Turkana County GIS data
＋ Follow new dataOrionGIS lists 41 open GIS datasets covering Turkana County (county code KE023, about 70,132 km²), 1 of them mapped at local scale. The most local data is listed first, followed by national layers for Kenya that include the county.
Every dataset has a map preview, its columns and sample rows, a licence and its source credited. Open any of them in a map, add them to a project or ask OrionAI about them with a free account. See also all Kenya GIS data and the other counties.
Digital Elevation Model (DEM) of Kenya showing the terrain surface elevation above sea level. Each pixel represents the elevation in metres. Use this layer for terrain analysis, slope and aspect mapping, watershed delineation, flood modelling, infrastructure siting, and visibility analysis.
Railway and rail transport network of Uganda 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.
Point locations of airports, airstrips and airfields in Uganda. 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.
Spatial distribution of estimated pregnancies across Uganda 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.
geoBoundaries ADM0 boundaries for Uganda: 1 units, representing 2017. Source: OpenStreetMap, Wambacher. Open Data Commons Open Database License 1.0
geoBoundaries ADM1 boundaries for Uganda: 4 units, representing 2017. Source: OpenStreetMap, Wambacher. Open Data Commons Open Database License 1.0
geoBoundaries ADM2 boundaries for Uganda: 151 units, representing 2006. Source: geoBoundaries, Wikimedia Commons.
geoBoundaries ADM3 boundaries for Uganda: 137 units, representing 2020. Source: Wikimedia Commons, Wikimedia Commons. The second license is Public Domain
Gridded population density of Uganda for the year 2020 at 1km resolution, adjusted to match UN national population estimates. Each grid cell shows the estimated number of people per square kilometre. Use this layer for settlement pattern analysis, infrastructure planning, service delivery optimisation, and identifying high and low density areas.
Railway and rail transport network of Kenya 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.
Point locations of educational facilities across Uganda, 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.
Point locations of health facilities in Uganda 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.
Energy infrastructure of Ethiopia including power plants, electricity transmission lines, substations and generation facilities. Use this layer for energy sector planning, electrification analysis, grid expansion studies, and renewable energy site assessment.
Locations of seaports, harbours and maritime infrastructure in Kenya. Includes commercial ports, fishing harbours and ferry terminals. Use this layer for maritime transport planning, trade logistics analysis, coastal zone management, and shipping route mapping.
Point locations of educational facilities across Kenya, 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.
Point locations of airports, airstrips and airfields in South Sudan. 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.
The Kenya Crop Land layer provides information on the extent of cropland, area specific major crop and other crops being grown in the same location. This layer was generated from the Landsat 8 - 30 meters resolution imagery data for September/October 2015 and validated using location points collected from subsequent field visits.
The Kenya Crop Land layer provides information on the extent of cropland, area specific major crop and other crops being grown in the same location. This layer was generated from the Landsat 8 - 30 meters resolution imagery data for September/October 2000 and validated using location points collected from subsequent field visits.
Data represents the Shuttle Radar Topography Mission (SRTM) 30 metres image for Kenya.These SRTM was created through mosaicking tiles and clippingto the extent of the country
geoBoundaries ADM0 boundaries for Kenya: 1 units, representing 2020. Source: RCMRD GeoPortal, geoBoundaries.
geoBoundaries ADM1 boundaries for Kenya: 47 units, representing 2020. Source: RCMRD GeoPortal, Africa GeoPortal.
Water resources and water infrastructure in Kenya including rivers, lakes, boreholes, wells and water points. Use this layer for water access analysis, WASH programme planning, drought monitoring, flood risk assessment, and water resource management.
Ward-level boundaries of Kenya (1,442 wards) from GADM 4.1. Used as zonal units for sub-county analysis, e.g. ward-level summaries within Kisumu Central.
Rivers, streams and drainage network of Kenya showing the extent and hierarchy of surface water features. Use this layer for watershed analysis, flood modelling, irrigation planning, water resource mapping, and environmental impact assessment.
47 county boundaries of Kenya from the IEBC 2019 administrative boundaries (Common Operational Datasets, HDX / OCHA RCO).
Sub-county boundaries of Kenya from the IEBC 2019 administrative boundaries (Common Operational Datasets, HDX / OCHA RCO). Includes Kisumu Central and all other sub-counties, with the parent county name on each feature.
National boundary of Kenya from the IEBC 2019 administrative boundaries (Common Operational Datasets, HDX / OCHA RCO).
This data set represents land cover map for the year 2016. This layer was clipped from Sentinel-2 global land cover data.
Spatial distribution of estimated births across Kenya 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.
Gridded population density of Kenya for the year 2020 at 1km resolution, adjusted to match UN national population estimates. Each grid cell shows the estimated number of people per square kilometre. Use this layer for settlement pattern analysis, infrastructure planning, service delivery optimisation, and identifying high and low density areas.
Point locations of health facilities in Sudan 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.
Layer showing changes in Kenya maize land areas from 2000 to 2010.
Layer showing changes in Kenya crop land areas from 2000 to 2010
Locations of markets and trading centres in Ethiopia. Includes food markets, commodity markets and informal trading points. Use this layer for economic analysis, food security assessment, supply chain mapping, market access studies, and trade route planning.
geoBoundaries ADM0 boundaries for South Sudan: 1 units, representing 2020. Source: South Sudan Information Management Working Group (IMWG), National Bureau of Statistics (NBS), and OCHA, OCHA South Sudan.
geoBoundaries ADM1 boundaries for South Sudan: 10 units, representing 2020. Source: South Sudan Information Management Working Group (IMWG), National Bureau of Statistics (NBS), and OCHA, OCHA South Sudan.