Tropical forest degradation monitoring: Radiometric issues of using both Landsat 8 and Sentinel 2 in one time series
For continuous monitoring of forest disturbance and re-growth dynamics with high temporal and spatial resolution, a dense time series of data is needed. Sentinel-2 and Landsat8 are the sensors, which are currently delivering optical data globally and free of charge. This study investigates, how data from both sensors can be integrated in a time series analysis for forest degradation monitoring in tropical areas in Malawi and Peru. Geometric inconsistencies exist and need to be eliminated before considering a time series classification approach. The differences could be removed by an automated image matching procedure. Radiometric differences in the raw data are reduced by using surface reflectance products (Landsat8) and Sen2Cor results (for Sentinel-2). The still remaining differences, mainly in the NIR and SWIR band, could be corrected by relative radiometric adjustment. First analysis of time series data show, that the magnitude of these remaining differences is much smaller than the magnitude of forest changes. Therefore, data from both sensors can be jointly used in a time series classification.