Dynamic land cover mapping exploiting hyperspectral prisma data

Earth Observation derived land cover products can provide an advance insight into coastal ecosystem monitoring to capture the fragmentation and changes of land surface. The work addresses the testing of consolidated classification algorithms on hyperspectral data in synergy with SAR and field data for the definition of biological and geophysical characteristics of surface coverage components to produce a detailed Dynamic Land Cover map. We obtain reliable land cover and land use information identifying different types of vegetation and soils condition and indicators of biogeophysical surface processes in the testing costal area of the Gulf of Oristano (Italy). The results offer further classification of specific land cover targets representing a contribution for the production of land cover products at different levels of thematic resolution to improve downstream application services and to support land policies and management.