Effective monitoring of deforestation and cropland expansion in Africa requires reliable estimates of land cover area. However, continental-scale land cover datasets generated solely or partially through remote sensing technologies show large differences in the extent and spatial distribution of forest and cropland. In this working paper, we identify 14 of the most commonly used land cover data products, summarise their spatial, temporal, and thematic properties, and compare their estimates of forest and cropland area. We describe the limitations to land cover data that result from their divergent predictions and discuss the implications for using this data to assess the agricultural drivers of deforestation in Africa.
Understanding agricultural drivers of deforestation through remote sensing: Opportunities and limitations in Sub-Saharan Africa
Year: 2017
