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ORIGINAL RESEARCH article

Front. Earth Sci.
Sec. Geohazards and Georisks
Volume 13 - 2025 | doi: 10.3389/feart.2025.1531615

Latent landslide hazard recognition in Fang County using synthetic aperture radar interferometry and geological data

Provisionally accepted
  • Nanyang Normal University, Nanyang, China

The final, formatted version of the article will be published soon.

    The northwest part of Hubei Province, China, is characterized by steep topography, complex geological structures, and intense precipitation, providing ideal natural conditions for landslide disasters. To address the lack of integration of synthetic aperture radar interferometry (InSAR) and geological data for the identification of latent landslide hazards, in this study, we incorporated InSAR technology and geological data to identify potential landslides in Fang County, northwest Hubei Province. With the aid of 10 ALOS-2 data scenes and high-precision digital elevation models of the study area, a displacement rate map with a maximum value of -70.6 mm/a was extracted. Then, according to the displacement rate and optical images, the suspected latent landslide area was delineated, and a comprehensive analysis of the slope map and fault and watershed buffer zone map was performed to obtain the final results. Compared to the existing latent landslide recognition method, the proposed method integrating InSAR and geological data can eliminate areas where landslides are geologically unlikely to occur, thereby enhancing the efficiency and accuracy of latent landslide hazard identification. The results were verified using geological and optical image features, which confirmed its effectiveness for identifying latent landslide hazards. The results of this research can contribute to the prediction and early warning of landslides and guide field investigations of geological disasters.

    Keywords: landslide, InSAR, Geological data, Hazard recognition, Fang County

    Received: 21 Nov 2024; Accepted: 02 Jan 2025.

    Copyright: © 2025 Wang, Fan and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Shunyao Wang, Nanyang Normal University, Nanyang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.