This raster dataset provides information on crop types and their spatial extent in Senegal . 33 classes are considered: peanut, aubergine, beref, bissap, cotton, diakhatou, fonio, okra, maize, cassava, millet, cowpea, watermelon, sweet potato, chilli, irrigated rice, rainfed rice, sesame, sorghum, cherry tomato, industrial tomato, vouandzou, cabbage, onion, potato, carrot, squash, green bean, melon, cucumber, green onion, turnip, other

This raster data provides a pre-processed dataset built on top of raw data harvested by on field enumerators. Points transformed into polygons through buffers, following a data quality control (i.e. mixed crops selection, removing weeds and burnt areas, road proximity check), are classified in crop type such as: coffee, cassava, maize etc. Each datum can contain further information as comments etc. 1554 features points.

This raster data provides a pre-processed dataset built on top of raw data harvested by on field enumerators. Points transformed into polygons through buffers, following a data quality control (i.e. mixed crops selection, removing weeds and burnt areas, road proximity check), are classified in crop type such as: coffee, cassava, maize etc. Pure Crops with more than 30 samples and the 2 main mixed crops with more than 50 samples only are taken into account. Each datum can contain further information as comments etc. 1083 features points.

This raster data provides a dataset containing points harvested and classified by on field enumerators. Points are classified as cropland, non cropland. Each datum can contain further information as comments and weather the point contains mixed crop. 2602 features points.

This raster data provides a pre-processed dataset built on top of raw data harvested by on field enumerators. Points transformed into polygons through buffers, following a data quality control (i.e. mixed crops selection, removing weeds and burnt areas, road proximity check), are classified in crop type such as: coffee, cassava, maize etc. Pure Crops with more than 30 samples only are taken into account. Each datum can contain further information as comments etc. 905 features points.

This raster dataset provides information on land cover in Lesotho. 15 classes are considered: Urban, Cropland, Degraded Cropland, Forest Needleleaf, Forest Broadleaf, Water body, Wetland, River Bank, Shrubland, Grassland, Degraded Grassland, Bare surfaces, Mines, Irrigated Cropland, Gullies.

This raster data provides a pre-processed dataset built on top of raw data harvested by on field enumerators. Points, following a data quality control (i.e. mixed crops selection, removing weeds and burnt areas, road proximity check), are classified in crop type such as: coffee, cassava, maize etc. Each datum can contain further information as comments etc. 1554 features points.

This raster data provides a pre-processed dataset built on top of raw data harvested by on field enumerators. Points transformed into polygons through buffers, following a data quality control (i.e. removing weeds and burnt areas, road proximity check), are classified in Non Crop type such as: Built-up, shrubland, forest etc. Points are classified as non cropland. Each datum can contain further information as comments etc. 1917 features Polygons.

This raster data provides a dataset containing points harvested and classified by on field enumerators. Points are classified as non cropland. Each datum can contain further information as comments etc. 1344 features points.

This raster data provides a pre-processed dataset built on top of raw data harvested by on field enumerators. Points transformed into polygons through buffers, following a data quality control (i.e. mixed crops selection, removing weeds and burnt areas, road proximity check), are classified in crop type such as: coffee, cassava, maize etc. Each datum can contain further information as comments etc. 1221 features points. This dataset is used for classification algorithm calibration.