Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing

Wetlands can only be well managed if their spatial location and extent are accurately documented, which presents a problem as wetland type and morphology are highly variable. Current efforts to delineate wetland extent are varied, resulting in a host of inconsistent and incomparable inventories. Thi...

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Autores principales: Nhamo, Luxon, Magidi, J., Dickens, Chris
Formato: Journal Article
Lenguaje:Inglés
Publicado: African Journals Online 2017
Materias:
Acceso en línea:https://hdl.handle.net/10568/91314
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author Nhamo, Luxon
Magidi, J.
Dickens, Chris
author_browse Dickens, Chris
Magidi, J.
Nhamo, Luxon
author_facet Nhamo, Luxon
Magidi, J.
Dickens, Chris
author_sort Nhamo, Luxon
collection Repository of Agricultural Research Outputs (CGSpace)
description Wetlands can only be well managed if their spatial location and extent are accurately documented, which presents a problem as wetland type and morphology are highly variable. Current efforts to delineate wetland extent are varied, resulting in a host of inconsistent and incomparable inventories. This study, done in the Witbank Dam Catchment in Mpumalanga Province of South Africa, explores a remote-sensing technique to delineate wetland extent and assesses the seasonal variations of the inundated area. The objective was to monitor the spatio-temporal changes of wetlands over time through remote sensing and GIS for effective wetland management. Multispectral satellite images, together with a digital elevation model (DEM), were used to delineate wetland extent. The seasonal variations of the inundated area were assessed through an analysis of monthly water indices derived from the normalised difference water index (NDWI). Landsat images and DEM were used to delineate wetland extent and MODIS images were used to assess seasonal variation of the inundated area. A time-series trend analysis on the delineated wetlands shows a declining tendency from 2000 to 2015, which could worsen in the coming few years if no remedial action is taken. Wetland area declined by 19% in the study area over the period under review. An analysis of NDWI indices on the wetland area showed that wetland inundated area is highly variable, exhibiting an increasing variability over time. An overlay of wetland area on cultivated land showed that 21% of the wetland area is subjected to cultivation which is a major contributing factor to wetland degradation.
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spelling CGSpace913142025-03-11T09:50:20Z Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing Nhamo, Luxon Magidi, J. Dickens, Chris wetlands flooding remote sensing gis spatial planning multispectral imagery satellite imagery sustainable development ecosystems dam construction catchment areas Wetlands can only be well managed if their spatial location and extent are accurately documented, which presents a problem as wetland type and morphology are highly variable. Current efforts to delineate wetland extent are varied, resulting in a host of inconsistent and incomparable inventories. This study, done in the Witbank Dam Catchment in Mpumalanga Province of South Africa, explores a remote-sensing technique to delineate wetland extent and assesses the seasonal variations of the inundated area. The objective was to monitor the spatio-temporal changes of wetlands over time through remote sensing and GIS for effective wetland management. Multispectral satellite images, together with a digital elevation model (DEM), were used to delineate wetland extent. The seasonal variations of the inundated area were assessed through an analysis of monthly water indices derived from the normalised difference water index (NDWI). Landsat images and DEM were used to delineate wetland extent and MODIS images were used to assess seasonal variation of the inundated area. A time-series trend analysis on the delineated wetlands shows a declining tendency from 2000 to 2015, which could worsen in the coming few years if no remedial action is taken. Wetland area declined by 19% in the study area over the period under review. An analysis of NDWI indices on the wetland area showed that wetland inundated area is highly variable, exhibiting an increasing variability over time. An overlay of wetland area on cultivated land showed that 21% of the wetland area is subjected to cultivation which is a major contributing factor to wetland degradation. 2017 2018-03-07T10:16:35Z 2018-03-07T10:16:35Z Journal Article https://hdl.handle.net/10568/91314 en Open Access African Journals Online Nhamo, Luxon; Magidi, J.; Dickens, Chris. 2017. Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing. Water SA. 43(4):543-552.. https://www.ajol.info/index.php/wsa/article/download/162560/152061. 10.4314/wsa.v43i4.02
spellingShingle wetlands
flooding
remote sensing
gis
spatial planning
multispectral imagery
satellite imagery
sustainable development
ecosystems
dam construction
catchment areas
Nhamo, Luxon
Magidi, J.
Dickens, Chris
Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing
title Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing
title_full Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing
title_fullStr Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing
title_full_unstemmed Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing
title_short Determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing
title_sort determining wetland spatial extent and seasonal variations of the inundated area using multispectral remote sensing
topic wetlands
flooding
remote sensing
gis
spatial planning
multispectral imagery
satellite imagery
sustainable development
ecosystems
dam construction
catchment areas
url https://hdl.handle.net/10568/91314
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AT dickenschris determiningwetlandspatialextentandseasonalvariationsoftheinundatedareausingmultispectralremotesensing