An integrated approach for environmental multi-source remote sensing

 

Remote sensing measurements have benefited from a great technological improvement, which has allowed a higher degree of automation while increasing spatial and temporal resolution of the collected data. Multi-     scale and multi-frequency optical and radar satellite sensors, often adopted in an integrated manner, are starting to provide efficient solutions for controlling and monitoring rapidly evolving urban and natural areas. On the other hand, close range remote-sensing techniques, such as operated by UAV platforms, and innovative ground-based instruments offer, respectively, the chance to downscale the observation performing site-specific analysis at an enhanced resolution and to collect in-situ dataset for calibration and data quality. By improving the quantity and quality of the collected data, a better understanding of the in-going processes is possible and the setting up of a numerical forecast model for future scenarios.

 

Therefore, implementation of integrated techniques for environmental monitoring turns out to be a strategic solution to analyze hazardous areas at different spatial and temporal resolution. Research devoted to the optimization of data processing tools by means of AI algorithms has evolved with the aim of improving the level of information and its reliability. In this context, a great impact is linked to the availability of open data and open-source processing tools distributed after the Copernicus Program.

 

A review of the available technologies for environmental monitoring is provided including examples on experimental cases in areas affected by natural hazards (volcanic eruptions, landslides, coastal erosion, flooding, etc.) and human activities that can produce incidental damages on the environment (urbanization, agriculture, infrastructures, landfills, dumpsites, pollutions, etc.). In addition, the same approach is useful for monitoring the degradation of the cultural heritage sites. Finally, the capability of collecting fat at a global level contributed to the analysis of environmental and economic impacts consequent the Covid-19 pandemic.