Abstract
Accurate assessment of savanna woody plant species diversity using remote sensing technologies can help ecologists by providing timely and cost-effective information for sustainable ecosystem management. With the ever-increasing variety of remotely-sensed data becoming available to the public, there is a need to understand the performances of different sensors (optical and structural) in discriminating multiple woody plant species in the savanna environment with morphologically similar features. The overall aim of the present study was to investigate the utility of remote sensing techniques in estimating woody plant species diversity (n = 30) including three different land cover types identified in a complex and localised savanna environment. This was achieved through the following specific objectives: The first objective was to characterise woody plant species diversity during a dry season or period within in a savanna environment, using textural information derived from WorldView- 2 imagery. The second objective was to compare the utility of three multispectral images (WorldView-2, Sentinel-2A and SPOT-6) in classifying woody plant species during a dry season or period. The third objective focussed on the comparison of the classification of savanna woody plant species between wet and dry seasons using Sentinel-2A and SPOT-6 images. The fourth objective assessed the impact of data fusion between Sentinel-1 C band Radio Detection and Ranging (RADAR) and Sentinel-2A multispectral data on discrimination of savanna woody plant species...
Ph.D. (Geography)