Article: Research on emergency monitoring methods for landslide disasters based on improved atmospheric correction GB-SAR and multi-source data geocoding Journal: International Journal of Environment and Pollution (IJEP) 2026 Vol.76 No.1/2 pp.57 - 73 Abstract: Ground-based synthetic aperture radar (GB-SAR) has become a key technical equipment in the field of geological disaster prevention. Existing monitoring methods have limitations: contact sensors offer limited coverage, while optical remote sensing struggles in adverse weather. This study presents an integrated remote sensing system combining improved GB-SAR, terrestrial laser scanning (TLS), and unmanned aerial vehicles (UAVs) for emergency monitoring. Innovations include an atmospheric correction model accounting for range, elevation, and azimuth angles, and a point cloud filtering method enhancing Permanent Scatterer selection. These reduce GB-SAR monitoring errors by 30%. A multi-source fusion framework integrates TLS's high-resolution 3D modelling and UAVs' rapid imaging for dynamic deformation analysis. The system enables fast risk area identification within 72 h to support emergency decisions. Experiments validate the improved GB-SAR's accuracy and the fusion strategy's effectiveness in landslide scenarios, offering a robust solution for real-time hazard assessment and mitigation. Inderscience Publishers - linking academia, business and industry through research

Title: Research on emergency monitoring methods for landslide disasters based on improved atmospheric correction GB-SAR and multi-source data geocoding

Authors: Hao Zhang; Xiaolin Yang; Xiangtian Zheng; Zhenan Yin; Guiwen Ren; Shanshan Hou

Addresses: China Academy of Safety Science and Technology, Beijing, 100012, China ' China Academy of Safety Science and Technology, Beijing, 100012, China ' Nanjing Institute of Technology, School of Computer Engineering, Nanjing, 211167, China ' Nanjing Institute of Technology, School of Computer Engineering, Nanjing, 211167, China ' Cathay Safety Technology Co., Ltd., Beijing, 102209, China ' Cathay Safety Technology Co., Ltd., Beijing, 102209, China

Abstract: Ground-based synthetic aperture radar (GB-SAR) has become a key technical equipment in the field of geological disaster prevention. Existing monitoring methods have limitations: contact sensors offer limited coverage, while optical remote sensing struggles in adverse weather. This study presents an integrated remote sensing system combining improved GB-SAR, terrestrial laser scanning (TLS), and unmanned aerial vehicles (UAVs) for emergency monitoring. Innovations include an atmospheric correction model accounting for range, elevation, and azimuth angles, and a point cloud filtering method enhancing Permanent Scatterer selection. These reduce GB-SAR monitoring errors by 30%. A multi-source fusion framework integrates TLS's high-resolution 3D modelling and UAVs' rapid imaging for dynamic deformation analysis. The system enables fast risk area identification within 72 h to support emergency decisions. Experiments validate the improved GB-SAR's accuracy and the fusion strategy's effectiveness in landslide scenarios, offering a robust solution for real-time hazard assessment and mitigation.

Keywords: landslide monitoring; GB-SAR; ground-based synthetic aperture radar; TLS; terrestrial laser scanning; UAVs; unmanned aerial vehicles.

DOI: 10.1504/IJEP.2026.151760

International Journal of Environment and Pollution, 2026 Vol.76 No.1/2, pp.57 - 73

Received: 31 Mar 2025
Accepted: 21 Jul 2025
Published online: 18 Feb 2026 *

Title: Research on emergency monitoring methods for landslide disasters based on improved atmospheric correction GB-SAR and multi-source data geocoding

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