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Understanding agricultural drivers of deforestation through remote sensing: opportunities and limitations in sub-Saharan Africa

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.

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With the support of country partners, IIED is conducting research to better understand existing and future competition and trade-offs between food production and natural forests, and the implications for land use policies in sub-Saharan Africa.

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Food demand and forests in sub-Saharan Africa

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