EVALUATING THE IMPACT OF LASRC AND SEN2COR ATMOSPHERIC CORRECTION ALGORITHMS ON LANDSAT-8/OLI AND SENTINEL-2/MSI DATA OVER AERONET STATIONS IN BRAZILIAN TERRITORY

Abstract. Accurate and consistent Surface Reflectance estimation from optical remote sensor observations is directly dependant on the used atmospheric correction processor differences caused by it may have implications further processes, e.g. classification. Brazil a continental scale country with different biomes. Recently, new initiatives, as Data Cube Project, are emerging using free open data policy data, more specifically medium spatial resolution images, to create image cubes classify Brazilian territory crops. For this reason, purpose of study verify, Landsat-8 Sentinel-2 images for territory, suitability processors maintained their providers, LaSRC USGS Sen2cor ESA, respectively. To achieve this, we tested surface reflectance products processed through comparing reference dataset computed ARCSI AERONET. The obtained results point that Landsat-8/OLI atmospherically corrected corrector other studies, while Sentinel-2/MSI performed best. Although corrections over weren’t in corrections, comparison references, most spectral bands achieved acceptable APU results.