The identification and early warning of potential landslides can effectively reduce the number of casualties and the amount of property loss. At present, interferometric synthetic aperture radar (InSAR) is considered one of the mainstream methods for the large-scale identification and detection of potential landslides, and it can obtain long-term time-series surface deformation data. However, the method of identifying anomalous deformation areas using InSAR data is still mainly manual delineation, which is time-consuming, labor-consuming, and has no generally accepted criterion. In this study, a two-stage detection deep learning network (InSARNet) is proposed and used to detect anomalous deformation areas in Maoxian County, Sichuan Province. Compared with the most commonly used detection models, it is demonstrated that the InSARNet has a better performance in the detection of anomalous deformation in mountainous areas, and all of the quantitative evaluation indexes are higher for InSARNet than for the other models. After the anomalous deformation areas are identified using the proposed model, the possible relationship between the anomalous deformation areas and potential landslides is investigated. Finally, the fact that the automatic and rapid identification of potential landslides is the inevitable trend of future development is discussed.

Carbon Capture, Utilization and Storage, also referred to as Carbon Capture, Utilization and Sequestration (CCUS), is one of the novel climate mitigation technologies by which CO₂ emissions are captured from sources, such as fossil power generation and industrial processes, and further either reused or stored with more attention being paid on the utilization of captured CO₂. In the whole CCUS process, the dominant migration pathway of CO₂ after being injected underground becomes very important information to judge the possible storage status as well as one of the essential references for evaluating possible environmental affects. Interferometric Synthetic Aperture Radar (InSAR) technology, with its advantages of extensive coverage in surface deformation monitoring and all-weather traceability of the injection processes, has become one of the promising technologies frequently adopted in worldwide CCUS projects. In this study, taking the CCUS sequestration area in Shizhuang Town, Shanxi Province, China, as an example, unmanned aerial vehicle (UAV) photography measurement technology with a 3D surface model at a resolution of 5.3 cm was applied to extract the high-resolution digital elevation model (DEM) of the study site in coordination with InSAR technology to more clearly display the results of surface deformation monitoring of the CO₂ injection area. A 2 km surface heaving dynamic processes before and after injection from June 2020 to July 2021 was obtained, and a CO₂ migration pathway northeastward was observed, which was rather consistent with the monitoring results by logging and micro-seismic studies. Additionally, an integrated monitoring scheme, which will be the trend of monitoring in the future, is proposed in the discussion.

Carbon neutrality is a goal the world is striving to achieve in the context of global warming. Carbon capture and storage (CCS) has received extensive attention as an effective method to reduce carbon dioxide (CO₂) in the atmosphere. What follows is the migration pathway and leakage monitoring after CO₂ injection. Interferometric synthetic aperture radar (InSAR) technology, with its advantages of extensive coverage in surface deformation monitoring and all-weather traceability of the injection processes, has become one of the promising technologies frequently adopted in worldwide CCS projects. However, there is no mature evaluation system to determine whether InSAR technology is suitable for each CO₂ sequestration area. In this study, a new evaluation model is proposed based on the eight factors that are selected from the principle of the InSAR technique and the unique characteristics of the CO₂ sequestration area. According to the proposed model, the feasibility of InSAR monitoring is evaluated for the existing typical sequestration areas in the world. Finally, the challenges and prospects of InSAR in the CCS project are discussed.

The premise of analyzing and researching robot technology is to establish a proper mathematical model and then to solve it with kinematics. In this study, a self-developed humanoid hydraulically driven dual-arm robot is taken as the research object, and the DH (Denavit–Hartenberg) parameter method and the rotational exponential formula (POE) are used to solve the kinematics of the robot. The calculation results are verified by simulation. The advantages and disadvantages of the two methods are analyzed. The differences between the two methods are compared. It lays a foundation for other scholars to choose mathematical models when analyzing the mechanism in the future.