Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.3390/rs14143282 http://hdl.handle.net/11449/241308 |
Resumo: | The overgrowth of macrophytes is a recurrent problem within reservoirs of urbanized and industrialized areas, a condition triggered by the damming of rivers and other human activities. Although the occurrence of aquatic plants in waterbodies has been widely monitored using remote sensing, the influence of climate variables on macrophyte spatiotemporal dynamics is rarely considered in studies developed for medium scales to long periods of time. We hypothesize that the spatial dispersion of macrophytes has its natural rhythms influenced by climate fluctuations, and, as such, its effects on the heterogeneous spatial distribution of this vegetation should be considered in the monitoring of water bodies. A eutrophic reservoir is selected for study, which uses the Normalized Difference Vegetation Index (NDVI) as a proxy for macrophytes. Landsat’s NDVI long-term time series are constructed and matched with the Climate Variable (CV) from the National Oceanic and Atmospheric Administration (NOAA) to assess the spatiotemporal dynamics of aquatic plants and their associated climate triggers. The NDVI and CV time series and their seasonal and trend components are correlated for the entire reservoir, compartments, and segmented areas of the water body. Granger-causality of these climate variables show that they contribute to describe and predict the spatial dispersion of macrophytes. |
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Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Seriescausalityclimate variablesLandsat time seriesmacrophytesmonitoringremote sensingreservoirsThe overgrowth of macrophytes is a recurrent problem within reservoirs of urbanized and industrialized areas, a condition triggered by the damming of rivers and other human activities. Although the occurrence of aquatic plants in waterbodies has been widely monitored using remote sensing, the influence of climate variables on macrophyte spatiotemporal dynamics is rarely considered in studies developed for medium scales to long periods of time. We hypothesize that the spatial dispersion of macrophytes has its natural rhythms influenced by climate fluctuations, and, as such, its effects on the heterogeneous spatial distribution of this vegetation should be considered in the monitoring of water bodies. A eutrophic reservoir is selected for study, which uses the Normalized Difference Vegetation Index (NDVI) as a proxy for macrophytes. Landsat’s NDVI long-term time series are constructed and matched with the Climate Variable (CV) from the National Oceanic and Atmospheric Administration (NOAA) to assess the spatiotemporal dynamics of aquatic plants and their associated climate triggers. The NDVI and CV time series and their seasonal and trend components are correlated for the entire reservoir, compartments, and segmented areas of the water body. Granger-causality of these climate variables show that they contribute to describe and predict the spatial dispersion of macrophytes.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)School of Technology and Sciences São Paulo State University (UNESP), Presidente Prudente, SPSchool of Earth and Planetary Sciences (EPS) Curtin UniversitySchool of Technology and Sciences São Paulo State University (UNESP), Presidente Prudente, SPCAPES: 001Universidade Estadual Paulista (UNESP)Curtin UniversityColadello, Leandro Fernandes [UNESP]Galo, Maria de Lourdes Bueno Trindade [UNESP]Shimabukuro, Milton Hirokazu [UNESP]Ivánová, IvanaAwange, Joseph2023-03-01T20:56:09Z2023-03-01T20:56:09Z2022-07-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.3390/rs14143282Remote Sensing, v. 14, n. 14, 2022.2072-4292http://hdl.handle.net/11449/24130810.3390/rs141432822-s2.0-85133793515Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRemote Sensinginfo:eu-repo/semantics/openAccess2024-06-18T18:18:16Zoai:repositorio.unesp.br:11449/241308Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:15:40.793930Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series |
title |
Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series |
spellingShingle |
Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series Coladello, Leandro Fernandes [UNESP] causality climate variables Landsat time series macrophytes monitoring remote sensing reservoirs |
title_short |
Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series |
title_full |
Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series |
title_fullStr |
Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series |
title_full_unstemmed |
Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series |
title_sort |
Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series |
author |
Coladello, Leandro Fernandes [UNESP] |
author_facet |
Coladello, Leandro Fernandes [UNESP] Galo, Maria de Lourdes Bueno Trindade [UNESP] Shimabukuro, Milton Hirokazu [UNESP] Ivánová, Ivana Awange, Joseph |
author_role |
author |
author2 |
Galo, Maria de Lourdes Bueno Trindade [UNESP] Shimabukuro, Milton Hirokazu [UNESP] Ivánová, Ivana Awange, Joseph |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Curtin University |
dc.contributor.author.fl_str_mv |
Coladello, Leandro Fernandes [UNESP] Galo, Maria de Lourdes Bueno Trindade [UNESP] Shimabukuro, Milton Hirokazu [UNESP] Ivánová, Ivana Awange, Joseph |
dc.subject.por.fl_str_mv |
causality climate variables Landsat time series macrophytes monitoring remote sensing reservoirs |
topic |
causality climate variables Landsat time series macrophytes monitoring remote sensing reservoirs |
description |
The overgrowth of macrophytes is a recurrent problem within reservoirs of urbanized and industrialized areas, a condition triggered by the damming of rivers and other human activities. Although the occurrence of aquatic plants in waterbodies has been widely monitored using remote sensing, the influence of climate variables on macrophyte spatiotemporal dynamics is rarely considered in studies developed for medium scales to long periods of time. We hypothesize that the spatial dispersion of macrophytes has its natural rhythms influenced by climate fluctuations, and, as such, its effects on the heterogeneous spatial distribution of this vegetation should be considered in the monitoring of water bodies. A eutrophic reservoir is selected for study, which uses the Normalized Difference Vegetation Index (NDVI) as a proxy for macrophytes. Landsat’s NDVI long-term time series are constructed and matched with the Climate Variable (CV) from the National Oceanic and Atmospheric Administration (NOAA) to assess the spatiotemporal dynamics of aquatic plants and their associated climate triggers. The NDVI and CV time series and their seasonal and trend components are correlated for the entire reservoir, compartments, and segmented areas of the water body. Granger-causality of these climate variables show that they contribute to describe and predict the spatial dispersion of macrophytes. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-07-01 2023-03-01T20:56:09Z 2023-03-01T20:56:09Z |
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/rs14143282 Remote Sensing, v. 14, n. 14, 2022. 2072-4292 http://hdl.handle.net/11449/241308 10.3390/rs14143282 2-s2.0-85133793515 |
url |
http://dx.doi.org/10.3390/rs14143282 http://hdl.handle.net/11449/241308 |
identifier_str_mv |
Remote Sensing, v. 14, n. 14, 2022. 2072-4292 10.3390/rs14143282 2-s2.0-85133793515 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Remote Sensing |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus 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_ |
1808129410404974592 |