Mapping Invasive Herbaceous Plant Species with Sentinel-2 Satellite Imagery: Echium plantagineum in a Mediterranean Shrubland as a Case Study

Invasive alien plants (IAPs) pose a serious threat to biodiversity, agriculture, health, and economies globally. Accurate mapping of IAPs is crucial for their management, mitigate impacts prevent further spread where possible. Remote sensing has become valuable tool in detecting IAPs, especially with freely available data such as Sentinel-2 satellite imagery. Yet, remote methods map herbaceous which tend be more difficult detect, particularly shrubland Mediterranean-type ecosystems, are still limited. There growing need detect at large scale monitoring management; however, countries or organizations limited budgets, this often not feasible. To address this, we aimed develop classification methodology based on optical IAP’s using Echium plantagineum case study the Fynbos Biome South Africa. We investigate use data, robust non-parametric classifier Random Forest, identify most important variables classification, all within cloud-based platform, Google Earth Engine. Findings reveal importance shortwave infrared red-edge parts spectrum including vegetation indices discriminating E. plantagineum. Here, demonstrate potential Forest classifier, Engine Mediterranean ecosystems.