## 2 Materials and Methods
After image coregistration of the stack of Level 1A complex products to achieve subpixel precision, five interferometric SAR pairs (Table 2) were formed with the objectives to:  
* temporally capture the two events via cross-event pairs, i.e., pre-event versus post-event scenes: one pair for the December 2014 event (i.e., 10/07/2014-12/04/2015), and three for the January 2018 event (i.e., 13/12/2017-30/01/2018, 10/01/2018-30/01/2018, and 26/01/2018-30/01/2018);
* analyse the areas where the two events occurred, but during time periods unaffected by the events themselves, in particular: before the January 2018 event (i.e., 18/01/2018-26/01/2018), and after the December 2014 event (i.e., 13/12/2017-30/01/2018). Differential interferograms were generated from the selected image pairs by subtracting topographic phase information based on NASA's shuttle radar topography mission (SRTM) global digital elevation model (DEM) at 1 arc-sec (\(\sim\)30 m) spatial resolution. No multilooking for the creation of the interferograms was employed, in order to keep the original scene resolution in range and azimuth. However, a Gaussian weighting filter with an adaptive window size of 3 to 5 pixels, as well as \begin{table}
\begin{tabular}{c c} \hline \hline
**Image Date (DD/MM/YYYY)** & **Satellite** \\ \hline
10/07/2014 & COSMO-SkyMed 2 \\
12/04/2015 & COSMO-SkyMed 4 \\
13/12/2017 & COSMO-SkyMed 4 \\
10/01/2018 & COSMO-SkyMed 2 \\
18/01/2018 & COSMO-SkyMed 1 \\
26/01/2018 & COSMO-SkyMed 2 \\
30/01/2018 & COSMO-SkyMed 4 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: COSMO-SkyMed StripMap HIMAGE scenes used for the analysis of the December 2014 and January 2018 events that occurred within the Nasca Lines WHS at the locations reported in Figures 1 and 2.  
range spectral shift filtering and azimuth common-band filtering, were exploited during the estimation of interferometric coherence (\(\gamma\)). The latter is a dimensionless number ranging between 0 and 1 that indicates the quality of interferometric fringes and can be estimated as the absolute value of the cross-correlation coefficient between two complex SAR images. Interferometric coherence therefore quantifies the degree of correlation between phase and amplitude information of the two images forming the pair, with \(\gamma=0\) indicating no coherence and \(\gamma=1\) a perfect correlation. The use of an adaptive window size for the estimation of coherence allowed a trade-off between the spatial resolution of the estimation and the estimation bias. This is achieved by using a smaller window size in high-coherence areas to keep the highest possible resolution and a larger window size in low-coherence areas (e.g., \(\gamma\) of 0.1-0.3) to minimise the bias. A wealth of other COSMO-SkyMed StripMap HIMAGE scenes acquired over the Nasca Lines exists in the data catalogue since 2011, which are potentially available to create many other interferometric pair combinations. Nevertheless, the abovementioned scenes and respective pairs were the only ones allowing both a suitable temporal sampling of the two selected events, and the optimisation of temporal (\(B_{t}\)) and normal baseline (\(B_{p}\)) combinations to minimize temporal and geometric decorrelation (Table 2). This enhanced the potential to identify decorrelation instances due to the events and reduce coherence loss due to baseline differences. The advantage in terms of data availability offered by the rich catalogue of COSMO-SkyMed scenes was therefore exploited to increase the opportunities for SAR image selection and consequent InSAR pair combination, and to undertake a more comprehensive change detection analysis of the two selected events of site disturbance (see discussion in Sections 3.1 and 3.2). The seven COSMO-SkyMed scenes and their derived products were ultimately geocoded to map geometry using the WGS84 ellipsoid, and ingested into a GIS environment to carry out the interpretation of the events.