A study on the monitoring of landslide deformation disasters in Wenxian County, Longnan City based on different time-series InSAR techniques

Jinlong Zhang, Rui Yang, Yuan Qi, Hui Zhang, Juan Zhang, Qianhong Guo, Chao Ma and Hongwei Wang ()
Additional contact information
Jinlong Zhang: Chinese Academy of Sciences
Rui Yang: Chinese Academy of Sciences
Yuan Qi: Chinese Academy of Sciences
Hui Zhang: Chinese Academy of Sciences
Juan Zhang: Chinese Academy of Sciences
Qianhong Guo: Bureau of Natural Resources of Zhuoni
Chao Ma: Chinese Academy of Sciences
Hongwei Wang: Chinese Academy of Sciences

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 13, No 14, 11875 pages

Abstract: Abstract Interferometry Synthetic Aperture Radar (InSAR) technology is widely employed in the identification of geological hazards. However, in regions characterized by high mountains, canyons, and dense vegetation, decorrelation often hampers effective identification. In this study, focusing on the landslide-prone area of Wenxian County in Longnan City with abundant vegetation, we propose a Multi-Temporal InSAR (MTI) monitoring method that integrates Persistent Scatterers (PS) points with Slowly-Decorrelating Filtered Phase (SDFP) points in order to effectively reduce decorrelation effects. Additionally, we conduct high-precision monitoring of landslide surface deformation in Wenxian County using the the Generic Atmospheric Correction Online Service for InSAR (GACOS). Based on cross-validation of results obtained from three different techniques and the comparison with GNSS monitoring results, we validate the accuracy of these identification results. Furthermore, we use time-series deformation analysis methods to analyze the dynamic evolution of the characteristics of landslides in Chengguan Town and Koutouba Township, Wenxian County, Longnan City, and investigate their relationship with different environmental factors, such as rainfall and temperature. Our findings demonstrate that the spatial distribution consistency of the surface deformation information identified by the three techniques is high. However, StaMPS-MTI technology has the highest spatial sampling rate in deformation results, which is 21.02% higher than that of StaMPS-PS and over 4.6 times higher than that of StaMPS-SBAS. Additionally, the errors and Root Mean Square Error (RMSE) of StaMPS-MTI results in comparison to GNSS monitoring results are also the smallest, with values of 5.35 mm and 9.38 mm. We also observe varying degrees of deformation in Level 1 landslide areas identified by the STAMPS-MTI method in Chengguan Town and Koutouba Township with distinct seasonal characteristics. The cumulative deformation in the period from March to June shows a noticeable acceleration, with landslide incidents caused by the freeze-thaw phenomenon due to rising temperatures in March and April while rainfall caused landslide incidents from April to June. This research provides essential data and scientific support for geological hazard monitoring, prevention, and early warning.

Keywords: Geological hazards; Sentinel-1A; Time-series InSAR; Deformation monitoring; Longnan City (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11069-024-06663-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:120:y:2024:i:13:d:10.1007_s11069-024-06663-5

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-024-06663-5

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().