## 3 Results  
The results achieved for the COSMO-SkyMed and Sentinel-1 datasets in the Norcia and Castellucio areas are reported in Figures 3 and 4, respectively. In both Norcia (Figure 3) and Castellucio (Figure 4), the differences in the ground resolutions among the COSMO-SkyMed Spotlight, StripMap and Sentinel-1 images can be clearly appreciated, thus helping to define the capability of each image source to detect backscattering variations referred to as single buildings. It is worth mentioning that Castellucio village was not included in the Spotlight COSMO-SkyMed footprint; therefore, in this area, the ACD and the CCD analyses were carried out using only the StripMap COSMO-SkyMed and the IW Sentinel-1 datasets. In Figure 5, an extract of the San Benedetto Church in Norcia is shown to compare and to appreciate in detail the potential of the three datasets used at the single-building scale. The cross-check conducted with an on-site damage mapping in Norcia village (Figure 6 and Table 4) confirmed that the ACD and CCD processing of the Spotlight COSMO-SkyMed images had the potential to serve as excellent options for rapid damage mapping at the single-building scale under operational conditions. Figure 3: Results achieved in Norcia village: (**A**) ACD Spotlight COSMO-SkyMed; (**B**) CCD Spotlight COSMO-SkyMed; (**C**) ACD StripMap COSMO-SkyMed ascending; (**D**) ACD StripMap COSMO-SkyMed descending; (**E**) ACD IW Sentinel-1 ascending; and (**F**) ACD IW Sentinel-1 descending. Figure 4: ACD results achieved in Castelluccio village: (**A**) StripMap COSMO-SkyMed ascending; (**B**) StripMap COSMO-SkyMed descending; (**C**) IW Sentinel-1 ascending; (**D**) IW Sentinel-1 descending; and (**E**) Google Earth background of Castelluccio village and elevation contour lines (in m. a. s. l.). The red dotted lines indicatively separate the east-facing portion and the west-facing portion of the village. The difference of the foreshortening related to ascending and descending geometry is clear and demonstrates the importance of the double geometry to map damaged areas in complex topographic environments. Figure 5: Extracts of the San Benedetto Church in Norcia. (**A,B**) Locations and post-earthquake pictures of the church (source: Google); (**C**) ACD Spotlight COSMO-SkyMed; (**D**) CCD Spotlight COSMO-SkyMed; (**E**) ACD StripMap COSMO-SkyMed descending; and (**F**) ACD IW Sentinel-1 descending. Furthermore, it is worth mentioning that, using Spotlight COSMO-SkyMed images, it is possible to map, with many details, the damage affecting slopes, transportation routes, and other infrastructure that are not commonly inventoried during \"Triage\" field inspections and that focus mainly on buildings, as reported in Figure 7, an extract of ancient walls in Norcia that were not inventoried by the Triage. However, we cannot neglect that some false positives can be detected, as shown by the yellow polygons in (Figure 6). These features show changes occurred due to the rise of the rescue facilities. They can be easily filtered out because the position of these structures is known through civil protection emergency plans. A quantitative evaluation for the accuracy of each dataset, computed with respect to the \"ground truth\" derived from Triage field surveys, is reported in Table 4. Collapsed buildings were selected by setting a threshold on yellow (210 \(<\) R \(<\) 255; 210 \(<\) G \(<\) 255; 0 \(<\) B \(<\) 60) and blue (0 \(<\) R \(<\) 60; 0 \(<\) G \(<\) 60; 210 \(<\) B \(<\) 255) and taking into consideration only clusters with at least 4 pixels to discard false alarms due to single noisy pixels.