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

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. [ABSTRACT FROM AUTHOR]