Considered cereal crops were selected using FAOStat data, Maize and Rice, Groundnuts (grain legume) was also included in this cluster. The location score (0 to 100) results from an arithmetic weighted sum calculation of normalized grids(cell statistics). The assumed weight for each of the criteria is as follows: ("Cereal Crops Production" * 0.4) + ("Human Population Density" * 0.2) + ("Port Accessibility" * 0.2) + ("Cities Accessibility" * 0.1) + ("Regional Cities Accessibility" * 0.1) **Data publication:** 2020-08-03 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement Two major sources were used, 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 • Production (mt), crops: maiz, rice, grou; 3. OpenStreetMap - Road, Railways and Places layers. 4. FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports; **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: Tree Crops (Ghana - ~1km) consists of a raster grid covering the country with 0.01 decimal degrees resolution, produced under the scope of the sub-Saharan Covid-19 African Corridor project pilot case, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) for the identification and definition of mobile storage (movable warehouses) recommended locations. The modeling variables characterize supply, demand and accessibility, main logistical factors for warehousing facilities location. These variables are, tree crops (supply), human population density (demand) and main transportation network infrastructure (accessibility). Considered tree crops were selected using FAOStat data, Plantains and cooking bananas, Cocoa beans, Oil palm fruit. The location score (0 to 100) results from an arithmetic weighted sum calculation of normalized grids(cell statistics). The assumed weight for each of the criteria is as follows: ("Tree Crops Production" * 0.4) + ("Human Population Density" * 0.2) + ("Port Accessibility" * 0.2) + ("Cities Accessibility" * 0.1) + ("Regional Cities Accessibility" * 0.1) **Data publication:** 2020-08-03 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement Two major sources were used, 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: Production (mt) - Crops: pltn, coco, oilp. 3. OpenStreetMap - Roads, Railways and places layer. 4. FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports; **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: Root Crops (Ghana - ~1km) consists of a raster grid covering the country with 0.01 decimal degrees resolution, produced under the scope of the sub-Saharan Covid-19 African Corridor project pilot case, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) for the identification and definition of mobile storage (movable warehouses) recommended locations. The modeling variables characterize supply, demand and accessibility, main logistical factors for warehousing facilities location. The location score for root crops variables: root crops (supply), human population density (demand) and main transportation network infrastructure (accessibility). Considered root crops were selected using FAOStat data: Cassava, Yams and Taro. The location score (0 to 100) results from an arithmetic weighted sum calculation of normalized grids (cell statistics). The assumed weight for each of the criteria is as follows: ("Cereal Crops Production" * 0.4) + ("Human Population Density" * 0.2) + ("Port Accessibility" * 0.2) + ("Cities Accessibility" * 0.1) + ("Regional Cities Accessibility" * 0.1) **Data publication:** 2020-08-03 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement Two major sources were used, 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 - Production (mt): cass, yams, orts. 3. OpenStreetMap - roads, railways and places layers. 4. FAO Data – Rivers of Africa, Inland Waters of Africa, Airports, Ports. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:**