Monitoring and analysis of surface deformation in alpine valley areas based on multidimensional InSAR technology

Abstract

Joshimath has received much attention for its massive ground subsidence at the beginning of the year. Rapid urbanization and its unique geographical location may have been one of the factors contributing to the occurrence of this geological disaster. In high mountain valley areas, the complex occurrence mechanism and diverse disaster patterns of geological hazards highlight the inadequacy of manual monitoring. To address this problem, the inversion of deformation of the Joshimath surface in multiple directions can be achieved by multidimensional InSAR techniques. Therefore, in this paper, the multidimensional SBAS-InSAR technique was used to process the lift-track Sentinel-1 data from 2020 to 2023 to obtain the two-dimensional vertical and horizontal deformation rates and time series characteristics of the Joshimath ground surface. To discover the causes of deformation and its correlation with anthropogenic activities and natural disasters by analyzing the spatial and temporal evolution of surface deformation. The results show that the area with the largest cumulative deformation is located in the northeastern part of the town, with a maximum cumulative subsidence of 271.2 mm and a cumulative horizontal movement of 336.5 mm. The spatial distribution of surface deformation is based on the lower part of the hill and develops towards the upper part of the hill, showing a trend of expansion from the bottom to the top. The temporal evolution is divided into two phases: gentle to rapid, and it is tentatively concluded that the decisive factor that caused the significant change in the rate of surface deformation and the early onset of the geological subsidence hazard was triggered by the 4.7 magnitude earthquake that struck near the town on 11 September 2021.

Geodetic Evidence for Cascading Landslide Motion Triggered by Extreme Rain Events at Joshimath, NW Himalaya

“…Second, localized deformation zones with dimensions <12 m as observed in the field are beyond the InSAR resolution limit (30 m). Similar to our results, Yang et al (2023) also did not observe notable change in the InSAR time-series during November 2022 and January 2023. Conversely, Shankar et al (2023) showed comparable results between GPS and Sentinel-1 InSAR (descending) observations.…”

“…Our analysis reveals that the episodic accelerations of the Joshimath landslide are triggered by extreme rain events. However, Yang et al (2023) suggested that the 4.7 magnitude earthquake that occurred on 11 September We note that the reported earthquake epicenter is about 28 km away from the Joshimath town and there are no significant earthquakes (M > 5) within 30 km for the past 20 years that correlate with the previous episodes of landslide acceleration (Figures 2c and 3d and Figure S1a in Supporting Information S1). Hence, it is difficult to reconcile the role of earthquakes in the mobility of Joshimath landslide.…”

“…However, Yang et al. (2023) suggested that the 4.7 magnitude earthquake that occurred on 11 September 2021 could have triggered the landslide acceleration since December 2021. We note that the reported earthquake epicenter is about 28 km away from the Joshimath town and there are no significant earthquakes ( M > 5) within 30 km for the past 20 years that correlate with the previous episodes of landslide acceleration (Figures 2c and 3d and Figure S1a in Supporting Information ).…”

Deformation monitoring around dam and reservoir in Indian Himalayas using SBAS-InSAR method

“…Also, we have validated two landslide sites L-1 and L-2 (Figure ), with GoogleEarth Pro. The observed deformation rate in both orbits can vary due to sensor Line of Sight (LOS), topography of the terrain and incidence angle of orbit's acquisition geometry [18].…”

Analysis and Prediction of Temporal and Spatial Evolution of Groundwater Storage by Combined SAR-GRACE Satellite Data

“…Taiyuan City and Yuncheng City, which have large annual change rates of GWS, were selected as the key areas for extracting surface deformation features, and the SAR images covering Taiyuan City and Yuncheng City were pre-processed and decoded respectively. To obtain interferometric pairs with higher coherence, the maximum temporal baseline was set to 150 and 100 days, respectively, and the maximum spatial baseline to 10% of the critical baseline [48], [49]. The spatial baseline connectivity of the image pairs is shown in Figure 11, where the X-axis represents the date, the Y-axis represents the baseline distance between the two view images, and the red and green dots represent the distribution of the primary and secondary images on the time series, respectively.…”