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Produção, visualização e análise de grandes volumes de imagens de sensoriamento remoto modeladas como cubos de dados multidimensionais para todo o território brasileiro.

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O Data Cube Explorer é um portal web para visualização de cubos de dados, coleções de imagens e classificações.

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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

by R. F. B. Marujo¹, J. G. Fronza¹, A. R. Soares¹, G. R. Queiroz¹ and K. R. Ferreira¹

1National Institute for Space Research (INPE), Brazil

DOI: https://doi.org/10.5194/isprs-annals-V-3-2021-271-2021

Publisher: ISPRS | Published: 17 Jun 2021

© Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License.

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 weren’t as consistent as in Landsat-8/OLI corrections, in comparison to the surface reflectance references, most of the spectral bands achieved acceptable APU results.

Keywords: Atmospheric Correction, Sentinel-2, LaSRC, Sen2cor, AERONET, Surface Reflectance

Share and Cite

Marujo, R. F. B., Fronza, J. G., Soares, A. R., Queiroz, G. R., and Ferreira, K. R.: 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. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 271–277, 2021.

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