Fig. 2: Data requirements for mapping and quantifying deforestation.

Example time-series imagery from Landsat (L9), Sentinel 2 (S2B), and Google Earth (Maxar Technologies) for a mining site in Haut-Uele province, Democratic Republic of the Congo. Subsets (a–c) depict composites of shorter (red, green, blue) to longer (near infrared, short wave infrared 1, short wave infrared 2) wavelengths for Landsat 9 and Sentinel 2B imagery, illustrating that wavelengths beyond the visible capture deforestation dynamics in higher contrast and detail. Subset (d) is the only available Google Earth image available for this site (the deforestation event is completely missed). Google Earth cannot be employed for forest monitoring due to its lack of systematic acquisitions. Subset (e) shows the spatial mismatch of 0.5ha grids (white squares) on 10–30 m image subsets, illustrating that the 0.5 minimum area threshold is incompatible with Landsat and Sentinel 2 data. Subset (f) illustrates per pixel forest loss information in a graphical time-series of Sentinel 2 NDVI data for a pixel at the center of e). Such time series are required for sample interpretation and are available at the pixel scale, not at the scale of 0.5ha squares. Subsets (a–c) and (e, f) illustrate the requirements needed for operational deforestation monitoring, including appropriate spectral and spatial resolutions, a systematic global acquisition strategy, robust georeferencing, and surface reflectance correction.