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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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 |
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Aboveground biomass mapping remote sensing Sentinel 2 Species diversity Wetland ecology Freshwater productivity Wetland agriculture |
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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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1719486695439597568 |