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The threat of invasive alien plant species is progressively becoming a serious global concern. Alien plant invasions adversely affect both ecological services and socio-economic systems. Hence, accurate detection and mapping of invasive alien species is valuable in mitigating adverse ecological and socio-economic effects. Recent advances in active and passive remote sensing technology have created new and cost-effective opportunities for the application of remote sensing to invasive species mapping. In this study, new generation Sentinel-2 ( S2 ) optical imagery was compared to  S2  derived Vegetation Indices (VIs) and  S2  VIs fused with Sentinel-1 ( S1 ) Synthetic Aperture Radar ( SAR ) imagery for detecting and mapping the American Bramble (   Rubus   cuneifolius   ). Fusion of  S2  VIs and  S1  SAR  imagery was conducted at pixel level and multi-class Support Vector Machine (SVM) image classification was used to determine the dominant land use land cover classes. Results indicated that  S2  derived VIs were the most accurate (80%) in detecting and mapping Bramble, while fused  S2  VIs and  S1  SAR  were the least accurate (54%). Findings from this study suggest that the application of  S2  VIs is more suitable for Bramble detection and mapping than the fused  S2  VIs and  S1  SAR . The superior performance of  S2  VIs highlights the value of the new generation  S2  VIs for invasive alien species detection and mapping. Furthermore, this study recommends the use of freely available new generation satellite imagery for cost effective and timeous mapping of Bramble from surrounding native vegetation and other land use land cover types.

The utility of Sentinel-2 Vegetation Indices (VIs) and Sentinel-1 Synthetic Aperture Radar ( SAR ) for invasive alien species detection and mapping