Change Detection of Vegetation Cover Using Remote Sensing and GIS – A Case Study of the West Coast Region of South Africa
https://doi.org/10.24057/2071-9388-2021-067
Abstract
This article investigates the possible permanent vegetation cover (VC) change over an extended time for five municipal regions in South Africa by applying satellite-acquired remote sensed normalized difference vegetation index (NDVI) values within a geographic information system (GIS), spatial (West Coast District) and time (1981 to 2019 and 2000 to 2020) context. The NDVI index measures surface reflectance and give a quantitative estimation of vegetation growth and biomass. The study found relevance in its application since VC change detection has taken prominence over the past number of years in terms of sustainable development. Methods of analysis include image mapping, temporal image differencing, Moran I statistic, and the Mann-Kendall trend test. In the main areas that recorded significant changes in their NDVI values (plus or minus 0.4 difference on their original NDVI value) over time, in general, have experienced substantial and permanent VC change. These areas are also spatially clustered and concentrated within specific areas within the wider district. However, these areas constitute only a minority of areas (less than 20%), whereas most of the areas within the district did not experience such significant and permanent change in VC. Instead, the changes that did occur in these majority of areas were related to seasonal variation, i.e., temporal changes.
About the Author
Clive Coetzee
Faculty of Military Science, University of Stellenbosch
South Africa
South Africa
Private Bag X2, Saldanha, 7396
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Review
For citations:
Coetzee C. Change Detection of Vegetation Cover Using Remote Sensing and GIS – A Case Study of the West Coast Region of South Africa. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2022;15(2):91-102. https://doi.org/10.24057/2071-9388-2021-067
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