## 2 Materials and Methods
### Subsidence Causality Inputs
No active faults at less than the century-scale, that could have influenced the surface, were detected in the study area [17]. Hence, this study considered only three potential causes of surface subsidence in the city: rock type, FLLD, and BL. Rock type and FLLD data were collected from secondary data sources [20; 30], as shown in Figure 3, on a true color image of S-2 of 24 October 2018. Figure 3a shows lithological map of the study area modified after the geological map produced by Egyptian geological survey in 1992 and [PERSON] and [PERSON] [20]. While, Figure 3b presents former lakes and lagoon in Alexandria modified after [PERSON] and [PERSON] [20], and [PERSON] [30]. However, BL needed to be developed as no existing data for this factor were available in Alexandria. Figure 3: Rock type and former lakes and lagoons (FLL) in the study area, **(a)** rock type and surface structure of the city, **(b)** former lakes and lagoons in Alexandria. To map the BL of Alexandria, we used the highest resolution data from Sentinel-2. Bands 2, 3, 4, and 8 (10m) are used to map land cover by using an un-supervised K-means classification method. Different classes were defined and combined to five land cover types: water, vegetation, soil, moderate impervious surfaces (IS), and dense IS, as illustrated in Figure 4. This figure shows the high density of built-up areas in Alexandria, with less vegetated spaces within urban blocks, and areas of cultivated crops present in the northeast and southeastern parts of the city. We isolated the water surface land cover from further analysis and combined bare soil with vegetation land cover in a single class and gave it a rank of 1. Moderate IS land cover had a rank of 2; while, dense IS was ranked 3, as illustrated in Figure 5a. In turn, we used the extracted height values of the PS points in the PS-InSAR result of the ascending data to interpolate a digital surface model (DSM) for Alexandria, as a reference for relative building heights average in the study area. Since the extracted height in the PS-InSAR process is a relative height, heights were classified without considering the exact value of each PS point height. Five classes were extracted from very low to very high DSM by using the quantile method as presented in Figure 5b, and ranked from 1 to 5. The last step when producing the BL integrated the ranked land cover map with the ranked DSM to finalize the BL map presented in Figure 5c. The DSM ranks were double weighted before integration because building height affects subsidence much more land-cover classification. Figure 4: Land cover classification of S-2 image of 24 October 2018 presented on its true color image. As illustrated in Figure 5c, high BL is spatially distributed in the historical built-up area in the city center, in the Alagami neighborhood in southwest Alexandria, in the densely built-up areas in Abu-Qir, and around new buildings in the southern parts of the city. The BL map of the city was used in combination with maps of the rock type and FLL to determine the spatial correlation of each potential subsidence causality factor and the vertical motion in the area of interest.