Parameter 

Land Use 

Represented classes

Forest

Grassland 

Cropland 

Wetland 

Settlement 

Otherland 

No data 

Description 

Land Use change map using the data collected through Africa Open DEAL more than 300k plots collected through Collect Earth between 2019 and 2020. Timeframe of the assessment is 2000-2019.


Forest subdivisions 

Broadleaf evergreen 

Broadleaf decidious

Broadleaf mixed 

Mixed forest (brod-con)

Coniferous evergreen 

Coniferous decidious

Coniferous mixed 

Coniferous plantation 

Palm 

Other plantation 

Mangrove forest 

Riparian forest 

Eucalyptus plantation 

Acacia plantation 

Non forest 

Forest in Africa by subdivision, using the data collected through Africa Open DEAL more than 300k plots collected through Collect Earth between 2019 and 2020. Timeframe of the assessment is 2000-2019.


Grassland subdivisions 

Grassland 

Grassland with shrubs 

Grassland with trees

Grassland with trees and shrubs

Shrubland

Shrubland with trees

Lichens and mosses 

Non grasslands 

Grassland in Africa by subdivision, using the data collected through Africa Open DEAL more than 300k plots collected through Collect Earth between 2019 and 2020.  Timeframe of the assessment is 2000-2019.


Cropland subdivisions 

Land under temorary crops 

Orchard 

Palm 

Rice paddy 

Greenhouse 

Land under permanent crops 

Non cropland

Croplands in Africa by subdivision, using the data collected through Africa Open DEAL more than 300k plots collected through Collect Earth between 2019 and 2020. Timeframe of the assessment is 2000-2019.

Land Use Change - Cropland transition Heatmap 

Cropland extension: low - high 

Land Use Change hotspots of land that has been transformed to CROPLAND, using the data collected through Africa Open DEAL more than 300k plots collected through Collect Earth between 2019 and 2020. Timeframe of the assessment is 2000-2019.

Land Use Change - Deforestation Heatmap 

Deforestation: low - high 

Land Use Change hotspots of forest land that has been transformed another land use (deforestation), using the data collected through Africa Open DEAL more than 300k plots collected through Collect Earth between 2019 and 2020. Timeframe of the assessment is 2000-2019.

Tree Cover  outside of  Forest

Tree Cover % outside Forest: 

0% - 91-90% 

Percentage of trees cover in areas that are not classified as forest, using the data collected through Africa Open DEAL more than 300k plots collected through Collect Earth between 2019 and 2020. Timeframe of the assessment is 2000-2019.

Trees/ha outside of Forest 

Trees/ha outside of Forest: 

1tree/ha - >30 trees/ha

Number of single trees per hectare in areas that are not classified as forest, using the data collected through Africa Open DEAL more than 300k plots collected through Collect Earth between 2019 and 2020. Timeframe of the assessment is 2000-2019.

FAO- The African Union 

Source data

FAO/ African Union 

Methodology

More than 350 African experts with knowledge of landscapes, GIS and land uses conducted the data collection using the free open-source software tool Collect Earth. The interpretation was made throughout 2019‒2020 in 16 nationally and regionally focused workshops (Collect Earth trainings and group data collection, called Mapathons) convened by FAO in collaboration with government and regional institutions including the Panafrican Agency of the Great Green Wall (PA-GGW) and the Southern Africa Development Community (SADC). 

Sampling Design 

The assessments draw on information from more than 300,000 sampling plots in Africa. The plots were distributed over stratified systematic grids for which the continent has been divided in (i) the hyper-arid zones, which were sampled at a lower intensity (20x20 km) because of the relative homogeneity of the landscape, and (ii) the nonhyper arid areas with a sampling intensity of 10x10 km. In addition, the Great Green Wall area has had a sampling design with a denser grid (6.5x6.5 km). At the national level, some of the countries opted for higher sampling density (e.g. Tunisia 4x4 km or Eswatini 2x2 km) in order to improve the accuracy of collected data 

Collected Data

Around 120 different environmental variables and land parameters were collected, including numbers and density of trees, existence of infrastructures, wild fires etc. 

Data Accurracy

3,200 plots (or 1 percent of the total sampling plots) were randomly selected throughout the continent, and were re-interpreted by FAO experts to quantify the measurement error. The overall accuracy, also including the sampling error, is estimated at over 90 percent over the whole sample with specific parameters, with uncertainties below 3 percent.