Potential of Multi-temporal InSAR for Detecting Retrogressive Thaw Slumps: A Case of the Beiluhe Region of the Tibetan Plateau

Abstract Permafrost degradation due to climate warming is severely reducing slope stability by increasing soil pore water pressure and decreasing shear strength. Retrogressive thaw slumps (RTSs) are among the most dynamic landforms in permafrost areas, which can result in the instability of landscap...

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Bibliographic Details
Published in:International Journal of Disaster Risk Science
Main Authors: Zhiping Jiao, Zhida Xu, Rui Guo, Zhiwei Zhou, Liming Jiang
Format: Article in Journal/Newspaper
Language:English
Published: SpringerOpen 2023
Subjects:
Multi-temporal InSAR
Permafrost thawing
Qinghai-Tibet Plateau (QTP)
Retrogressive thaw slump
Disasters and engineering
TA495
Mati
permafrost
Online Access:https://doi.org/10.1007/s13753-023-00505-x
https://doaj.org/article/27e999e02f5d45e0aedc73a55482f11a
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Summary:Abstract Permafrost degradation due to climate warming is severely reducing slope stability by increasing soil pore water pressure and decreasing shear strength. Retrogressive thaw slumps (RTSs) are among the most dynamic landforms in permafrost areas, which can result in the instability of landscape and ecosystem. However, the spatiotemporal characteristics of surface deformation of RTSs are still unclear, and the potentials of deformation properties in mapping large-scale RTSs need to be further assessed. In this study, we applied a multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) method to map the spatiotemporal variations in surface deformation of RTSs in the Beiluhe region of the Tibetan Plateau by using 112 scenes of Sentinel-1 SAR data acquired from 2017 to 2021. The deformation rates of RTSs ranged from − 35 to 20 mm/year, and three typical motion stages were inferred by analyzing the deformation variation trend of the headwall of RTSs: stable, abrupt thaw, and linear subsidence. A total of 375 RTSs were identified in the Mati Hill region by combining InSAR-based deformation results with visual interpretation of optical remote sensing images. Among them, 76 RTSs were newly developed, and 26% more than the inventory derived from the optical images alone. This study demonstrated that the combination of InSAR-derived deformation with optical images has significant potential for detecting RTSs with high accuracy and efficiency at the regional scale.

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