The characteristics of earthquake surface ruptures, such as geometry, slip distribution, and coseismic deformation, contain important information about the earthquake rupture process, and so investigations and analyses of earthquake surface rupture have played a crucial role in modern earthquake hazard studies, especially with the increasing availability of high-resolution topographic and imagery data for tectono-geomorphic interpretation. In this study, we use Structure from Motion (SfM) photogrammetry to build a 1 m resolution digital elevation model (DEM) of the fault and combine this with filed observations to map the surface ruptures of the 1931 M8.0 Fuyun earthquake, China. These high-resolution topographic data enable to identify and measure the displaced gullies, and so the rupture locations and along-strike slip distribution are obtained in detail. Four paleoearthquake events are identified through the offset cluster characteristics. The coseismic offset of the 1931 Fuyun earthquake is extracted from the offset distribution, which shows four continuous undulations along the fault strike, corresponding to the four segments of surface rupture. Moreover, a high offset gradient is observed in the step area connected by the rupture segment. These findings, combined with the width and bending angle of the step area at the joint of the rupture segment, indicate that the 1931 Fuyun earthquake was a cascade rupture formed by four rupture segments. This study expands the available offset measurement data of Fuyun fault and confirms the applicability of high-resolution topographic data to active tectonic research.

The objective of this article was to apply supervised classification to accomplish automated landform mapping using four morphometric parameters. The approach was tested on high-resolution light detection and ranging (lidar) elevation data from the northern flank of the Dushanzi Anticline, western China. The morphometric parameters were calculated by applying a moving window to the lidar-derived digital elevation models (DEMs). The results obtained from using the Jeffries–Matusita distance and standard deviation ellipses for the training areas show that the main landforms in the study area can be distinguished using the four morphometric parameters. Compared with field surveying and image interpretation, the automated landform classification technique has advantages in terms of its efficiency and reproducibility, and it is capable of accurately reconstructing a detailed geomorphological map covering the study area with a classification accuracy of 72.9% and a kappa coefficient (κ) of 0.66. The geomorphological map derived using the automated classification approach revealed an obvious east–west zone composed of alluvial landforms. The close spatial relationship between this zone and mapped thrust faults indicates that this east–west zone represents a belt of seismic risks associated with the thrust faults, which should be avoided in major engineering projects. Due to its accuracy and efficacy, an automated landform classification has considerable prospects for its application in geomorphological mapping and landform characterization studies in the future, especially given the increasing availability of high-resolution digital terrain data.

High-resolution topographic data are fundamental for active tectonics studies. Within the last 2 decades, the airborne light detection and ranging (LiDAR) system provided a solution for the accurate and efficient acquisition of detailed geomorphic features. The use of LiDAR data for the identification of microstructural and geomorphic features, fault zone activity analysis, and earthquake disaster assessment remains challenging and has been the focus of active tectonics studies. Based on the LiDAR data of Dushanzi anticline–a reverse fault zone in Xinjiang, China, our group carried out a significant number of active tectonic research studies. By reviewing the specific content of these works, we summarized the main application of LiDAR for a specific structure, the Dushanzi Reverse Fault in the northern Tianshan. In addition, other applications of LiDAR in active tectonics are summarized in this paper. These studies show that high-resolution LiDAR data facilitate detailed studies of the fault activity and paleoseismicity. We hope more researchers can realize the advantages of LiDAR technology in active tectonics research and apply LiDAR technology into their own practical work, so as to promote the development of active tectonics research.

The complexity of strike-slip fault segmentation affects the initiation, propagation, and termination of earthquake ruptures and the earthquake magnitude. Studying the fault geometry, kinematics, and segmentation provides fundamental knowledge for mitigating earthquake hazards along faults. The Zemuhe, Daliangshan, and Xiaojiang Faults intersect along the eastern boundary of the Tibetan Plateau in the area from Ningnan in Sichuan Province to Qiaojia in Yunnan Province. Although few large earthquakes have occurred on these faults, the relationships between the intersections of these three faults and earthquake rupture behavior in this region are poorly constrained. The interpretation of aerial photographs and detailed field surveys revealed the geometric pattern and fault kinematics in the area of intersection. The distribution patterns and focal depths near the faults were obtained via analysis of seismic data in the area of intersection. The northern segment of the Xiaojiang Fault deviates approximately 25° northwest of Qiaojia, forming a conspicuous bend. The Xiaojiang Fault continues to extend southeast of the Ningnan Basin, where it intersects with the southern segment of the Zemuhe Fault, forming a pull-apart basin approximately 4.5 km wide. The bend and Ningnan pull-apart basin mark the segmented boundary between the Zemuhe Fault and the Xiaojiang Fault, which may prevent the propagation of large earthquake ruptures along the eastern boundary fault. Moreover, the lack of obvious geometric complexity between the Daliangshan Fault and Xiaojiang Fault might hinder the prevention of earthquake rupture propagation. Additionally, our results suggest that different earthquake prevention and disaster reduction measures should be taken for different cities in the region.

The precise characterization of surface rupture zones and associated co-seismic displacement fields from large earthquakes provides critical insights into seismic rupture mechanisms, earthquake dynamics, and hazard assessments. Stereo-photogrammetric digital elevation models (DEMs), produced from high-resolution satellite stereo imagery, offer reliable global datasets that are suitable for the detailed extraction and quantification of vertical co-seismic displacements. In this study, we utilized pre- and post-event WorldView-2 stereo images of the 2024 Ms7.1 Wushi earthquake in Xinjiang to generate DEMs with a spatial resolution of 0.5 m and corresponding terrain point clouds with an average density of approximately 4 points/m². Subsequently, we applied the Iterative Closest Point (ICP) algorithm to perform differencing analysis on these datasets. Special care was taken to reduce influences from terrain changes such as vegetation growth and anthropogenic structures. Ultimately, by maintaining sufficient spatial detail, we obtained a three-dimensional co-seismic displacement field with a resolution of 15 m within grid cells measuring 30 m near the fault trace. The results indicate a clear vertical displacement distribution pattern along the causative sinistral–thrust fault, exhibiting alternating uplift and subsidence zones that follow a characteristic “high-in-center and low-at-ends” profile, along with localized peak displacement clusters. Vertical displacements range from approximately 0.2 to 1.4 m, with a maximum displacement of ~1.46 m located in the piedmont region north of the Qialemati River, near the transition between alluvial fan deposits and bedrock. Horizontal displacement components in the east-west and north-south directions are negligible, consistent with focal mechanism solutions and surface rupture observations from field investigations. The successful extraction of this high-resolution vertical displacement field validates the efficacy of satellite-based high-resolution stereo-imaging methods for overcoming the limitations of GNSS and InSAR techniques in characterizing near-field surface displacements associated with earthquake ruptures. Moreover, this dataset provides robust constraints for investigating fault-slip mechanisms within near-surface geological contexts.

The Daliangshan Fault Zone is an important branch fault of the Xianshuihe-Xiaojiang Fault System, which is the eastern boundary of the Sichuan-Yunnan Rhombic Block. It plays a great role in understanding the tectonic activity in the southeast margin of the Qinghai-Tibet Plateau. In this paper, three left-lateral strike-slip faults in the middle and southern segments of the Daliangshan Fault Zone, including Puxiong Fault, Butuo Fault, and Jiaojihe Fault, are taken as the research objects. And high-precision topographic data with a resolution of 0.5 m is obtained by using UAV photography combined with SfM technology. Based on these data, the fault geomorphologic markers are interpreted and 517 left-lateral displacement values are measured along the 160-km-long middle and southern segments of the Daliangshan Fault Zone. By analyzing the displacement distribution, it is concluded that the three faults in the middle and southern segments of the Daliangshan Fault Zone share a relatively similar rupturing behavior. There have been at least three surface-rupturing earthquake events in the middle and southern segments of the Daliangshan Fault Zone, which is in good agreement with the results of previous paleo-seismic trenching researches. According to the paleo-seismic trenching researches, the latest surface-rupturing earthquake event is a cascading rupture, with an average co-seismic displacement of about 3.7 m; Combined with the empirical formulas, the estimated magnitude for a complete rupture of the middle and southern segments of the Daliangshan Fault Zone ranges from Mw 7.4 to Mw 7.7.