Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.3390/rs6021634 http://hdl.handle.net/11449/113368 |
Resumo: | Monitoring chlorophyll-a (chl-a) concentrations is important for the management of water quality, because it is a good indicator of the eutrophication level in an aquatic system. Thus, our main purpose was to develop an alternative technique to monitor chl-a in time and space through remote sensing techniques. However, one of the limitations of remote sensing is the resolution. To achieve a high temporal resolution and medium space resolution, we used the Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m reflectance product, MOD09GA, and limnological parameters from the Itumbiara Reservoir. With these data, an empirical (O14a) and semi-empirical (O14b) algorithm were developed. Algorithms were cross-calibrated and validated using three datasets: one for each campaign and a third consisting of a combination of the two individual campaigns. Algorithm O14a produced the best validation with a root mean square error (RMSE) of 30.4%, whereas O14b produced an RMSE of 32.41% using the mixed dataset calibration. O14a was applied to MOD09GA to build a time series for the reservoir for the year of 2009. The time-series analysis revealed that there were occurrences of algal blooms in the summer that were likely related to the additional input of nutrients caused by rainfall runoff. During the winter, however, the few observed algal blooms events were related to periods of atmospheric meteorological variations that represented an enhanced external influence on the processes of mixing and stratification of the water column. Finally, the use of remote sensing techniques can be an important tool for policy makers, environmental managers and the scientific community with which to monitor water quality. |
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Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazilchlorophyll-abio-optic modelingtime-seriesMODISMonitoring chlorophyll-a (chl-a) concentrations is important for the management of water quality, because it is a good indicator of the eutrophication level in an aquatic system. Thus, our main purpose was to develop an alternative technique to monitor chl-a in time and space through remote sensing techniques. However, one of the limitations of remote sensing is the resolution. To achieve a high temporal resolution and medium space resolution, we used the Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m reflectance product, MOD09GA, and limnological parameters from the Itumbiara Reservoir. With these data, an empirical (O14a) and semi-empirical (O14b) algorithm were developed. Algorithms were cross-calibrated and validated using three datasets: one for each campaign and a third consisting of a combination of the two individual campaigns. Algorithm O14a produced the best validation with a root mean square error (RMSE) of 30.4%, whereas O14b produced an RMSE of 32.41% using the mixed dataset calibration. O14a was applied to MOD09GA to build a time series for the reservoir for the year of 2009. The time-series analysis revealed that there were occurrences of algal blooms in the summer that were likely related to the additional input of nutrients caused by rainfall runoff. During the winter, however, the few observed algal blooms events were related to periods of atmospheric meteorological variations that represented an enhanced external influence on the processes of mixing and stratification of the water column. Finally, the use of remote sensing techniques can be an important tool for policy makers, environmental managers and the scientific community with which to monitor water quality.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Natl Inst Space Res INPE, Remote Sensing Div, BR-1758 Sao Jose Dos Campos, SP, BrazilState Univ Sao Paulo, Cartog Engn Dept, BR-19060900 Prudente, SP, BrazilNatl Inst Space Res INPE, Reg Ctr Amazon, BR-2651 Belem, PA, BrazilGeopixel Solucoes Geotecnol, BR-12245902 Sao Jose Dos Campos, SP, BrazilETEP Fac, BR-12242800 Sao Jose Dos Campos, SP, BrazilState Univ Sao Paulo, Cartog Engn Dept, BR-19060900 Prudente, SP, BrazilFAPESP: 07/08103-2Mdpi AgInstituto Nacional de Pesquisas Espaciais (INPE)Universidade Estadual Paulista (Unesp)Geopixel Solucoes GeotecnolETEP FacOgashawara, IgorAlcantara, Enner H. [UNESP]Curtarelli, Marcelo P.Adami, MarcosNascimento, Renata F. F.Souza, Arley F.Stech, Jose L.Kampel, Milton2014-12-03T13:11:39Z2014-12-03T13:11:39Z2014-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1634-1653application/pdfhttp://dx.doi.org/10.3390/rs6021634Remote Sensing. Basel: Mdpi Ag, v. 6, n. 2, p. 1634-1653, 2014.2072-4292http://hdl.handle.net/11449/11336810.3390/rs6021634WOS:000336092100034WOS000336092100034.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRemote Sensing3.4061,386info:eu-repo/semantics/openAccess2024-06-18T15:01:09Zoai:repositorio.unesp.br:11449/113368Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:22:40.587035Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil |
title |
Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil |
spellingShingle |
Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil Ogashawara, Igor chlorophyll-a bio-optic modeling time-series MODIS |
title_short |
Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil |
title_full |
Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil |
title_fullStr |
Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil |
title_full_unstemmed |
Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil |
title_sort |
Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo-to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil |
author |
Ogashawara, Igor |
author_facet |
Ogashawara, Igor Alcantara, Enner H. [UNESP] Curtarelli, Marcelo P. Adami, Marcos Nascimento, Renata F. F. Souza, Arley F. Stech, Jose L. Kampel, Milton |
author_role |
author |
author2 |
Alcantara, Enner H. [UNESP] Curtarelli, Marcelo P. Adami, Marcos Nascimento, Renata F. F. Souza, Arley F. Stech, Jose L. Kampel, Milton |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Instituto Nacional de Pesquisas Espaciais (INPE) Universidade Estadual Paulista (Unesp) Geopixel Solucoes Geotecnol ETEP Fac |
dc.contributor.author.fl_str_mv |
Ogashawara, Igor Alcantara, Enner H. [UNESP] Curtarelli, Marcelo P. Adami, Marcos Nascimento, Renata F. F. Souza, Arley F. Stech, Jose L. Kampel, Milton |
dc.subject.por.fl_str_mv |
chlorophyll-a bio-optic modeling time-series MODIS |
topic |
chlorophyll-a bio-optic modeling time-series MODIS |
description |
Monitoring chlorophyll-a (chl-a) concentrations is important for the management of water quality, because it is a good indicator of the eutrophication level in an aquatic system. Thus, our main purpose was to develop an alternative technique to monitor chl-a in time and space through remote sensing techniques. However, one of the limitations of remote sensing is the resolution. To achieve a high temporal resolution and medium space resolution, we used the Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m reflectance product, MOD09GA, and limnological parameters from the Itumbiara Reservoir. With these data, an empirical (O14a) and semi-empirical (O14b) algorithm were developed. Algorithms were cross-calibrated and validated using three datasets: one for each campaign and a third consisting of a combination of the two individual campaigns. Algorithm O14a produced the best validation with a root mean square error (RMSE) of 30.4%, whereas O14b produced an RMSE of 32.41% using the mixed dataset calibration. O14a was applied to MOD09GA to build a time series for the reservoir for the year of 2009. The time-series analysis revealed that there were occurrences of algal blooms in the summer that were likely related to the additional input of nutrients caused by rainfall runoff. During the winter, however, the few observed algal blooms events were related to periods of atmospheric meteorological variations that represented an enhanced external influence on the processes of mixing and stratification of the water column. Finally, the use of remote sensing techniques can be an important tool for policy makers, environmental managers and the scientific community with which to monitor water quality. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-12-03T13:11:39Z 2014-12-03T13:11:39Z 2014-02-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.3390/rs6021634 Remote Sensing. Basel: Mdpi Ag, v. 6, n. 2, p. 1634-1653, 2014. 2072-4292 http://hdl.handle.net/11449/113368 10.3390/rs6021634 WOS:000336092100034 WOS000336092100034.pdf |
url |
http://dx.doi.org/10.3390/rs6021634 http://hdl.handle.net/11449/113368 |
identifier_str_mv |
Remote Sensing. Basel: Mdpi Ag, v. 6, n. 2, p. 1634-1653, 2014. 2072-4292 10.3390/rs6021634 WOS:000336092100034 WOS000336092100034.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Remote Sensing 3.406 1,386 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
1634-1653 application/pdf |
dc.publisher.none.fl_str_mv |
Mdpi Ag |
publisher.none.fl_str_mv |
Mdpi Ag |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128504071454720 |