Assessment and mapping of wetland vegetation as an indicator of ecological productivity in Maungani Wetland in Limpopo, South Africa

Thesis (M.Sc. (Geography)) -- University of Limpopo, 2020 === Wetland vegetation provides a variety of goods and services such as carbon sequestration, flood control, climate regulation, filtering contamination, improve and maintain water quality, ecological functioning. However, changes in land cov...

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Main Author: Mashala, Makgabo Johanna
Other Authors: Dube, T.
Format: Others
Language:en
Published: 2021
Subjects:
Online Access:http://hdl.handle.net/10386/3478
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spelling ndltd-netd.ac.za-oai-union.ndltd.org-ul-oai-ulspace.ul.ac.za-10386-34782021-10-01T05:09:21Z Assessment and mapping of wetland vegetation as an indicator of ecological productivity in Maungani Wetland in Limpopo, South Africa Mashala, Makgabo Johanna Dube, T. Dhau, I. Aboveground biomass mapping remote sensing Sentinel 2 Species diversity Wetland ecology Freshwater productivity Wetland agriculture Thesis (M.Sc. (Geography)) -- University of Limpopo, 2020 Wetland vegetation provides a variety of goods and services such as carbon sequestration, flood control, climate regulation, filtering contamination, improve and maintain water quality, ecological functioning. However, changes in land cover and uses, overgrazing and environmental changes have resulted in the transformation of the wetland ecosystem. So far, a lot of focus has been biased towards large wetlands neglecting wetlands at a local scale. Smaller wetlands continue to receive massive degradation by the surrounding communities.Therefore, this study seeks to assess and map wetland vegetation as an indicator of ecological productivity on a small scale. The Sentinel-2 MSI image was used to map wetland plant species diversity and above-ground biomass (AGB). Four key diversity indices; the Shannon Wiener (H), Simpson (D), Pielou (J), and Species richness (S) were used to measure species diversity. A multilinear regression technique was applied to establish the relationship between remotely sensed data and diversity indices and AGB. The results indicated that Simpson (D) has a high relationship with combined vegetation indices and spectral band, yielding the highest accuracy when compared to other diversity indices. For example, an R² of 0.75, and the RMSE of 0.08 and AIC of -191.6 were observed. Further, vegetation AGB was estimated with high accuracy of an R² of 0.65, the RMSE 29.02, and AIC of 280.21. These results indicate that Maungani wetland has high species abundance largely dominated by one species (Cyperus latifidius) and highly productive. The findings of this work underscore the relevance of remotely sensed to estimate and monitor wetland plant species diversity with high accuracy. 2021-09-29T06:58:40Z 2021-09-29T06:58:40Z 2020 Thesis http://hdl.handle.net/10386/3478 en PDF xi, 66 leaves
collection NDLTD
language en
format Others
sources NDLTD
topic Aboveground biomass
mapping
remote sensing
Sentinel 2
Species diversity
Wetland ecology
Freshwater productivity
Wetland agriculture
spellingShingle Aboveground biomass
mapping
remote sensing
Sentinel 2
Species diversity
Wetland ecology
Freshwater productivity
Wetland agriculture
Mashala, Makgabo Johanna
Assessment and mapping of wetland vegetation as an indicator of ecological productivity in Maungani Wetland in Limpopo, South Africa
description Thesis (M.Sc. (Geography)) -- University of Limpopo, 2020 === Wetland vegetation provides a variety of goods and services such as carbon sequestration, flood control, climate regulation, filtering contamination, improve and maintain water quality, ecological functioning. However, changes in land cover and uses, overgrazing and environmental changes have resulted in the transformation of the wetland ecosystem. So far, a lot of focus has been biased towards large wetlands neglecting wetlands at a local scale. Smaller wetlands continue to receive massive degradation by the surrounding communities.Therefore, this study seeks to assess and map wetland vegetation as an indicator of ecological productivity on a small scale. The Sentinel-2 MSI image was used to map wetland plant species diversity and above-ground biomass (AGB). Four key diversity indices; the Shannon Wiener (H), Simpson (D), Pielou (J), and Species richness (S) were used to measure species diversity. A multilinear regression technique was applied to establish the relationship between remotely sensed data and diversity indices and AGB. The results indicated that Simpson (D) has a high relationship with combined vegetation indices and spectral band, yielding the highest accuracy when compared to other diversity indices. For example, an R² of 0.75, and the RMSE of 0.08 and AIC of -191.6 were observed. Further, vegetation AGB was estimated with high accuracy of an R² of 0.65, the RMSE 29.02, and AIC of 280.21. These results indicate that Maungani wetland has high species abundance largely dominated by one species (Cyperus latifidius) and highly productive. The findings of this work underscore the relevance of remotely sensed to estimate and monitor wetland plant species diversity with high accuracy.
author2 Dube, T.
author_facet Dube, T.
Mashala, Makgabo Johanna
author Mashala, Makgabo Johanna
author_sort Mashala, Makgabo Johanna
title Assessment and mapping of wetland vegetation as an indicator of ecological productivity in Maungani Wetland in Limpopo, South Africa
title_short Assessment and mapping of wetland vegetation as an indicator of ecological productivity in Maungani Wetland in Limpopo, South Africa
title_full Assessment and mapping of wetland vegetation as an indicator of ecological productivity in Maungani Wetland in Limpopo, South Africa
title_fullStr Assessment and mapping of wetland vegetation as an indicator of ecological productivity in Maungani Wetland in Limpopo, South Africa
title_full_unstemmed Assessment and mapping of wetland vegetation as an indicator of ecological productivity in Maungani Wetland in Limpopo, South Africa
title_sort assessment and mapping of wetland vegetation as an indicator of ecological productivity in maungani wetland in limpopo, south africa
publishDate 2021
url http://hdl.handle.net/10386/3478
work_keys_str_mv AT mashalamakgabojohanna assessmentandmappingofwetlandvegetationasanindicatorofecologicalproductivityinmaunganiwetlandinlimpoposouthafrica
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