# Characterizing Micro-Displacements on Active Faults in the Gobi Desert with Time-Series InSAR
## 4 Results and Discussion  
### The Patterns of Surface Deformation in the Jiujing Region  
Using the method outlined in Section 3, Figures 6 and 7 show the patterns of vertical (D\({}_{\rm U}\)) and eastward (D\({}_{\rm E}\)) displacements within the study area. The Sentinel-1 data were analysed in terms of potential structural phenomena. The measured deformations were interpreted and compared against independent priori data sources. Further potential explanations for apparent movements in InSAR data are discussed for the area as a whole in Section 4.4. Figure 5: The schematic illustrations of (**a**) normal fault and (**b**) reverse fault. According to the published literature, the faults in this region are considered to be inactive [21,23]. However, the PSI data show small but measurable movements along both known faults (such as F16-2, F17, F18, and F20-2) and on previously unmapped active faults (traced by blue lines in Figure 8 and presented in Table 2). The interpretation of unmapped faults is supported by discontinuities (which might be valleys, gullies, or cracks) on the surface of the granite, which are visible in Google Earth satellite imagery. The use of InSAR in this context may therefore provide a new method of characterising known faults and identifying previously unknown faults, thus enhancing the understanding of regional tectonic regimes and stress mechanisms. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Fault No.** & **Dipping Direction** & **Vertical Shearing Component** & **Lateral Shearing Component** \\ \hline F\({}_{\text{a}}\) & South & Reverse & Sinistral \\ F\({}_{\text{b}}\) & South & Reverse & Sinistral \\ F\({}_{\text{c}}\) & East & Normal & – \\ F\({}_{\text{g}}\) & Northeast & Reverse & Detral \\ F\({}_{\text{i+1}}\) & East & Reverse & – \\ F\({}_{\text{i-2}}\) & North & Reverse & Sinistral \\ F\({}_{\text{i+1}}\) & Southwest & Reverse & Detral \\ F\({}_{\text{m}}\) & East & Reverse & – \\ F\({}_{\text{n}}\) & East & Reverse & – \\ F\({}_{\text{o}}\) & East & Reverse & – \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The characteristics of newly identified active faults in Jiujing region. Figure 6: The pattern of vertical deformation (D\({}_{\text{U}}\)) in the Jiujing region, where the positive values (upper, red side of colour axis) refer to the uplift and negative values (blue, lower side of colour axis) refers to subsidence. Values in white text indicate movement rates with standard deviations in mm a\({}^{-1}\) and the full data are presented in Table S1 in Supplementary Materials. To better describe the deformation patterns, the Jiujing region has been divided into 30 blocks, labelled from JJ1 to JJ30 (Figures 6 and 7); based on the distribution of faults, their information and the vertical velocity normal distribution curves have been summarised and presented in Tables S1 and S2 and Figure S1 in Supplementary Materials. The time-series analyses conducted across several major blocks (blocks 3, 6, 7, 12, 19, and 21) presents the temporal variation of vertical displacement (shown in Figure 9a-f, and the original data is presented in Table S3 in Supplementary Materials). This is achieved through the averaging of the displacement values of 300 PS points within each block. The standard deviations of the datasets are represented by the error bars. Meanwhile, three cross-sections (AA', BB', and CC', Figure 6) were generated to show the spatial distribution of vertical displacement. It should be recognised that these results are estimated from a time series of around 2.5 years of SAR data acquisitions, and they represent continuous ground movement with consistent downward or upward trends over that time; thus, they are considered to be accurate enough to reflect the surface movement against time. The decorrelation noise and atmospheric artifacts are usually random; however, the time-series analysis in Figure 9a-f showed consistent trends of uplifting or subsiding.