Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series

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 influe...

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Main Authors: Coladello, L.F., Galo, M.D.L.B.T., Shimabukuro, M.H., Ivanova, Ivana, Awange, Joseph
Format: Journal Article
Language:English
Published: MDPI 2022
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/90687
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author Coladello, L.F.
Galo, M.D.L.B.T.
Shimabukuro, M.H.
Ivanova, Ivana
Awange, Joseph
author_facet Coladello, L.F.
Galo, M.D.L.B.T.
Shimabukuro, M.H.
Ivanova, Ivana
Awange, Joseph
author_sort Coladello, L.F.
building Curtin Institutional Repository
collection Online Access
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.
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spelling curtin-20.500.11937-906872023-04-03T00:41:37Z Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series Coladello, L.F. Galo, M.D.L.B.T. Shimabukuro, M.H. Ivanova, Ivana Awange, Joseph Science & Technology Life Sciences & Biomedicine Physical Sciences Technology Environmental Sciences Geosciences, Multidisciplinary Remote Sensing Imaging Science & Photographic Technology Environmental Sciences & Ecology Geology Landsat time series climate variables monitoring causality reservoirs macrophytes remote sensing AQUATIC VEGETATION TREND ANALYSIS LAKE VICTORIA TAIHU LAKE COVER DEGRADATION VARIABILITY REANALYSIS FLOODPLAIN ABUNDANCE 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. 2022 Journal Article http://hdl.handle.net/20.500.11937/90687 10.3390/rs14143282 English http://creativecommons.org/licenses/by/4.0/ MDPI fulltext
spellingShingle Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Technology
Environmental Sciences
Geosciences, Multidisciplinary
Remote Sensing
Imaging Science & Photographic Technology
Environmental Sciences & Ecology
Geology
Landsat time series
climate variables
monitoring
causality
reservoirs
macrophytes
remote sensing
AQUATIC VEGETATION
TREND ANALYSIS
LAKE VICTORIA
TAIHU LAKE
COVER
DEGRADATION
VARIABILITY
REANALYSIS
FLOODPLAIN
ABUNDANCE
Coladello, L.F.
Galo, M.D.L.B.T.
Shimabukuro, M.H.
Ivanova, Ivana
Awange, Joseph
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
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_short 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
topic Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Technology
Environmental Sciences
Geosciences, Multidisciplinary
Remote Sensing
Imaging Science & Photographic Technology
Environmental Sciences & Ecology
Geology
Landsat time series
climate variables
monitoring
causality
reservoirs
macrophytes
remote sensing
AQUATIC VEGETATION
TREND ANALYSIS
LAKE VICTORIA
TAIHU LAKE
COVER
DEGRADATION
VARIABILITY
REANALYSIS
FLOODPLAIN
ABUNDANCE
url http://hdl.handle.net/20.500.11937/90687