## 2 Materials and Methods
### Amplitude and Coherent Change Detection  
SAR images consist of complex data containing the amplitude and phase information of backscattered signals. Both these information types can be used as indicators for change detections. Two change detection approaches can be performed using SAR data [26]: the amplitude change detection (ACD), which identifies changes in backscatter intensity between two or more scenes; and the coherent change detection (CCD), which investigates interferometric coherence between two or more scenes [27]. To simulate an emergency scenario and to investigate the performance of our datasets, we selected the images pairs nearest to the event (StripMap and Sentinel-1) and, in the case of Spotlight, it was the only available since they are very rare. In the CCD method we also selected image pairs considering the best compromise with the lower temporal baseline and InSAR coherence. Pre-processing of the COSMO-SkyMed and Sentinel-1 SAR images, including coregistration and interferogram computation to generate interferometric coherence, was carried out by using SARPROZ software before applying ACD/CCD. Both IRIS and SARPROZ software were used for the ACD/CCD analyses, with the aim to generate an RGB image through the combination of different channels together, by using two or more SAR images and assigning to the R, G, and B channels the amplitude or the InSAR coherence of the SAR images (Equations (1) and (2)). In ACD methods, amplitude values are used without interferometric phase information by calculating the amount to which the backscatter intensity changed due to natural disasters, using the difference between or the ratio of SAR images acquired before and after the event [12]. This technique is sensitive only to changes that affect backscatter and does not consider complex SAR information (intensity or phase). However, such events must be of adequate size to be recognizable in SAR imagery, and the changes in backscatter intensity must be higher than the noise or the speckle effect. We combined the amplitudes of three different images to generate RGB images (i.e., two images taken before and one after the earthquake). We assigned the RGB channels as follows (Table 2). \[ \begin{array}{l}\text{R}=\text{amplitude Image \#1; [0-255]}\\ \text{G}=\text{amplitude Image \#2; [0-255]}\\ \text{B}=\text{amplitude Image \#3. [0-255]}\\ \end{array}  \tag{1}\]  
In CCD, the InSAR coherence of an image pair is used to quantify changes in the phase of each pixel of the images. Loss of coherence or any decorrelation in the phase allows the quantification of the scattering characteristic changes and the subsequent detection of surface changes [28; 29]. This approach reveals changes that are not detectable in the pixel intensities/amplitudes, since changing the surface generates phase differences and leads to the decorrelation of complex signals. We combined the amplitudes and the phases of two images from each dataset (i.e., one taken before and one after the earthquake) to generate RGB images. In particular, the RGB channels were filled as follows (Table 3). \[ \begin{array}{l}\text{R}=\text{interferometric coherence between Image\#1 and Image\#2 [0-255]}\\ \text{G}=\text{(amplitude Image\#1+ amplitude Image\#2)/2 [0-255]}\\ \text{B}=\text{amplitude Image\#1--amplitude Image\#2 [0-255]}\\ \end{array}  \tag{2}\] \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Dataset** & **Image \#1** & **Image \#2** & **Image \#3** \\  & **(dd/mm/yyyy)** & **(dd/mm/yyyy)** & **(dd/mm/yyyy)** \\ \hline Spotlight & 31 August 2016 & 30 October 2016 & 31 October 2016 \\ StripMap HIMAGE Ascending & 5 October 2016 & 21 October 2016 & 22 November 2016 \\ StripMap HIMAGE Descending & 11 October 2016 & 27 October 2016 & 3 November 2016 \\ Sentinel-1 Ascending & 20 October 2016 & 26 October 2016 & 1 November 2016 \\ Sentinel-1 Descending & 19 October 2016 & 25 October 2016 & 31 October 2016 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: RGB combination used for each stack for the ACD.