Application of a Multispectral UAS to Assess the Cover and Biomass of the Invasive Dune Species Carpobrotus edulis

Abstract

Remote sensing can support dune ecosystem conservation. Unoccupied Aircraft Systems (UAS) equipped with multispectral cameras can provide information for identifying different vegetation species, including Carpobrotus edulis—one of the most prominent alien species in Portuguese dune ecosystems. This work investigates the use of multispectral UAS for C. edulis identification and biomass estimation. A UAS with a five-band multispectral camera was used to capture images from the sand dunes of the Cávado River spit. Simultaneously, field samples of C. edulis were collected for laboratorial quantification of biomass through Dry Weight (DW). Five supervised classification algorithms were tested to estimate the total area of C. edulis, with the Random Forest algorithm achieving the best results (C. edulis Producer Accuracy (PA) = 0.91, C. edulis User Accuracy (UA) = 0.80, kappa = 0.87, Overall Accuracy (OA) = 0.89). Sixteen vegetation indices (VIs) were assessed to estimate the Above-Ground Biomass (AGB) of C. edulis, using three regression models to correlate the sample areas VI and DW. An exponential regression model of the Renormalized Difference Vegetation Index (RDVI) presented the best fit for C. edulis DW (R2 = 0.86; p-value < 0.05; normalised root mean square error (NRMSE) = 0.09). This result was later used to estimate the total AGB in the area, which can be used for monitoring and management plans—namely, removal campaigns.