%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.27.12.31.38
%2 sid.inpe.br/marte2/2017/10.27.12.31.39
%@isbn 978-85-17-00088-1
%F 59640
%T Avaliação de modelos de correção atmosférica para a estimativa do total de sólidos em suspensão no reservatório de Barra Bonita via imagem OLI/Landsat-8
%D 2017
%A Bernardo, Nariane Marselhe Ribeiro,
%A Alcântara, Enner Herenio,
%A Rodrigues, Thanan Walesza Pequeno,
%A Watanabe, Fernanda Sayuri Yoshino,
%@electronicmailaddress narianebernardo@gmail.com
%E Gherardi, Douglas Francisco Marcolino,
%E Aragão, Luiz Eduardo Oliveira e Cruz de,
%B Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)
%C Santos
%8 28-31 maio 2017
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 1995-2002
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X The atmosphere contains gases and molecules that affect the signal registered by remote sensors. These effects might be minimized in order to provide suitable surface reflectance (Rsup) values in aquatic systems. The atmospheric correction methods aim to minimize such interferences and avoid the under or overestimation of remote sensing reflectance (Rrs). Accurate Rrs provides better information about the state of aquatic system, it means, establishing the concentration of aquatic compounds accurately. The aim of this study was to assess the outputs from five atmospheric correction methods (Dark Object Subtraction - DOS; Quick Atmospheric Correction QUAC; Fast Line-of-sight Atmospheric Analysis of Hypercubes - FLAASH; Atmospheric Correction for OLI lite ACOLITE, and Provisional Landsat-8 Surface Reflectance Algorithm - L8SR). The main purpose was to investigate the suitability of Rrs for estimating total suspended matter concentrations (TSM) in Barra Bonita Hydroelectrical Reservoir. To establish TSM concentrations via atmospherically corrected Operational Land Imager (OLI) scene, the TSM retrieval model was calibrated and validated with in situ data. Thereby, the achieved results from TSM retrieval model application demonstrated that L8SR was able to provide the most suitable Rrs values for green and red spectral bands, and consequently, the lowest TSM retrieval errors (Mean Absolute Percentage Error ranged from 8% to 128%, respectively). In the near-infrared band, retrieving Rrs is still a challenge for all the tested algorithms.
%9 Áreas úmidas e águas interiores
%@language pt
%3 59640.pdf