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Earth environmental monitoring using multi-source multi-temporal satellite imagery.
Satellite remote sensing has become a strong focus of global interest, offering valuable tools to systematically observe and analyze the Earth's surface and supporting responses to natural risks and disasters. The current ever-growing multi-source capability of orbiting instruments, including hundreds of micro and nano satellites, has been requiring new analysis approaches for the synergistic processing and joint interpretation of this large and heterogeneous amount of data. Here a review of processing techniques for satellite data analysis and environmental monitoring will be presented, together with the emergent use of the newest machine learning and soft computing technologies. Different applications of multi-temporal multi-source satellite imagery analysis will be shown including: volcanic hazards, forest fires, damage mapping and waste disposal sites characterization. Moreover the methodology devised in the framework of the INGV SAFARI project, which designs a comprehensive space-based strategy for next-generation quantitative natural hazard monitoring integrating the most recent satellite imagery capabilities and the relative products, will be proposed.