Estimating Aquatic Plant Diversity Using Spectral Metrics from Drone Hyperspectral Imaging

Due to their morpho-physiological peculiarities and wide phenotypic plasticity, aquatic plants occupy the extremes of the global spectrum of vegetation forms; such heterogeneity results in them exhibiting contrasting patterns of diversity along ecological and geographical gradients. In the last decade, high-throughput imaging spectroscopy has emerged as a feasible and efficient option for assessing plant diversity based on spectral proxies directly related to morphological and biochemical traits, which we define as spectro-functional traits. Linking spectral traits with plant species diversity to characterise plant communities can further advance this topic. In this study, we explored the use of spectral features extracted from centimetre resolution hyperspectral images collected by a drone to estimate functional diversity using generalized additive models (GAMs) within communities of floating hydrophytes and helophytes sampled across a trophic gradient.