# Quaternary Activity and Paleoearthquakes of the Fushan Fault, Shanxi, China
## 2 Materials and Methods  
### Remote Sensing Data Acquisition  
The Fushan Fault is located in the southeastern part of Fushan County, an area characterized by complex terrain and difficult access. In this study, we selected UAV technology owing to its significant advantage in rapidly obtaining high-resolution images in complex terrain areas. UAV survey technology involves the integration of drones with remote sensing technology, including various sensors, advanced unmanned flight technology, remote control techniques, and digital photogrammetry. This technology enables the efficient and convenient acquisition of ground images and remote sensing data, serving as a powerful supplement to traditional aerial photogrammetry and field survey methods. It is character ized by its mobility, flexibility, high efficiency, precision, low cost, and wide applicability. A typical drone aerial survey system consists of three main components: the drone aircraft, imaging system, and data processing system.  
For this investigation, a DJI Phantom 4 Pro quadcopter (DJI, Shenzhen, China) UAV equipped with a 20-megapixel digital camera was used to collect aerial survey data from multiple geomorphic sites along the Fushan Fault. Considering the specific conditions of the Fushan Fault, five ground control points were established (Figure 3; Table 1). The flight altitude was set at 350 m, with a forward overlap rate of 50-70% and a side overlap rate of no less than 25%. A total of 4675 valid aerial photographs of the Fushan Fault were obtained, with an image resolution of up to 0.5 m in the study area. Post-processing of image data was performed using the Agisoft PhotoScan 1.2.6 software, including aligning photographs, generating dense point clouds, creating meshes, and applying textures. This process resulted in the creation of a Digital Elevation Model (DEM) and Digital Orthophoto Map (DOM), which accurately reflected the terrain and geomorphology of the Fushan Fault.  
Next, we obtained satellite remote sensing images of GF1-PMS1 and GF1-PMS2. After geometric correction, orthorectification, and image fusion, the satellite images were combined with the contour data generated from the DEM, and the geometric shape of the Fushan Fault was ultimately determined by comparing textural and tonal variations in the images. The location of the Fushan Fault was clearly delineated, with distinct fault landforms, good continuity, and no branching faults (Figure 4).  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Ground Control Points** & **Flight Altitude** & **Number of Photographs** \\ \hline
1. Baozishang village & 350 & 850 \\
2. Lijia’an village & 350 & 811 \\
3. Huaijiyuan village & 350 & 1066 \\
4. Chejiazhuang village & 350 & 756 \\
5. Yaoxiang Mountain village & 350 & 1192 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Unmanned aerial vehicle survey data for the Fushan Fault.  
Figure 3: (**a**) Structural characteristics of the Fushan Fault area and locations of unmanned aerial vehicle (UAV) survey control points, exploration trenches, and bedrock surfaces. The black border in the figure (**a**) represents the range of (**b**).