@Article{OgashawaraAlcâStecTund:2014:CyDeGu,
author = "Ogashawara, Igor and Alc{\^a}ntara, E. H. de and Stech, Jos{\'e}
Luiz and Tundisi, J. G.",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and
Universidade Estadual Paulista 'J{\'u}lio de Mesquita Filho'
(UNESP), Departamento de Cartografia, Presidente Prudente, SP,
Brazil and {Instituto Nacional de Pesquisas Espaciais (INPE)} and
Instituto Internacional de Ecologia, S{\~a}o Carlos, SP, Brazil",
title = "Cyanobacteria detection in Guarapiranga reservoir (S{\~a}o Paulo
state, Brazil) using landsat TM and ETM+ images /
Detec{\c{c}}{\~a}o de cianobact{\'e}rias no reservat{\'o}rio
de Guarapiranga (estado de S{\~a}o Paulo, Brasil) utilizando
imagens landsat TM e ETM+",
journal = "Revista Ambiente \& {\'A}gua",
year = "2014",
volume = "9",
number = "2",
pages = "224--238",
abstract = "Algae bloom is one of the major consequences of the eutrophication
of aquatic systems, including algae capable of producing toxic
substances. Among these are several species of cyanobacteria, also
known as blue-green algae, that have the capacity to adapt
themselves to changes in the water column. Thus, the horizontal
distribution of cyanobacteria harmful algae blooms (CHABs) is
essential, not only to the environment, but also for public
health. The use of remote sensing techniques for mapping CHABs has
been explored by means of bio-optical modeling of phycocyanin
(PC), a unique inland waters cyanobacteria pigment. However, due
to the small number of sensors with a spectral band of the PC
absorption feature, it is difficult to develop semi-analytical
models. This study evaluated the use of an empirical model to
identify CHABs using TM and ETM+ sensors aboard Landsat 5 and 7
satellites. Five images were acquired for applying the model.
Besides the images, data was also collected in the Guarapiranga
Reservoir, in S{\~a}o Paulo Metropolitan Region, regarding the
cyanobacteria cell count (cells/mL), which was used as an
indicator of CHABs biomass. When model values were analyzed
excluding calibration factors for temperate lakes, they showed a
medium correlation (R2 = 0.81, p = 0.036), while when the factors
were included the model showed a high correlation (R2 = 0.96,
p=0.003) to the cyanobacteria cell count. The empirical model
analyzed proved useful as an important tool for policy makers,
since it provided information regarding the horizontal
distribution of CHABs which could not be acquired from traditional
monitoring techniques.",
doi = "10.4136/ambi-agua.1327",
url = "http://dx.doi.org/10.4136/ambi-agua.1327",
issn = "1980-993X",
label = "scopus 2014-11 OgashawaraAlc{\^a}StecTund:2014:CyDeGu",
language = "en",
targetfile = "Cyanobacteria detection in Guarapiranga Reservoir (Sao Paulo
State, Brazil) using Landsat TM and ETM images.pdf",
urlaccessdate = "03 jun. 2024"
}