@InCollection{OgashawaraCurtAraúStec:2016:BiMoTr,
author = "Ogashawara, Igor and Curtarelli, Marcelo Pedroso and Ara{\'u}jo,
Carlos Alberto Sampaio de and Stech, Jos{\'e} Luiz",
title = "Bio-optical modeling in a tropical hypersaline lagoon
environment",
booktitle = "Environmental applications of remote sensing",
publisher = "InTech",
year = "2016",
editor = "Marghany, Maged",
pages = "235--258",
keywords = "Water quality, chlorophyll-a, turbidity, bio-optical modeling.",
abstract = "In this chapter, we attempted to present an overview of the use of
remote sensing to mon\‐ itor water quality parameters,
mainly chlorophyll-a (chl-a) and turbidity. We summarized the main
concepts of bio-optical modeling and presented a case study of the
application of the Hyperspectral Imager for the Coastal Ocean
(HICO) for the monitoring of water quality in a tropical
hypersaline aquatic environment. Using HICO, we evaluated a set of
different semi-empirical bio-optical algorithms for chl-a and
turbidity estimation devel\‐ oped for inland and oceanic
waters in the Araruama Lagoon, RJ, Brazil, which is an ex\‐
treme environment due to its high salinity values. We also
developed an empirical algorithm for both water quality parameters
and compared the performances. Results showed that for chl-a
estimation all models have a low performance with a normalized
root mean square error (NRMSE) varying from 24.13 to 30.46. For
turbidity, the bio-opti\‐ cal algorithms showed a better
performance with the NRMSE between 15.49 and 28.04. Overall, these
results highlight the importance of including extreme
environments, such as the Araruama Lagoon, on the validation of
bio-optical algorithms as well as the need for new orbital
hyperspectral sensors which will improve the development of the
field.",
affiliation = "{Indiana University} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
doi = "10.5772/61869",
url = "http://dx.doi.org/10.5772/61869",
isbn = "978-953-51-2444-3 and 978-953-51-2443-6",
language = "en",
targetfile = "ogashawara_bio.pdf",
urlaccessdate = "28 abr. 2024"
}