Development of an automatic methodology, based on open source tools, for the analysis of hyperspectral and multispectral satellite imagery in forest cover mapping: comparison between PRISMA and Sentinel-2 data.

The doctoral work aims to investigate the potential of new hyperspectral data that will be available and to develop an automatic methodology, based on open-source tools, to manage them agilely, analyze them, and study forest cover through their classification. Specifically, a methodology has been developed for the management and classification of experimental hyperspectral data from the Italian satellite mission PRISMA (PRecursore IperSpettrale della Missione Applicativa), which have characteristics very similar to the data that will be provided by new satellite missions planned for the end of this decade (2020-2030). In parallel, the ability of the same methodology to process other types of data was tested, specifically using data derived from multispectral images of the Copernicus Sentinel-2 satellite.