MAPPING COASTAL AND WETLAND VEGETATION COMMUNITIES USING MULTI-TEMPORAL SENTINEL-2 DATA

Abstract

Operational monitoring of complex vegetation communities, such as the ones growing in coastal and wetland areas, can be effectively supported by satellite remote sensing, providing quantitative spatialized information on vegetation parameters, as well as on their temporal evolution. With this work, we explored and evaluated the potential of Sentinel-2 data for assessing the status and evolution of coastal vegetation as the primary indicator of ecosystem conditions, by mapping the different plant communities of Venice lagoon (Northeast Italy) via a rule-based classification approach exploiting synoptic seasonal features of spectral indices and multispectral reflectance. The results demonstrated that coastal and wetland vegetation community type maps derived for two different years scored a good overall accuracy around 80%, with some misclassification in the coastal areas and overestimation of salt marsh communities coverage, and that virtual collaborative environments can facilitate the use of Sentinel-2 data and products to multidisciplinary users.