@Article{AlcāntaraCurtStec:2016:ReItHy,
author = "Alc{\^a}ntara, Enner and Curtarelli, Marcelo Pedroso and Stech,
Jos{\'e} Luiz",
affiliation = "{Universidade Estadual Paulista (UNESP)} and {Instituto Nacional
de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "Estimating total suspended matter using the particle
backscattering coefficient: Results from the Itumbiara
hydroelectric reservoir (Goi{\'a}s State, Brazil)",
journal = "Remote Sensing Letters",
year = "2016",
volume = "7",
number = "4",
pages = "397--406",
month = "Jan.",
abstract = "In this study, a quasi-analytical algorithm (QAA)-based model was
parameterized using remote-sensing reflectance (Rrs, units in
sr1), total absorption coefficient (at) and total suspended matter
(TSM) concentration. The model was based on the particle
backscattering at 561 nm (bbp(561)) and was derived from the QAA
and TSM concentration. The aim of this work was to parameterize a
QAA-based model to estimate the TSM concentration using the
Landsat-8 Operational Land Imager (OLI) sensor in the Itumbiara
hydroelectric reservoir, Brazil. The results demonstrated that the
calibrated model, TSM = 0:907 + 5:479 × bbp(561) +, had a
coefficient of determination of R2= 0.70 and that the validation
had an R2= 0.82, RMSE = 41.39% and a mean bias of 0.074 mg l-1.
The primary observation using the TSM and bbp(561) maps is that
waters with lower bbp(561) values have lower TSM concentrations;
there is a direct correlation between bbp(561) and TSM
concentration.",
doi = "10.1080/2150704X.2015.1137646",
url = "http://dx.doi.org/10.1080/2150704X.2015.1137646",
issn = "2150-704X",
language = "en",
targetfile = "1_alcantara_estimating.pdf",
urlaccessdate = "27 abr. 2024"
}