@Article{WatanabeAlRoImBaRo:2015:EsChCo,
author = "Watanabe, Fernanda Sayuri Yoshino and Alc{\^a}ntara, Enner and
Rodrigues, Thanan Walesza Pequeno and Imai, Nilton Nobuhiro and
Barbosa, Claudio Clemente Faria and Rotta, Luiz Henrique da
Silva",
affiliation = "{Universidade Estadual Paulista (UNESP)} and {Universidade
Estadual Paulista (UNESP)} and {Universidade Estadual Paulista
(UNESP)} and {Universidade Estadual Paulista (UNESP)} and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and
{Universidade Estadual Paulista (UNESP)}",
title = "Estimation of chlorophyll-a concentration and the trophic state of
the Barra Bonita hydroelectric reservoir using OLI/Landsat-8
images",
journal = "International Journal of Environmental Research and Public
Health",
year = "2015",
volume = "2015",
number = "12",
pages = "9",
month = "Aug.",
keywords = "Bio-optical models, Case-2 waters, Chlorophyll-a, Multispectral
image, Remote sensing.",
abstract = "Reservoirs are artificial environments built by humans, and the
impacts of these environments are not completely known. Retention
time and high nutrient availability in the water increases the
eutrophic level. Eutrophication is directly correlated to primary
productivity by phytoplankton. These organisms have an important
role in the environment. However, high concentrations of
determined species can lead to public health problems. Species of
cyanobacteria produce toxins that in determined concentrations can
cause serious diseases in the liver and nervous system, which
could lead to death. Phytoplankton has photoactive pigments that
can be used to identify these toxins. Thus, remote sensing data is
a viable alternative for mapping these pigments, and consequently,
the trophic. Chlorophyll-a (Chl-a) is present in all phytoplankton
species. Therefore, the aim of this work was to evaluate the
performance of images of the sensor Operational Land Imager (OLI)
onboard the Landsat-8 satellite in determining Chl-a
concentrations and estimating the trophic level in a tropical
reservoir. Empirical models were fitted using data from two field
surveys conducted in May and October 2014 (Austral Autumn and
Austral Spring, respectively). Models were applied in a temporal
series of OLI images from May 2013 to October 2014. The estimated
Chl-a concentration was used to classify the trophic level from a
trophic state index that adopted the concentration of this
pigment-like parameter. The models of Chl-a concentration showed
reasonable results, but their performance was likely impaired by
the atmospheric correction. Consequently, the trophic level
classification also did not obtain better results.",
doi = "10.3390/ijerph120910391",
url = "http://dx.doi.org/10.3390/ijerph120910391",
issn = "1661-7827 and 1660-4601",
language = "en",
targetfile = "watanabe_estimation.pdf",
urlaccessdate = "27 abr. 2024"
}