| dc.description.abstract | Detecting and mapping the occurrence, spatial distribution and abundance of Alien Invasive Plants (AIPs) have recently gained substantial attention, globally. This work, therefore, provides an overview of advancements in satellite remote sensing for mapping and monitoring of AIPs and associated challenges and opportunities. Satellite remote sensing techniques have been successful in detecting and mapping the spatial and temporal distribution of AIPs in rangeland ecosystems. Also, the launch of high spatial resolution and hyperspectral remote sensing sensors marked a major breakthrough to precise characterization of earth surface feature as well as optimal resource monitoring. Although essential, the improvements in spatial and spectral properties of remote sensing sensors presented a number of challenges including the excessive acquisition and limited temporal resolution. Therefore, the use of high spatial and hyperspectral datasets is not a plausible alternative to continued and operational scale earth observation, especially in financially constrained countries. On the other hand, literature shows that image classification algorithms have been instrumental in compensating the poor spatial and spectral resolution of remote sensing sensors. Furthermore, the emergence of robust and advanced non-parametric image classification algorithms have been a major development in image classification algorithms. | en_US |
