A research report submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirement for the degree of Masters of Science (GIS and Remote Sensing) at the School of Geography, Archaeology & Environmental Studies / Tamarix spp, commonly known as tamarisk or salt cedar, belong to the family of Tamaricaceae. It is a phreaphytic halophyte with 55 species in the genus Tamarix. South Africa has one indigenous (Tamarix usneoides) and two exotic (T. ramosissima and T.chinensis). Not only are the exotic Tamarix species becoming infamous invaders, but their hybridisation with the indigenous T. usneoides is also complicating morphological discrimination between the different species, and the prospect of potential use of bio-control agents to curb invasion. Thus, lack of spatial information about the current and the past distribution of tamarisk have hampered the effort to control its invasion. This study aimed at investigating the use of multi-temporal remotely sensed data to map the exotic Tamarix invasion in the riparian ecosystem of the Western Cape Province of South Africa, where it predominantly occurs. Random Forest (RF) and Support Vector Machine (SVM) were tested to classify Tamarix and other land-cover types. Sentinel 2 data and Landsat OLI earth observation data were used to map the current and the temporal exotic Tamarix distribution between 2007 and 2018, respectively. This included mapping the current and the multi-temporal Tamarix extent of invasion using the multi-spectral sensors Sentinel 2 and Landsat 5 and 8, respectively. Sentinel 2 was able to detect and discriminate the exotic Tamarix spp invasion using RF and SVM algorithms. The Random Forest classification achieved an overall accuracy of 87.83% and kappa of 0.85, while SVM achieved an overall accuracy of 86.31% and kappa of 0.83. Multi-temporal Landsat data was able to map the current and previous extent of exotic Tamarix invasion for the period between 2007 and 2018. Six land-cover types were classified using SVM. The overall accuracies achieved for 2007, 2014 and 2018 were 87.66%, 91.10%, and 90.62% respectively, and the kappa were 0.85, 0.89, and 0.88, respectively. It was found that the exotic Tamarix invasion increased from 284.67 ha to 647.10 ha in De Rust area, 74.70 ha to 97.29 ha in Leeu Gamka and 215.01 ha to 544.41 ha in Prince Albert region in a period of 11 years. Sentinel 2 and Landsat data have shown the potential to be used in Tamarix mapping. The results obtained in this study would help in implementation of conservation and rehabilitation plans. / GR 2020