Assessing land use induced disturbance to vegetation cover in the upper Molopo catchment, South Africa, using Landsat images

Abstract

Historical images in archive can serve as data record for quantifying disturbance to vegetation cover. This study used the post-classification comparison change detection technique on a Landsat (TM, ETM+, OLI) image dataset (1989, 1996, 2005, 2013) in assessing long-term effects of land use factors on the vegetation cover of the upper Molopo river catchment, South Africa. The Normalized Difference Vegetation Index (NDVI) enhanced vegetation. Based on field data, three NDVI value classes that indicated the vegetation density could then be identified: high (NDVI > 0.5.), medium (NDVI 0.3–0.5), and low (NDVI < 0.3). These NDVI classes were used in a supervised Maximum Likelihood Classification (MLC) of the respective images. Change in area of cover by the classes indicated a reduction in medium density vegetation, particularly within 5 kilometers of human settlements. There was a statistically significant correlation between human population and medium density vegetation (r = −0.960; P < 0.01).