TY - JOUR
T1 - Understanding the Relationship Between Land Use, Land Cover Changes, and Water Quality in Polluted Urban Water Systems
T2 - A Remote Sensing Perspective
AU - Phunge, Muwanwa
AU - Dhau, Inos
AU - Modley, Lee Ann
N1 - Publisher Copyright:
© The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
PY - 2025/1/1
Y1 - 2025/1/1
N2 - Land use and land cover change threaten the ecological state of the most polluted urban catchment in South Africa due to the loss of biodiversity. For a country undergoing rapid economic growth, monitoring the impact of land use on water quality provides effective water management mitigations. Therefore, this study aimed to assess the impact of land use and land cover changes on water quality. Historical land use and land cover and water quality data from 2003, 2008, 2013, 2018, and 2023 were used to determine the correlation. Supervised classification with a maximum likelihood classifier was applied to generate LULC classification maps for the selected periods. The Spearman correlation model was used to determine the relationship between LULC change and water quality variables. The results of the LULC change from 2003 to 2023 revealed an increase in residential areas, bare soil, and mines; meanwhile, forest/agriculture and water bodies recorded a decreasing trend. The study findings highlighted the need to adopt sustainable land use management practices to minimise further water quality deterioration in the Klip River.
AB - Land use and land cover change threaten the ecological state of the most polluted urban catchment in South Africa due to the loss of biodiversity. For a country undergoing rapid economic growth, monitoring the impact of land use on water quality provides effective water management mitigations. Therefore, this study aimed to assess the impact of land use and land cover changes on water quality. Historical land use and land cover and water quality data from 2003, 2008, 2013, 2018, and 2023 were used to determine the correlation. Supervised classification with a maximum likelihood classifier was applied to generate LULC classification maps for the selected periods. The Spearman correlation model was used to determine the relationship between LULC change and water quality variables. The results of the LULC change from 2003 to 2023 revealed an increase in residential areas, bare soil, and mines; meanwhile, forest/agriculture and water bodies recorded a decreasing trend. The study findings highlighted the need to adopt sustainable land use management practices to minimise further water quality deterioration in the Klip River.
KW - land use classification
KW - pollution
KW - satellite data
KW - urbanisation
KW - water management
UR - https://www.scopus.com/pages/publications/105011062840
U2 - 10.1177/11786221251342907
DO - 10.1177/11786221251342907
M3 - Article
AN - SCOPUS:105011062840
SN - 1178-6221
VL - 18
JO - Air, Soil and Water Research
JF - Air, Soil and Water Research
M1 - 11786221251342907
ER -
