Africa Burned Area Product Generation, Quality Assessment and Validation – Demonstrating a Multi-Source Land Imaging (MuSLI) Landsat-8 Sentinel-2 Capability

This proposal will generate a 30 m weekly burned area product by combination of Landsat-8, Sentinel-2A, and -2B data. The algorithm will be applied on a multi-temporal per-pixel basis with temporal consistency checks to reduce commission errors. Seamless integration of the different sensor data will be enabled by a random forest change regression that is parameterized with synthetic training data and that models reflective wavelength change considering the different sensor spectral response functions. Temporal consistency checks and active fire detections derived from Landsat-8 and Sentinel-2 and contemporaneous MODIS and VIIRS active fire detections will be used to differentiate between burned areas and spectrally similar non-fire surface changes. The product will be developed for all of Africa south of the Tropic of Cancer (23.5°N) to reflect the early continental availability of Sentinel-2B data and our long standing regional experience and collaborations. Product validation will be conducted by comparison with visually interpreted commercial high resolution data, and a field campaign, endorsed by a regional network of African fire scientists and practitioners.