# A Synthetic Aperture Radar-Based Robust Satellite Technique (RST) for Timely Mapping of Floods
## 7 Discussion  
SAR data have been largely used for flood detection purposes owing to their capability to provide detailed all-day and all-weather information. The Copernicus program, as well as the Cosmo Sky Med mission [65] have facilitated the acquisition of data with good temporal resolution, owing to the presence of several satellites sharing the same payload. One residual limitation related to the intensive computational tasks related to the pre-processing of SAR data, especially when long-term series are analyzed, has been recently faced thanks to the availability of advanced computing platforms, such as Google Earth Engine. In this study, GEE has facilitated the implementation of a multi-temporal approach, RST-FLOOD, on a historical series of S1 data to map different flooding events that have occurred in Europe in recent years. Among the dozen events available, whose analysis would have clearly not been feasible and out of the scope of the study, we selected five flood episodes representative of a wider range of characteristics in terms of the area affected, precipitation, and damage. Moreover, detailed reference data were available for these events, making them useful in terms of assessing the accuracy of the proposed methodology. To this end, in the absence of in situ data, we used other maps and information made available by the Copernicus Emergency Mapping System. In any case, it is worth saying that accurate ground measurements of flood extent are difficult to obtain because of meteorological and safety conditions [66], and they are usually collected with a time delay with respect to satellite acquisition, which could lead to misclassification due to flood dynamics [18]. Therefore, using remote sensing data/products as reference maps, such as those provided by the CEMS, still represents a viable alternative [14; 17; 18; 67], even if also these products may lack accuracy depending on the quality and sensitivity of the considered data and method of analysis. The obtained results, when compared with CEMS maps/information, indicate the feasibility of the proposed approach. In more detail, considering all the analyzed events together, a Kappa index value of 0.78 and an overall accuracy of 0.96 were found, suggesting the good reliability of the method. Similar confirmations arose from the analysis of the Uaf and Paf mean values, equal to 0.78 and 0.90, respectively. Such good results have been obtained notwithstanding several issues typically affecting the accuracy of flood disaster information [18], such as the high heterogeneity (spatial resolution, date of acquisition, etc.) of the considered reference maps, ranging from S1 images to S2, RADARSAT, and ground data, as well as the methods used for detecting flooded pixels. In any case, other events should be investigated in the future to further confirm such results. Owing to its implementation within the GEE platform, where all other ancillary data used to increase the quality of the results are also present, the proposed approach can be easily applied on a global scale and can provide crucial information for remote areas characterized by the presence of ungauged and/or poorly instrumented basins. In these areas, as well as for those where a violent and/or extreme event, such as a flood, can destroy the ground monitoring system, satellite data can represent the only source of information available [68]. Furthermore, the processing of dense SAR time series is performed in a short time, allowing for the rapid production of results. The technique is completely automatic and unsupervised and does not require a preliminary selection of a baseline or human support. Once the accuracy of the proposed approach in mapping flood events was assessed, its potential for monitoring purposes was investigated. To this end, we analyzed the last of