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Abstract:
African forest are increasingly in decline as a result of land-use conversion due to human activities.
However, a consistent and detailed characterization and mapping of land-use change that results in
forest loss is not available at the spatial-temporal resolution and thematic levels suitable for decisionmaking
at the local and regional scales; so far they have only been provided on coarser scales and
restricted to humid forests. Here we present the first high-resolution (5 m) and continental-scale
mapping of land use following deforestation in Africa, which covers an estimated 13.85% of the
global forest area, including humid and dry forests. We use reference data for 15 different land-use
types from 30 countries and implement an active learning framework to train a deep learning model
for predicting land-use following deforestation with an F1-score of 84 ± 0.7 for the whole of Africa.
Our results show that the causes of forest loss vary by region. In general, small-scale cropland is the
dominant driver of forest loss in Africa, with hotspots in Madagascar and DRC. In addition, commodity
crops such as cacao, oil palm, and rubber are the dominant drivers of forest loss in the humid forests of
western and central Africa, forming an “arc of commodity crops” in that region. At the same time, the
hotspots for cashew are found to increasingly dominate in the dry forests of both western and southeastern
Africa, while larger hotspots for large-scale croplands were found in Nigeria and Zambia. The
increased expansion of cacao, cashew, oil palm, rubber, and large-scale croplands observed in humid
and dry forests of western and south-eastern Africa suggests they are vulnerable to future land-use
changes by commodity crops, thus creating challenges for achieving the zero deforestation supply
chains, support REDD+ initiatives, and towards sustainable development goals.
