Mapping distribution patterns of invasive alien species in the Santa Monica Mountains using airborne imaging spectroscopy and line-point transect data

The Santa Monica Mountains National Recreation Area (SMMNRA) is a region of ecological importance, vulnerable to ecosystem degradation due to climate change and the spread of invasive plant species (IPS). Despite wide recognition of the presence and rapid expansion of invasive species in the SMMNRA, few studies have quantified the proportion and distribution of IPS in the region. A combination of high-resolution airborne imaging spectroscopy data and line-point transect data was used to model the distributions of five target IPS. A support vector machine model was applied to the imaging spectroscopy data and achieved an overall accuracy of 93.1%±2.2% over 10 iterations. Additionally, spatial autocorrelation was used to delineate clustering patterns of the five species in both datasets. The species distribution maps and cluster maps derived from both the transects and remote sensing data were compared and contrasted to determine the effectiveness of both approaches for identifying regions of concentrated cover and small cover fractions of the five target IPS. Both datasets revealed species from the Poaceae family were most abundantly distributed in the SMMNRA, followed by Brassicaceae and Asteraceae, though species-level abundance rankings differed. Areas of expansive IPS cover were consistently identified in both the transect and imaging spectroscopy datasets, however, results diverged in heterogeneous landscapes. Transect-based clusters indicated low IPS dominance, while imaging spectroscopy more effectively captured spatial heterogeneity. These results emphasize the value of fine-spatial and spectral resolution data for detecting IPS patterns in complex environments and demonstrate how combining airborne imaging spectroscopy with field-based methods can inform IPS management.