Synergetic use of unmanned aerial vehicle and satellite images for detecting non-native tree species: An insight into Acacia saligna invasion in the Mediterranean coast - Marzialetti, Flavio; Di Febbraro, Mirko; Frate, Ludovico; De Simone, Walter; Acosta, Alicia Teresa Rosario; Carranza, Maria Laura (Frontiers in Environmental Science, 2022)
Invasive Alien Plants (IAPs) are increasingly threatening biodiversity worldwide, thus early detection and monitoring tools are still needed. Here we explored the potential of Unmanned Aerial Vehicle (UAV) images in providing intermediate reference data able to link IAPs field occurrence and satellite information. Specifically, we used very high spatial resolution (VHR) UAV maps of A. saligna as calibration data for satellite based predicting its spread in Mediterranean coastal dunes. Based on two satellite platforms (PlanetScope and Sentinel-2), we developed and tested a dedicated procedure to predict A. saligna spread organized in four steps: (1) setting of calibration data for satellite-based predictions, by aggregating UAV-based VHR IAPs maps to satellite spatial resolution (3 m and 10 m); (2) selection of monthly multispectral (blue, green, red and near infra-red bands) cloud-free images for both satellite platforms; (3) calculation of monthly spectral variables depicting leaf and plant characteristics, canopy biomass, soil features, surface water and of Hue, Intensity and Saturation values; (4) prediction of A. saligna distribution and identification of the most important spectral variables discriminating IAPs occurrence using a Random Forest model (RF). RF models calibrated for both satellite platforms showed high predictive performances (R2 > 0.6; RMSE < 0.008), with accurate spatially-explicit predictions of the invaded areas. While Sentinel-2 performed slightly better, the PlanetScope-based model effectively delineated invaded areas edges and small patches. The summer leaf chlorophyll content followed by soil spectral variables resulted the most important variables discriminating A. saligna patches from native vegetation. Such variables depicted the characteristic IAP phenology, and the typically altered leaf litter and soil organic matter of invaded patches.