# A Synthetic Aperture Radar-Based Robust Satellite Technique (RST) for Timely Mapping of Floods
## 8 Conclusions  
In this study, the RST-FLOOD method, which has already proven successful in detecting and monitoring flood events using optical data, was applied to Synthetic Aperture Radar (SAR) data for the first time. Sentinel 1 data, freely provided by the Copernicus program, were used for this aim, exploiting the potential of the Google Earth Engine platform. Five test cases were evaluated by comparing the results of the SAR-RST-FLOOD method with those provided by the Copernicus Emergency Mapping System. The user accuracy values ranged from 0.58 to 0.97, with an average value of 0.78, producing accuracy values from 0.69 to 0.98, with an average value of 0.90, and the K values ranged from 0.68 to 0.87, with an average value of 0.78. These satisfactory results, achieved notwithstanding the discrepancies in terms of spatial resolution, time of acquisition, and method used between the two datasets, indicate the good performance of the proposed approach. Moreover, they highlight the main advantage of a multi-temporal approach, such as the one presented here, with respect to traditional techniques, namely its capability to automatically define local (i.e., at the pixel level) adaptive thresholds useful for the robust identification of flooded areas, reducing the occurrence of false detections. In addition, the strong capability of providing useful information about flood dynamics due to the good temporal resolution provided by the S1 constellation, when fully operational, was also demonstrated. Frequently updated and accurate indications about flood extent during crises are crucial to overcoming the issues related to the poor accessibility of the areas affected by the event, as well as the potentially bad functionality of ground monitoring systems. The high computing potential of the Google Earth Engine platform allows for the rapid generation of results, making the proposed approach suitable for near real-time activities in support of disaster monitoring and management activities. Timely and accurate information about flood extent and evolution is fundamental not only during the emergency phase, when they can allow for better management of the crisis by decision makers, but also in the recovery phase, to develop accurate flood hazard maps that are useful for mitigating the flooding risk for the areas affected by the flood. Considering that the developed system is already filled with all the information useful for its implementation, its potential to be applied on a global scale as well as to support the management of ungauged or remote basins are evident. Local and regional public authorities and institutions can take advantage of our research by integrating the information provided with those by traditional approaches to obtain a clearer understanding of the event in progress. Future analysis will focus on assessing the capability of the SAR-RST-FLOOD approach to detect floods in urban areas, mountainous regions, and coastal zones, trying to implement a method that can be applied everywhere with a constant level of accuracy. Conceptualization, M.L. and T.L. ; methodology, M.L. and T.L. ; software, M.L. and F.A. ; validation, M.L. ; formal analysis, M.L. and T.L. ; writing--original draft preparation, M.L. and T.L. ; writing--review and editing, R.A., A.M. and T.L. ; supervision, T.L. All authors  
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