Mapping Prosopis L.(Mesquites) Using Sentinel‐2 MSI Satellite Data, NDVI and SVI Spectral Indices with Maximum‐Likelihood and Random Forest Classifiers

摘要: Mapping of invasive alien plants (IAPs) is important for developing informed initiatives to assist environmentalists in managing the spread and impacts of IAPs. The Prosopis plant species is an aggressive IAP that has been considered a scourge in different regions of the globe. The aim of this study is to map the spatial distribution of the invasive alien Prosopis plant in southwestern Botswana using the higher spatial and spectral resolution Sentinel‐2A (S2A) MultiSpectral Instrument (MSI) satellite sensor data. Supervised parametric maximum likelihood classification (MLC) was compared with the nonparametric Random Forest (RF) classifier for the detection and mapping of the Prosopis using 10 m S2A sensor bands, integrated with normalized difference vegetation index (NDVI) and Sentinel Improved Vegetation Index (SVI). Using S2A, S2A and NDVI, and S2A and SVI, MLC mapped the land use/land cover …