GEOSAT 2 Atmospherically Corrected Images: Algorithm Validation

Autor: César Fernández, Carolina de Castro, María Elena Calleja, Rafael Sousa, Rubén Niño, Lucía García, Silvia Fraile, Iñigo Molina
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Environmental Sciences Proceedings, Vol 29, Iss 1, p 64 (2023)
Druh dokumentu: article
ISSN: 2673-4931
DOI: 10.3390/ECRS2023-16296
Popis: Solar radiation reflected by the Earth’s surface to satellite sensors is modified by its interaction with the atmosphere. The application of atmospheric correction of optical satellite imagery is an essential and needed pre-processing tool for modeling biophysical variables, multi-temporal analysis, and digital classification processes. As a result, true surface reflectance values are obtained without atmosphere influence. To assess this process, GEOSAT (part of the ESA’s Third-Party Mission Programme) performs an optimization of the GEOSAT 2 very high resolution (VHR) multispectral imagery adapting the well-known 6S model to the different wavelengths covered by the GEOSAT 2 spectral bands (VHR, PAN). The 6S model predicts surface reflectance (BOA) using information from the apparent reflectance (TOA) captured by the satellite sensor and the corresponding atmospheric conditions. To perform the atmospheric correction (AC), both the configuration of the atmosphere at the time of capture and the conditions of scene pointing and luminosity, must be considered. The first is mainly determined by three values: water vapor, ozone, and the number of air-suspended particles (aerosols). For the latter, the geometry of the scene, as well as the respective sun and sensor observation positions are the values to be considered. To validate the resultant GEOSAT 2 AC images, obtained from applying the GEOSAT atmospheric correction algorithm, different common areas between these and Sentinel-2 L2A products have been selected. Then, band-by-band (R, G, B, and NIR) operations were performed, such as the calculation of the mean square error (RMSE) and a regression analysis. Then, spectral profiles for the three generic land coverages (vegetation, soil, and water) were also gathered over the spectral range of GEOSAT 2 and S2 corresponding bands. The outcomes, once analyzed, lead us to conclude that the results obtained by applying the promising GEOSAT AC algorithm are satisfactory and seem to correctly estimate BOA reflectance values for vegetation and water coverages. To extend the study and improve the result, ground reflectance values will be required.
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