## 4 Results
### Comparison with Landsat  
To assess the reliability of the proposed approach, the Landsat 7 ETM+ image of 5 December 2013, at 9:31 GMT, was exploited (Figure 1). In Figure 6(a), a magnification of the area within the red box in Figure 1 is plotted, using the Boolean mask already plotted in Figure 2 in the background, where water affected areas are clearly visible along the Basento and Lato rivers, notwithstanding no data acquisition due to the Landsat 7's Scan Line Corrector (SLC) failure. An area of about 28 km\({}^{2}\) was identified as water affected within the investigated box (green pixels in Figure 6(a)). The RST-FLOOD results carried out for 5 December 2013 have been superimposed on those areas aggregating MODIS and VIIRS detections (at 11:30 GMT and 11:52 GMT, respectively) achieved with the same ALICE index (Figure 6(b),c), estimating an area ranging between 15 and 18 km\({}^{2}\) when the ratio (Figure 6(c)) and the difference (Figure 6(b)) index is used, respectively. Considering all the Landsat \begin{table}
\begin{tabular}{c c c} \hline  & **ALICE\({}_{\text{NIR-VIS}}\)** & **ALICE\({}_{\text{NIR/VIS}}\)** \\ \hline
4 December 2013 & 214 & 272 \\
5 December 2013 & 262 & 243 \\ \hline \end{tabular}
\end{table} 
Table 2: Number of anomalous pixels identified by the two ALICE indices in the two analyzed VIIRS imagery. Figure 6: Anomalous pixels detected within the red box shown in Figure 1 by VIIRS-based RST-FLOOD on (**a**) 4 December 2013 at 12:10 GMT and (**b**) 5 December 2013 at 11:52 GMT using ALICE\({}_{\text{NIR-VIS}}\) (violet pixels) and ALICE\({}_{\text{NIR/VIS}}\) (orange pixels). In green, the pixels detected as anomalous by both indices are highlighted. 7 water affected pixels depicted in Figure 7a as a benchmark for assessing the extension of flooded areas, a maximum underestimation of about 46% was computed for RST-FLOOD. The large difference in terms of spatial resolution among ETM+ and the two optical sensors used in this work forms the basis of this result [12]. Spurious and isolated ETM+ water affected pixels cannot be detected at the spatial resolution allowed by MODIS and VIIRS. Moreover, even when those pixels are aggregated, their total contribution in terms of sub-pixel effect can provide a result lower than the expected value as defined by RST-FLOOD, and therefore they are not identified as anomalous. On the other hand, such an outcome is quite relevant, because it confirms the potential of the proposed approach in effectively detecting the presence of flooded areas notwithstanding the medium spatial resolution of the used data. Furthermore, concerning Landsat 7 water affected pixels, it is worth mentioning that they also take into account permanent water, as well as other effects not directly ascribable to water presence. Figure 7: (**a**) Subset of the image shown in Figure 2 highlighting water affected pixels; (**b**) anomalous pixels detected by ALICE\({}_{\text{NIR-VIS}}\) on 5 December 2013 at 11:30 GMT for MODIS (pink) and at 11:52 GMT for VIIRS (violet); (**c**) anomalous pixels detected by ALICE\({}_{\text{NIR/VIS}}\) on 5 December 2013 at 11:30 GMT for MODIS (orange) and at 11:50 GMT for VIIRS (brown). In any case, such a comparison shows the satisfactory capability of the proposed approach in detecting flooded areas regardless of the sensors used, and the different sensitivities of RST-FLOOD indicators when implemented on MODIS and VIIRS imagery. These aspects assume great relevance in detecting flooded areas by optical satellite data, reinforcing the great usefulness of implementing an integrated satellite system within the flood hazard management cycle, allowing for a more detailed identification of flooded areas and a continuous monitoring of the ongoing phenomenon on a large spatial scale. Advantages arising from such an integration are clearly observable when analyzing Figure 8, where the outputs produced by applying the same index on both of the sensors for the two available images are shown.