Cyanobacteria detection in Guarapiranga Reservoir (São Paulo State, Brazil) using Landsat TM and ETM+ images

Detalhes bibliográficos
Autor(a) principal: Ogashawara,Igor
Data de Publicação: 2014
Outros Autores: Alcântara,Enner Herenio de, Stech,José Luiz, Tundisi,José Galizia
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Ambiente & Água
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2014000200005
Resumo: 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 São 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.
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spelling Cyanobacteria detection in Guarapiranga Reservoir (São Paulo State, Brazil) using Landsat TM and ETM+ imagesphytoplanktonwater qualityenvironmental healthsatellite imageryAlgae 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 São 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.Instituto de Pesquisas Ambientais em Bacias Hidrográficas2014-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2014000200005Revista Ambiente & Água v.9 n.2 2014reponame:Revista Ambiente & Águainstname:Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)instacron:IPABHI10.4136/ambi-agua.1327info:eu-repo/semantics/openAccessOgashawara,IgorAlcântara,Enner Herenio deStech,José LuizTundisi,José Galiziaeng2014-06-30T00:00:00Zoai:scielo:S1980-993X2014000200005Revistahttp://www.ambi-agua.net/PUBhttps://old.scielo.br/oai/scielo-oai.php||ambi.agua@gmail.com1980-993X1980-993Xopendoar:2014-06-30T00:00Revista Ambiente & Água - Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)false
dc.title.none.fl_str_mv Cyanobacteria detection in Guarapiranga Reservoir (São Paulo State, Brazil) using Landsat TM and ETM+ images
title Cyanobacteria detection in Guarapiranga Reservoir (São Paulo State, Brazil) using Landsat TM and ETM+ images
spellingShingle Cyanobacteria detection in Guarapiranga Reservoir (São Paulo State, Brazil) using Landsat TM and ETM+ images
Ogashawara,Igor
phytoplankton
water quality
environmental health
satellite imagery
title_short Cyanobacteria detection in Guarapiranga Reservoir (São Paulo State, Brazil) using Landsat TM and ETM+ images
title_full Cyanobacteria detection in Guarapiranga Reservoir (São Paulo State, Brazil) using Landsat TM and ETM+ images
title_fullStr Cyanobacteria detection in Guarapiranga Reservoir (São Paulo State, Brazil) using Landsat TM and ETM+ images
title_full_unstemmed Cyanobacteria detection in Guarapiranga Reservoir (São Paulo State, Brazil) using Landsat TM and ETM+ images
title_sort Cyanobacteria detection in Guarapiranga Reservoir (São Paulo State, Brazil) using Landsat TM and ETM+ images
author Ogashawara,Igor
author_facet Ogashawara,Igor
Alcântara,Enner Herenio de
Stech,José Luiz
Tundisi,José Galizia
author_role author
author2 Alcântara,Enner Herenio de
Stech,José Luiz
Tundisi,José Galizia
author2_role author
author
author
dc.contributor.author.fl_str_mv Ogashawara,Igor
Alcântara,Enner Herenio de
Stech,José Luiz
Tundisi,José Galizia
dc.subject.por.fl_str_mv phytoplankton
water quality
environmental health
satellite imagery
topic phytoplankton
water quality
environmental health
satellite imagery
description 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 São 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.
publishDate 2014
dc.date.none.fl_str_mv 2014-06-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2014000200005
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.4136/ambi-agua.1327
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Instituto de Pesquisas Ambientais em Bacias Hidrográficas
publisher.none.fl_str_mv Instituto de Pesquisas Ambientais em Bacias Hidrográficas
dc.source.none.fl_str_mv Revista Ambiente & Água v.9 n.2 2014
reponame:Revista Ambiente & Água
instname:Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)
instacron:IPABHI
instname_str Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)
instacron_str IPABHI
institution IPABHI
reponame_str Revista Ambiente & Água
collection Revista Ambiente & Água
repository.name.fl_str_mv Revista Ambiente & Água - Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)
repository.mail.fl_str_mv ||ambi.agua@gmail.com
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