Advances in Remote Sensing Technology for Ground Deformation

Dear Colleagues,

(1) Introduction, including scientific background and highlighting the importance of this research area.

Remote sensing provides an efficient, wide-area, and non-contact means to monitor ground deformation caused by natural or anthropogenic processes such as earthquakes, landslides, volcanic activity, land subsidence, and mining. Techniques like Interferometric Synthetic Aperture Radar (InSAR) allow for the detection of ground displacement with centimeter- to millimeter-scale accuracy by comparing radar images acquired at different times. Optical and LiDAR data further support the mapping of surface changes, fault ruptures, or slope instabilities through 3D modeling and time-series analysis. Satellite missions such as Sentinel-1, ALOS-2, and TerraSAR-X enable continuous, global deformation monitoring, while UAV-based and ground-based sensors provide detailed local observations.

(2) Aim of the Special Issue and how the subject relates to the journal scope.

Integration of GNSS, InSAR, and optical data improves spatial and temporal resolution, offering insights into deformation mechanisms and hazard assessment. These methods are critical for early warning, infrastructure protection, and geohazard management. By combining remote sensing with machine learning and cloud processing, it is now possible to automate deformation detection and forecast trends over large regions. Overall, remote sensing has revolutionized geoscience monitoring by providing a cost-effective, repeatable, and scalable approach to understanding Earth’s dynamic surface processes.

(3) Suggested themes and article types for submissions.

1. Special processes to handle the remote sensing data for ground deformation;
2. Combine multi-source remote sensing data to analyze information about ground deformation;
3. New technologies to reveal high accuracy or resolution for ground deformation via remote sensing;
4. AI approaches to improve efficiency for ground deformation detecting via remote sensing;
5. Articles about theorical development, case studies or technical improvement regarding to this topic are welcome.

Prof. Dr. Teng-To Yu
Guest Editor

Manuscript Submission Information

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