## 2 Remote Sensing Technologies for the Monitoring of Coastal and River Delta Regions
### Sea Surface Monitoring through SAR-Based Approaches  
Sea surface can be evaluated by studying and estimating sea state parameters, such as bathymetry, waves, currents, wind vectors, etc. [262]. Several sea state observation instruments are available for marine monitoring, such as waveform buoys, weather stations, scatterometers, anemometric stations, etc. Such instruments can provide continuously acquired data but only at fixed locations, usually installed in specific strategic coastal areas. In recent years, SAR has allowed a new and exciting direction of remote monitoring, thanks to its synoptic vision and the ability to provide data covering large areas [263]. Hence, SAR features overcome limits related to some of the classic in situ instruments, and SAR images have been integrated with optical or multispectral images. Furthermore, SAR can be mounted on different platforms, such as aircraft or satellites [108]; this opportunity can provide other techniques and applications to monitor the sea surface state [120]. In the context of marine monitoring, existing satellite SAR systems are widely used to detect oil spills, and there are many other surface characteristics (such as wind, current characteristics, natural films, surface temperature patterns, rain cells) that provide oil-like radar signatures. However, operational use of SAR (satellite or airborne) is limited by some factors. Satellites sensors move along orbits, and therefore, they are governed by celestial laws; this implies, first of all, that the revisiting time, after which the same region is imaged again, is fixed and cannot be changed in the case of emergencies. Moreover, the orbits covered by remote sensing satellites, cannot allow north-south deformation detections. Accordingly, spaceborne sensors could be not flexible enough to be helpful in catastrophe management. In this context, airborne SAR platforms could allow overcoming the above-mentioned limits while also assuring spatial resolutions higher than those of some satellite SAR sensors, due to smaller acceptable dimensions of transmitting antennas. Airborne SAR sensors were developed due to their flexibility and lower cost; hence, they are more efficient than the much more expensive satellite missions [264]. Nevertheless, airborne raw data are affected by the so-called motion errors, which are due to the presence of atmospheric turbulences that produce sensor track deviations from an ideal straight track. Motion errors, if not properly accounted for during the SAR focusing procedure, may seriously damage the quality of the final image. Accordingly, the so-called Motion Compensation (briefly MOCO) algorithms are commonly applied within the SAR focusing step with the aim of achieving the same image accuracy usually reached with spaceborne SAR data [265,266]. Consequently, the choice of the SAR platform is made based on the type of analysis to be developed. The use of SAR data to estimate sea state parameters is based on the computation of the SAR signal backscattered to the radar instrument from the sea, which is governed by the interaction between the transmitted electromagnetic waves and short surface waves. The development of algorithms to extract surface currents from a collected SAR image's amplitude signal is a somewhat complicated issue. Furthermore, the SAR intensity's exclusive use is not enough for the direct measurement of sea currents due to many variables that globally influence the sea backscattering, such as the wind, bathymetry, etc. Therefore, the joint use of amplitude and phase information embedded in the SAR images provides the means to access more direct measurements of interest parameters [120,267]. Marine surface current velocities are a crucial sea state parameter that can also be estimated through SAR sensors, thanks to many research efforts in this field in the last years [120,267,268,269,270,271,272]. Today, SAR-based applications are relatively well-established for estimating waves and the derivation of wind over the sea surface [273,274,275].