# A Synthetic Aperture Radar-Based Robust Satellite Technique (RST) for Timely Mapping of Floods
## 7 Discussion
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Event 5: Zaragoza Inundation 10 December 2021** & \multicolumn{3}{c}{**Reference Data**} & \multicolumn{3}{c}{**Accuracy Matrix**} \\ \hline  & Flood & Not Flood & UA\({}_{\text{f}}\) & UA\({}_{\text{nf}}\) & PA\({}_{\text{f}}\) & PA\({}_{\text{nf}}\) & K \\
**RST-SAR-FLOOD** & Flood & 360,790 & 147,090 & 0.97 & 0.95 & 0.87 & 0.90 & 0.87 \\  & Not Flooded & 24,790 & 4,762,093 & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Confusion matrix for the Ebro River (Zaragozza) event (16 December 2021). the considered test cases in greater detail, i.e., the Ebro River event that occurred around Zaragozza in December 2021. Two other S1 images were available after the one of 16 December 2021, already analyzed (Figure 8). The first one was acquired on 17 December 2021 by S1A and the second on 22 December 2021 by S1B. The results of the RST-SAR-FLOOD application for these two images are shown in Figure 9a,b. Figure 9: Flood maps of the Ebro River (Zaragozza) event for: (**a**) 17 December 2021; (**b**) 22 December 2021. A clear reduction in the flooded areas is evident in the two maps, especially in the second one, highlighting the zones most affected by the flood, whose presence was still evident one week after the first detection. This information, typically acquired when a meteorological perturbation is still present and hence prevents optical data acquisition, is fundamental to better manage recovery actions, as well as to delineate clear flooding scenarios useful for implementing future mitigation activities. The availability of more images, together with other information acquired remotely or in situ, such as the measurement of rainfall spatial and temporal variability, is fundamental for modelling and reconstructing catastrophic flooding events [68]. The integration of human observations (crowdsourced data) may further help to validate complex flooding events in data-scar areas with unavailable gauged records [68; 69; 70]. Finally, it should be stressed that accurate indications about the areas affected by a flood event are fundamental to developing flood hazard maps that are useful for risk-aware analyses and designs [71]. In this context, the development of probabilistic approaches and stochastic techniques for flood hazard assessment may improve the definition of flood risk scenarios [71]. The implementation of the proposed methodology was made possible by the concurrence of two factors. The European Union's choice to make all the data collected within the Copernicus program open and freely available represents an innovative idea that has allowed for the growing use of these data in the everyday life of each kind of potential stakeholder, from local regional authorities to the general public [72], as well as the development of several downstream applications. This has been facilitated and accelerated by the development of cloud computing systems, such as GEE, which permits \"easy\" access to and processing of these data [33], overcoming one of the main barriers to a more systematic use of Copernicus data/products [72]. The potential limitations of the RST-SAR-FLOOD method may be represented by a reduced capability to investigate floods occurring in urban areas, mountainous regions, and coastal zones, where the discrimination between flooded pixels and others showing similar characteristics could be more complicated [18]. Another issue of the proposed approach is represented by the current temporal resolution of Sentinel 1 data. S1B, launched in April 2016, stopped working on 23 December 2021, soon after the acquisition of the image analyzed in Figure 9, due to a failure of the electronic power supply to the instruments [54]. The ESA is currently working on the launch of Sentinel-1C as soon as possible to re-establish the satellites constellation [73].