The GHS-BUILT-S spatial raster dataset depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surf...
The GHS-BUILT-S spatial raster dataset depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surf...
The GHS-BUILT-S spatial raster dataset depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surf...
The GHS-BUILT-S spatial raster dataset depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surf...
The GHS-BUILT-S spatial raster dataset depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surf...
The GHS-BUILT-S spatial raster dataset depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surf...
This raster dataset depicts the distribution of the building heights, as Average of the Net Building Height (ANBH), generalized at the resolution of 100m, and referred to the year 2018. The input data...
The GHS-BUILT-V R2023A dataset depicts the distribution of built-up volumes, expressed as number of cubic meters. This data reports about the total built-up volume. Data are spatial-temporal interpola...
The EC JRC global map of forest cover provides a spatially explicit representation of forest presence and absence for the year 2020 at 10m spatial resolution.The year 2020 corresponds to the cut-off d...
The GHS-BUILT-V R2023A dataset depicts the distribution of built-up volumes, expressed as number of cubic meters. This data reports about the total built-up volume. Data are spatial-temporal interpola...
Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to sanitation and fo...
Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to electricity and f...
Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to piped water and f...
This dataset represents a geographic clip to Africa of the
World Database on Protected Areas (WDPA),
which is the authoritative and most complete global dataset on terrestrial and ...
This spatial dataset contains the geographic boundaries and ecological evaluations of 45 Key Landscapes for Conservation and Development (KLCDs) across Sub-Saharan Africa. Building on the K...
