Effect of Atmospheric Corrections on NDVI: Intercomparability of Landsat 8, Sentinel-2, and UAV Sensors

Sentinel-2 and Landsat 8 satellites constitute an unprecedented source of freely accessible satellite imagery. To produce precise outputs from the data, however, proper use atmospheric correction methods is crucial. In this work, we tested performance six different (QUAC, FLAASH, DOS, ACOLITE, 6S, Sen2Cor), together with given by providers, non-corrected image, images acquired using unmanned aerial vehicle while working normalised difference vegetation index (NDVI) as most widely used index. We their across urban, rural, vegetated land cover types. Our results show a substantial impact choice method on resulting NDVI. Moreover, demonstrate that can increase intercomparability between data