@Article{MarujoFroSoaQueFer:2021:EvImLA,
               author = "Marujo, Rennan de Freitas Bezerra and Fronza, Jos{\'e} Guilherme 
                         and Soares, Anderson Reis and Queiroz, Gilberto Ribeiro de and 
                         Ferreira, Karine Reis",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "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",
              journal = "ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial 
                         Information Sciences",
                 year = "2021",
               volume = "3",
                pages = "271--277",
                 note = "{Pr{\^e}mio CAPES Elsevier 2023 - ODS 2: Fome zero e Agricultura 
                         sustent{\'a}vel}",
             keywords = "Atmospheric Correction, Sentinel-2, LaSRC, Sen2cor, AERONET, 
                         Surface Reflectance.",
             abstract = "Accurate and consistent Surface Reflectance estimation from 
                         optical remote sensor observations is directly dependant on the 
                         used atmospheric correction processor and the differences caused 
                         by it may have implications on further processes, e.g. 
                         classification. Brazil is a continental scale country with 
                         different biomes. Recently, new initiatives, as the Brazil Data 
                         Cube Project, are emerging and using free and open data policy 
                         data, more specifically medium spatial resolution sensor images, 
                         to create image data cubes and classify the Brazilian territory 
                         crops. For this reason, the purpose of this study is to verify, on 
                         Landsat-8 and Sentinel-2 images for the Brazilian territory, the 
                         suitability of the atmospheric correction processors maintained by 
                         their image providers, LaSRC from USGS and Sen2cor from ESA, 
                         respectively. To achieve this, we tested the surface reflectance 
                         products from Landsat-8 processed through LaSRC and Sentinel-2 
                         processed through LaSRC and Sen2cor comparing to a reference 
                         dataset computed by ARCSI and AERONET. The obtained results point 
                         that Landsat-8/OLI images atmospherically corrected using the 
                         LaSRC corrector are consistent to the surface reflectance 
                         reference and other atmospheric correction processors studies, 
                         while for Sentinel-2/MSI images, Sen2cor performed best. Although 
                         corrections over Sentinel-2/MSI data werent as consistent as in 
                         Landsat-8/OLI corrections, in comparison to the surface 
                         reflectance references, most of the spectral bands achieved 
                         acceptable APU results.",
                  doi = "10.5194/isprs-annals-V-3-2021-271-2021",
                  url = "http://dx.doi.org/10.5194/isprs-annals-V-3-2021-271-2021",
                 issn = "0924-2716",
             language = "en",
           targetfile = "marujo_evaluationg.pdf",
        urlaccessdate = "29 jun. 2024"
}