Remote sensing of plant diversity from terrestrial to aquatic systems – a case study in Italy

The expansion of remote sensing applications has advanced the study of vegetation function and diversity, mainly focusing on terrestrial plants, but more recently including aquatic species. However, the relationship between spectral characteristics and plant diversity, especially in land-water interface ecotones, remains underexplored. To address this, new empirical data were collected from study sites in Italy and China to develop methods for estimating species and functional diversity from spectral data covering highly heterogeneous plant communities ranging from terrestrial to aquatic ecosystems. The reference data collection in the Italian study site was carried out in June-August 2024 in the Mantua lake system (wetland ecosystem), Parco del Mincio wet meadows (grassland ecosystem) and Bosco Fontana (forest ecosystem) from 30 target plant communities (10 each for the three ecosystem types), ranging from aquatic (floating and emergent hydrophytes, riparian helophytes) to terrestrial (wet grasslands and floodplain forests): community composition, functional traits, spectral response, drone-based hyperspectral and LIDAR data, and synthetic parameters characterising environmental conditions (e.g., trophic status, substrate). Spectral features extracted from centimetre resolution imaging spectroscopy data were used to estimate plant species diversity based on optical species clustering and parametric models fed with multidimensional spectral features. In addition, the functional diversity of sampled communities was modelled and mapped from centimetre resolution imaging spectroscopy data using diversity metrics based on spectro-functional traits covering target plant groups and spectral hypervolumes (richness and divergence). Further work will be carried out to integrate the data collected in both study sites (Italy and China) into a unique dataset, from which quantitative comparisons of the results obtained will be made to explore which approach is effective for both aquatic and terrestrial vegetation, and to assess the ecological relevance of spatial patterns of plant traits and diversity assessed from remote sensing data across scales and sites.