Evaluating the spatiotemporal changes of urban wetlands in Klip River wetland, South Africa
Date
2023-09
Authors
Journal Title
Journal ISSN
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Publisher
University of the Witwatersrand, Johannesburg
Abstract
This study assesses the impacts of land use / land cover (LULC) change in an urban wetland over the past 30 years utilizing machine learning and satellite-based techniques. This study looked at LULC distributions in the Klip River wetland in Gauteng, South Africa. The aims and methods used in this study were: (1) to conduct a comprehensive analysis to map and evaluate the effects of LULC changes in the Klip River wetland spanning from 1990 to 2020, employing Landsat datasets at intervals of 10 years, and to quantify both spatial and temporal alterations in urban wetland area. (2) To predict the change in urban wetland area due to specific LULC changes for 2030 and 2040 using the MOLUSCE plugin in QGIS. This model is based on observed LULC including bare soil, built-up area, water, wetland, and other vegetation in the quaternary catchment C22A of the Klip River wetland, using multispectral satellite images obtained from Landsat 5 (1990), Landsat 7 (2000 and 2010) and Landsat 8 OLI (2020). (3) For the results of this study, thematic maps were classified using the Random Forest algorithm in Google Earth Engine. Change maps were produced using QGIS to determine the spatiotemporal changes within the study area. To simulate future LULC for 2030 and 2040, the MOLUSCE plugin in QGIS v2.8.18 was used. The overall accuracies achieved for the classified maps for 1990, 2000, 2010, and 2020 were 85.19%, 89.80%, 84.09%, and 88.12%, respectively. The results indicated a significant decrease in wetland area from 14.82% (6949.39 ha) in 1990 to 5.54% (2759.2 ha) in 2020. The major causes of these changes were the build-up area, which increased from 0.17% (80.36 ha) in 1990 to 45.96% (22 901 ha) in 2020—the projected years 2030 and 2040 achieved a kappa value of 0.71 and 0.61, respectively. The results indicate that built-up areas continue to increase annually, while wetlands will decrease. These LULC transformations posed a severe threat to the wetlands. Hence, proper management of wetland ecosystems is required, and if not implemented soon, the wetland ecosystem will be lost.
Description
A dissertation submitted in partial fulfilment of the degree of Master of Science (in GIS and Remote Sensing), Faculty of Science, School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg, 2023.
Keywords
Urban wetland, Machine learning algorithm, Random Forest, Remote sensing, MOLUSCE, Land use/Land cover changes, Klip River wetland, UCTD
Citation
Nxumalo, Nolwazi. (2023). Evaluating the spatiotemporal changes of urban wetlands in Klip River wetland, South Africa. [Master's dissertation, University of the Witwatersrand, Johannesburg]. https://hdl.handle.net/10539/42514