Publicação: Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series
dc.contributor.author | Coladello, Leandro Fernandes [UNESP] | |
dc.contributor.author | Galo, Maria de Lourdes Bueno Trindade [UNESP] | |
dc.contributor.author | Shimabukuro, Milton Hirokazu [UNESP] | |
dc.contributor.author | Ivánová, Ivana | |
dc.contributor.author | Awange, Joseph | |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
dc.contributor.institution | Curtin University | |
dc.date.accessioned | 2023-03-01T20:56:09Z | |
dc.date.available | 2023-03-01T20:56:09Z | |
dc.date.issued | 2022-07-01 | |
dc.description.abstract | 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. | en |
dc.description.affiliation | School of Technology and Sciences São Paulo State University (UNESP), Presidente Prudente, SP | |
dc.description.affiliation | School of Earth and Planetary Sciences (EPS) Curtin University | |
dc.description.affiliationUnesp | School of Technology and Sciences São Paulo State University (UNESP), Presidente Prudente, SP | |
dc.description.sponsorship | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) | |
dc.description.sponsorshipId | CAPES: 001 | |
dc.identifier | http://dx.doi.org/10.3390/rs14143282 | |
dc.identifier.citation | Remote Sensing, v. 14, n. 14, 2022. | |
dc.identifier.doi | 10.3390/rs14143282 | |
dc.identifier.issn | 2072-4292 | |
dc.identifier.scopus | 2-s2.0-85133793515 | |
dc.identifier.uri | http://hdl.handle.net/11449/241308 | |
dc.language.iso | eng | |
dc.relation.ispartof | Remote Sensing | |
dc.source | Scopus | |
dc.subject | causality | |
dc.subject | climate variables | |
dc.subject | Landsat time series | |
dc.subject | macrophytes | |
dc.subject | monitoring | |
dc.subject | remote sensing | |
dc.subject | reservoirs | |
dc.title | Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series | en |
dc.type | Artigo | |
dspace.entity.type | Publication | |
unesp.department | Estatística - FCT | pt |