@InProceedings{AlcântaraBernRodrWata:2017:ReTuMo,
author = "Alc{\^a}ntara, Enner Herenio and Bernardo, Nariane Marselhe
Ribeiro and Rodrigues, Thanan Walesza Pequeno and Watanabe,
Fernanda Sayuri Yoshino",
title = "Regional-scale tuned model to estimate the dissolved organic
carbon in Barra Bonita reservoir from OLI/Landsat-8 images",
booktitle = "Anais...",
year = "2017",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "1462--1469",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "Through exchange of heat and water with the atmosphere inland
waters affect climate at the regional scale and play an important
role in the global carbon cycle. Therefore there is a need to
develop methods and models for mapping inland water carbon content
to understand the role of lakes in the global carbon cycle. The
colored dissolved organic matter (CDOM) has a strong correlation
with dissolved organic carbon (DOC) and can be studied using
remote sensed images. In this work, we developed an empirical
model to estimate the DOC concentration by using the absorption
coefficient of CDOM (aCDOM). The aCDOM was estimated through band
ratio index and validated with in situ data. The empirical
adjusted model to estimate the DOC was applied to a series of
OLI/Landsat-8 images. The results showed a good relationship
between the aCDOM at 412 nm (aCDOM412) and the ratio between OLI
band 1 and OLI band 3, but the validation results showed a
normalized root mean square error (NRMSE) of about 37.89%. The
aCDOM412 obtained in laboratory was used to establish a
relationship between aCDOM412 and DOC. The DOC spatial
distribution was then obtained and the concentration varied from
22 to 52 mg.l-1 during the year of 2014.",
conference-location = "Santos",
conference-year = "28-31 maio 2017",
isbn = "978-85-17-00088-1",
label = "59239",
language = "en",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3PS4GNU",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PS4GNU",
targetfile = "59239.pdf",
type = "Sensoriamento remoto de {\'a}guas interiores",
urlaccessdate = "27 abr. 2024"
}