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Monitoring the Subsidence in Wan’an Town of Deyang Based on PS-InSAR Technology (Sichuan, China)

Author

Listed:
  • Hongyi Guo

    (Dpto. Geología, Faculty of Sciences, University of Salamanca, Plaza de la Caidos s/n, 37008 Salamanca, Spain)

  • Antonio Miguel Martínez-Graña

    (Dpto. Geología, Faculty of Sciences, University of Salamanca, Plaza de la Caidos s/n, 37008 Salamanca, Spain)

  • José Angel González-Delgado

    (Dpto. Geología, Faculty of Sciences, University of Salamanca, Plaza de la Caidos s/n, 37008 Salamanca, Spain)

Abstract

In recent years, land subsidence has become a crucial factor affecting urban safety and sustainable development, especially in Wan’an Town. To accurately monitor and analyze the land subsidence in Wan’an Town, this study uses the PS-InSAR technique combined with an improved DEM for detailed research on land subsidence in Wan’an Town. PS-InSAR, or Permanent Scatterer Interferometric SAR, is suitable for high-precision monitoring of surface deformation. The natural neighbor interpolation method optimizes DEM data, improving its spatial resolution and accuracy. In this study, multiple periods of SAR imagery data of Wan’an Town were collected and preprocessed through radiometric calibration, phase unwrapping, and other steps. Using the PS-InSAR technique, the phase information of permanent scatterers (PS points) on the surface was extracted to establish a deformation model and preliminarily analyze the land subsidence in Wan’an Town. Concurrently, the DEM data were optimized using the natural neighbor interpolation method to enhance its accuracy. Finally, the optimized DEM data were combined with the surface deformation information extracted through the PS-InSAR technique for a detailed analysis of the land subsidence in Wan’an Town. The research results indicate that the DEM data optimized by the natural neighbor interpolation method have higher accuracy and spatial resolution, providing a more accurate reflection of the topographical features of Wan’an Town. The research found that the optimized DEM provided a more accurate reflection of Wan’an Town’s topographical features. By combining PS-InSAR data, subsidence information from 2016 to 2024 was calculated. The study area showed varying degrees of subsidence, with rates ranging from 6 mm/year to 10 mm/year. Four characteristic deformation areas were analyzed for causes and influencing factors. The findings contribute to understanding urban land subsidence, guiding urban planning, and providing data support for geological disaster warning and prevention.

Suggested Citation

  • Hongyi Guo & Antonio Miguel Martínez-Graña & José Angel González-Delgado, 2024. "Monitoring the Subsidence in Wan’an Town of Deyang Based on PS-InSAR Technology (Sichuan, China)," Sustainability, MDPI, vol. 16(22), pages 1-22, November.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:10010-:d:1522515
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    References listed on IDEAS

    as
    1. Doan Quang Tri & Nguyen Van Nhat & Quach Thi Thanh Tuyet & Ha T. T. Pham & Pham Tien Duc & Nguyen Thanh Thuy, 2024. "Applying an Analytic Hierarchy Process and a Geographic Information System for Assessment of Land Subsidence Risk Due to Drought: A Case Study in Ca Mau Peninsula, Vietnam," Sustainability, MDPI, vol. 16(7), pages 1-23, March.
    2. Salman Ahmadi & Reza Soodmand Afshar & Mohammad Fathollahy & Kamran Nobakht Vakili, 2023. "Identification of land subsidence hazard in asadabad plain using the PS-InSAR method and its relationship with the geological characteristics," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(1), pages 1157-1178, May.
    3. Shuai Jiao & Xiaojuan Li & Jie Yu & Mingyuan Lyu & Ke Zhang & Yuehui Li & Pengyuan Shi, 2024. "Multi-Scale Analysis of Surface Building Density and Land Subsidence Using a Combination of Wavelet Transform and Spatial Autocorrelation in the Plains of Beijing," Sustainability, MDPI, vol. 16(7), pages 1-23, March.
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