## 2 Remote Sensing Technologies for the Monitoring of Coastal and River Delta Regions  
The exploitation of Remote Sensing (RS), Geographic Information Systems (GIS), and Global Navigation Satellite System (GNSS) techniques are crucial to maintaining efficient natural disaster management chains, and the knowledge of these methodologies allows the identification of potential gaps existing in the usability of the collected data and encourages the development of new approaches. It is widely accepted that satellite-based EO observations complement traditional in situ measurements. They are valuable tools that allow geospatial products to support decision support systems for different natural calamities. Over the last two decades, we have witnessed a growing availability of RS satellite constellations. The knowledge of natural catastrophes [90; 95; 96; 97; 98; 99; 100; 101] has been improved using many images with various spatial, spectral, and radiometric resolutions. Historically, optical remote sensing satellites using moderate and high spatial resolutions have commonly been used for observing coastal environment evolution. The Landsat satellites have continuously been in operation since 1972, which provides a continuity of high-quality Earth Observations and measurements, with spatial resolutions of about 30 m. The unique continuity and reliability of the Landsat data allow long-period time series analyses to investigate the global evolution of coastal regions [102; 103]. Advanced approaches applying spatial and temporal data fusion models have recently been developed to combine Landsat imagery with lower frequency but higher spatial resolution observations and MODIS and VIIRS observations with a low spatial resolution and higher temporal resolution [104]. In this context, a significant role is now played by the \"Landsat-like\" Sentinel-2 constellation that consists of the two Sentinel-2A/B sensors and routinely provides a global revisit interval of 5 days at a spatial resolution of 10-60 m. Virtual satellite constellations can be designed by combining Landsat, Sentinel-2, and other optical remote sensing satellite data with similar resolutions, effectively increasing the global revisit interval. For example, Landsat-8, Sentinel-2A, and Sentinel-2B data can yield a comprehensive revisit period of 2.9 days [99; 105; 106]. It can map dynamic coastal geomorphological changes at a fine temporal resolution, directly benefiting coastal evolution mapping [107]. Moreover, RS technologies operating at the microwave band of the electromagnetic spectrum are also extensively employed to recover information about the geometrical and electromagnetic properties of an imaged scene. Synthetic Aperture Radar (SAR) represents a uniquely useful microwave instrument for EO, as it can acquire high-resolution data from the Earth with the potential to operate day and night and in any weather condition [108]. Sequences of SAR data are exploited by interferometric SAR techniques (InSAR) [109; 110; 111; 112; 113; 114; 115; 116; 117; 118; 119] for coastal mapping and monitoring to determine regions where severe changes have occurred over time, and correlate these changes with shoreline changes, coastal erosion, groundwater exploitation, etc. Other methodologies, such as measurement of the Doppler Centroid Anomaly (DCA) [120], can provide a viable and accurate estimation of sea surface displacements based on a single SAR image, which are related to currents and wind. Nonetheless, InSAR systems have some limitations that need to be taken into consideration, as they can limit the reliability of the final products to some extent. These include noise introduced by wind [121], heavy precipitation [122], atmospheric perturbations [123], decorrelation phenomena [124], topography decorrelation [125], and other limitations that may arise from an incorrect data processing. If not well understood, the above limitations can be responsible for unreliable results, which could lead scholars to unreal and biased analyzes.