Masters Degrees (Geography and Environmental Studies)

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Browsing Masters Degrees (Geography and Environmental Studies) by Author "Bell, Maria Aletta"

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    Monitoring rehabilitation success using remotely sensed vegetation indices at Navachab Gold Mine, Namibia
    (Stellenbosch : Stellenbosch University, 2015-12) Bell, Maria Aletta; Van Niekerk, Adriaan; Eloff, P. J.; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Geography and Environmental Studies.
    ENGLISH ABSTRACT: Remote sensing and vegetation indices were evaluated for its usefulness to monitor the success of the rehabilitation programme of the decommissioned tailings storage facility (TSF1) of the Navachab Gold Mine, Karibib, Namibia. The study aimed to objectively illustrate the rehabilitation progression from tailings (baseline) to soil (capping) and vegetation (planted as well as natural). Baseline data sets of 2004 and 2005 were compared with imagery of 2009, 2010 and 2011. All the images were subjected to panchromatic sharpening using the subtractive resolution merge (SRM) method before georegistration. As no recent accurate topographical maps were available of the study area, the May 2010 image was used as a reference image. All other images were georegistered to this image. A number of vegetation indices (VIs) were evaluated. The results showed that the normalised difference vegetation index (NDVI) and the transformed vegetation index (TVI) provided the most promising results. Although the difference vegetation index (DVI) and enhanced vegetation index (EVI) distinguished the vegetation, rock, and soil classes, it was not as successful as the other VIs in classifying the rain water pond. TVI and NDVI were further evaluated for their efficacy in detecting changes. This was done by generating a series of change images and by qualitatively comparing them to false colour images of the same period. Both the NDVI and TVI delivered good results, but it was found that the TVI is more successful when water is present in the images. The research concludes that change analyses based on the TVI is an effective method for monitoring mine rehabilitation programmes.