Wall-to-wall mapping of tree extent in the tropics with Sentinel-1 and Sentinel-2

Abstract

Remote sensing based assessments of tree cover and extent provide insight into global and local land use planning. However, there remains considerable uncertainty about the distribution of tree cover in drylands and in areas with non-forest land use. Here, we present a 10-m map of tree extent for 4.35 billion hectares in the tropics (-23.44° to 23.44° latitude) based on multitemporal composites of Sentinel-1 and Sentinel-2 analyzed with convolutional neural networks, from which we derive spatially aggregated tree cover data at a 70-m (0.49 ha) resolution. We identify 2719 million hectares of tropical land with ≥10% tree cover, including 680 million hectares in tropical drylands. We find that 52% of tropical cropland and 46% of tropical urban areas had ≥10% tree cover in 2020. Compared to previous datasets, we demonstrate improved ability to map tree extent in areas with high canopy cover heterogeneity and with open canopy cover, especially in drylands, urban areas, and on cropland. As such, this data is expected to enable improved monitoring of tree cover distributions at local scales.