Field data associated with blackfly/vector-control monitoring along communities and the Ose River system around the Edo–Ondo border. The underlying study says the collected data are openly available through Figshare.

Plant specimen records from Ahmadu Bello University, including taxonomy, collection information, locality and geographic information.

Georeferenced plant-occurrence data from the hill forests and Biological Garden around Obafemi Awolowo University, useful for vegetation, biodiversity and ecological mapping.

Bird observations across Nigeria, covering pentad/grid locations and dates, designed for mapping and spatio-temporal analysis. The current GBIF record was published/updated on 2 June 2026.

A current geospatial food-security classification dataset for Nigeria covering July 2026 to January 2027. The package includes downloadable Shapefile, GeoJSON and KML data representing current and projected acute food-insecurity conditions, together with near-term and medium-term projections. The resource is useful for humanitarian mapping, food-security analysis, vulnerability assessment, spatial planning and development research. Publisher: FEWS NET.

A 10 m resolution geospatial raster dataset mapping the spatial distribution of cassava and maize fields across Oyo State, southwestern Nigeria, for 2022. Crop predictions were generated using fused Sentinel-1 SAR and Sentinel-2 optical imagery, supervised machine-learning classification and field-validated ground-truth observations. The package includes GeoTIFF crop-extent layers, a combined ZIP package and README documentation. Creators include researchers from the University of Delaware, IITA, NASRDA, University of Ibadan, University of Maryland and partner institutions.

A gridded geospatial dataset representing the distance from each approximately 100 m grid-cell centre to the nearest inland waterbody in Nigeria. The dataset was produced using global inland-water data from the ESA Climate Change Initiative and geodesic distance calculations. It can support hydrological analysis, environmental modelling, agricultural suitability studies, settlement planning, water-access analysis and spatial risk assessment. Publisher: WorldPop, University of Southampton and CIESIN; source water data from the ESA Climate Change Initiative.

A collection of approximately 100 m GeoTIFF layers representing the distance from each grid cell to the nearest edge of selected ESA CCI land-cover classes in Nigeria. The layers include cultivated areas, woody-tree areas, shrub areas, herbaceous areas, sparse vegetation, aquatic vegetation, artificial surfaces and bare areas. The dataset can support landscape analysis, land-use modelling, ecological studies, agricultural analysis, fragmentation assessment and remote sensing research. Publisher: WorldPop, University of Southampton and CIESIN; source land-cover data from the ESA Climate Change Initiative.

A geospatial classification of Nigeria’s degree of urbanisation for 2025, produced using WorldPop Global2 population data and the GHSL GHS-DUG tool. The release includes 1 km GeoTIFF classification grids, spatial entities and population statistics representing different settlement and urbanisation classes across Nigeria. Publisher: WorldPop, University of Southampton, as part of the DEGURBA project

A high-resolution geospatial covariate dataset providing the distance from each approximately 100 m grid cell to the nearest built-up area across Nigeria. The dataset covers annual layers from 2015 through 2030 and combines GHSL built-up data with Microsoft Building Footprints, Google Open Buildings and World Settlement Footprint data. It is useful for urban expansion analysis, settlement accessibility, land-use modelling, population studies and spatial suitability analysis. Publisher: WorldPop, University of Southampton and CIESIN.