# Space-Based Displacement Monitoring of Coastal Urban Areas: The Case of Limassol's Coastal Front
## 2 Materials and Methods
### Data Processing
#### 2.2.1 Satellite Data Processing  
Considering the novelty of the research due to the lack of previous investigations in urban areas of Cyprus and the fact that a significant number of buildings are in the planning or developmental stages, open data policies through multiple hubs, which involve the use of non-commercial satellite data, were chosen in order to guarantee the reusability of the current study approach on larger spatial and time scales. More specifically, Copernicus satellites' imagery data, particularly focusing on Sentinel-1 imagery data, were used. This satellite system provides free data with global coverage with a weekly revisit period [39; 40; 41]. In conjunction with short temporal baselines, the possibility of coherent phase information between the primary and secondary images increases, thus contributing to a potentially greater density of Persistent Scatterers (PS) for estimating deformation over time [42]. The processing and analyzing of Copernicus Sentinel-1 data, covering a time interval ranging from March 2016 to March 2021, were implemented by using the Sentinel Application \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Rank** & **Name** & **Height (m)** & **Floors** & **Construction Year** & **Location** & **Image** \\ \hline
8 & Dream Tower & 119 & 27 & 2023 &
\begin{tabular}{c} 33.11762\({}^{\circ}\) E \\ 34.70637\({}^{\circ}\) N \\ \end{tabular} & \\ \hline
9 & iHome & 56 & 11 & 2018 &
\begin{tabular}{c} 33.11431\({}^{\circ}\) E \\ 34.70687\({}^{\circ}\) N \\ \end{tabular} & \\ \hline
10 & The Icon & 104 & 21 & 2021 &
\begin{tabular}{c} 33.05059\({}^{\circ}\) E \\ 34.68385\({}^{\circ}\) N \\ \end{tabular} & \\ \hline
11 & MARR Tower & 116 & 24 & 2019 &
\begin{tabular}{c} 33.08530\({}^{\circ}\) E \\ 34.69408\({}^{\circ}\) N \\ \end{tabular} & \\ \hline
12 & DTA Tower & 100 & 22 & 2019 &
\begin{tabular}{c} 33.09071\({}^{\circ}\) E \\ 34.69755\({}^{\circ}\) N \\ \end{tabular} & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._Platform (SNAP), the Stanford Method for Persistent Scatterers (StaMPS/MTI) [43], and the'snap2 stamps' python workflow. StaMPS/MTI is a Sentinel-1 TOPS data PSI processing open-source software package that is demonstrated in automated mode. At the same time,'snap2 stamps' contains python scripts to automate the preprocessing of Sentinel-1 SLC data and their preparation for ingestion by StaMPS [44; 45; 46]. Forty-six Sentinel-1B advanced synthetic aperture radar images acquired by the European Space Agency from the satellite during descending acquisition mode from 2017 to 2021 were used to identify and calculate the deformation information, as presented in Table 3, functioning in C-band (5.4 GHz). It is noteworthy that the dataset follows a repeat sequence interval of almost 30 days between every image in order to avoid decorrelation in the temporal analysis of the baseline. This period was selected for two reasons: Firstly, most of the buildings' development started in late 2016, so the earlier study will be insufficient. Secondly, the benchmarks' network for leveling reasons was designed and implemented by the Laboratory of Geodesy of the Cyprus University of Technology throughout 2017. The Sentinel-1 dataset is composed of Single-Look Complex (SLC) images with Interferometric Wide (IW) mode, with similar characteristics, creating a time series sequence over the five-year period. The Interferometric Wide (IW) swath mode, applied in the present research, acquires data with a 250 km swath, with a high spatial resolution of 5 \(\times\) 20 m, and by using Terrain Observation with Progressive Scans SAR (TOPS), it captures one subswath in range direction [47]. Specifically, in the Sentinel-1 scenes observed by the 167 relative orbit number, the orbit passed over Limassol in descending acquisition mode. Moreover, according to [PERSON] et al.