Chengyan Fan is a Postdoctoral Fellow of Department of Earth and Environmental Sciences at The Chinese University of Hong Kong. Chengyan obtained his Bachelor, Master, and Ph.D. degrees from Lanzhou University in 2018, 2020, and 2025, respectively, and participated in a joint training and collaborative research program with CUHK. During his Ph.D. study, he used InSAR technology to comprehensively study permafrost dynamics, ground ice.
InSAR is an effective tool for indirectly monitoring large-scale hydrological-thermal dynamics of the active layer and permafrost by detecting the surface deformation. However, the conventional time-series models of InSAR technology do not consider the distinctive and pronounced seasonal characteristics of deformation over permafrost. Although permafrost-tailored models have been developed, their performance relative to the conventional models has not been assessed. In this study, we modify sinusoidal function and Stefan-equation-based models (permafrost-tailored) to better characterize surface deformation over permafrost, and assess advantages and limitations of these models for three application scenarios: filling time-series gaps for Small Baseline Subset (SBAS) inversion, deriving velocity and amplitude of deformation and selecting reference points automatically. The HyP3 interferograms generated from Sentinel-1 are utilized to analyze the surface deformation of the permafrost region over the upper reaches of the Heihe River Basin from 2017 to 2023. The result shows that adding a semi-annual component to the sinusoidal function can better capture the characteristics of ground surface deformation in permafrost regions. The modified Stefan-equation-based model performs well in those application scenarios, but it is only recommended for complex scenarios that conventional mathematical models cannot handle or for detailed simulations at individual points due to sophisticated data preparation and high computational cost. Furthermore, we find reference points can introduce substantial uncertainties into the deformation velocity and amplitude measurements, in comparison to the uncertainties derived from interferograms alone. The analysis of deformation amplitude and inter-annual velocity reveals that an ice-rich permafrost region, exhibiting a seasonal amplitude of 50–130 mm, is experiencing rapid degradation characterized by a subsidence velocity ranging from −10 to −20 mm/yr. Our study gives a permafrost-tailored modification and quantitative assessment on the InSAR time-series models. It can also serve as a reference and promotion for the application of InSAR technology in future permafrost research. The dataset and code are available at https://github.com/Fanchengyan/FanInSAR.
JGR Earth Surface
Pronounced underestimation of surface deformation due to unwrapping errors over Tibetan Plateau permafrost by Sentinel-1 InSAR: Identification and correctio
Chengyan Fan, Lin Liu, Zhuoyi Zhao, and Cuicui Mu
Journal of Geophysical Research: Earth Surface, Mar 2025
Surface deformation plays an important role in permafrost studies as it is closely associated with the hydrological-thermal dynamics of the active layer and permafrost, affecting the stability of infrastructure. In this study, we have identified a significant underestimation of surface deformation over permafrost using Sentinel-1 InSAR, which is attributed to unwrapping errors in interferograms. Specifically, the inclusion of interferograms with longer temporal baselines in the SBAS network will cause unwrapping errors to occur more frequently and severely, leading to a more pronounced underestimation, exceeding 3 times in severe cases. To address this issue, we propose a novel correction strategy to mitigate unwrapping errors by correcting long-span interferograms with reliable short-span interferograms in the temporal domain. Here, 12-day interferograms are utilized as the reliable interferograms for the correction. The results show that the seasonal deformation amplitude over an ice-rich permafrost location on the Tibetan Plateau increases to approximately 110 mm after applying the correction, compared to the previous underestimation of only about 28 mm. The proposed correction method facilitates accurate retrieval and verification permafrost products from InSAR time series, such as the ground ice/water storage and thickness of the active layer. This in turn deepens our understanding of surface deformation in permafrost regions under a warming climate. Moreover, the proposed correction method demonstrates its promise as an effective strategy for mitigating underestimation issues in various InSAR studies that suffer from unwrapping errors.
JAG
Unveiling large-scale velocity characteristics of rock glaciers in the Tibet-Pamir-Karakoram region using InSAR
Zhangyu Sun, Lin Liu, Chengyan Fan, Yan Hu, and 4 more authors
International Journal of Applied Earth Observation and Geoinformation, Aug 2025
Rock glaciers are debris landforms formed by long-term creep of ice-rich permafrost. Their kinematics provide critical insights for climate change and permafrost studies, mountain hydrology, and hazard assessment. Previous studies have measured rock glacier velocities using field-based terrestrial geodetic surveys, repeat photogrammetry, and Interferometric Synthetic Aperture Radar (InSAR). However, these methods have typically been confined to local regions, leaving the large-scale velocity characteristics underexplored. In this study, we developed a multi-temporal and multi-geometry InSAR framework for systematically generating rock glacier velocity fields. We rigorously validated our approach by comparing the InSAR-derived velocities with those derived from very-high-resolution optical imagery (Pléiades satellite imagery and aerial imagery) and Global Navigation Satellite System (GNSS) measurements. The mean relative difference is approximately 20 % when compared to velocities from Pléiades and aerial images, increasing to 50 % for GNSS point measurements. Applying our method, we produced the first large-scale regional rock glacier velocity dataset, encompassing downslope velocity fields for 19,727 previously inventoried rock glaciers in the Tibet-Pamir-Karakoram region. We found a velocity contrast between different climatic domains: rock glaciers in the westerlies domain move on average faster (median = 30 cm/yr) than those in the monsoon domain (median = 13 cm/yr). Our study presents a methodological framework for assessing rock glacier velocities using InSAR and demonstrates its capability for large-scale applications. This approach can be readily adapted to other regions worldwide to support the assessment and monitoring of rock glacier dynamics in a changing climate.
2024
GRL
Widespread and rapid activities of retrogressive thaw slumps on the Qinghai-Tibet Plateau from 2016 to 2022
Zhuoxuan Xia, Lin Liu, Cuicui Mu, Xiaoqing Peng, and 4 more authors
Retrogressive thaw slumps (RTSs), formed by abrupt degradation of ice-rich permafrost, are widely distributed on the Qinghai-Tibet Plateau, causing infrastructure damage and enhancing soil carbon emissions. We compiled annual RTS inventories across the plateau from 2016 to 2022 using a deep-learning-aided method to quantify the spatial-temporal variations. We found that RTS-affected locations increased from 1,592 to 3,805 in 2016–2022, which increased affected areas by 2.8 times from 1,714 to 6,507 ha. The most active initiation and expansion periods were in 2016–2017 and 2018–2019. RTSs tend to be clustered, showing local heterogeneity among clusters characterized by various responses toward high temperatures and precipitation and tendencies to be on different topography and vegetation types. This research reveals the rapid development, wide distribution and regional heterogeneity of RTS activities, serving as a crucial step toward understanding how RTSs respond to climate change and regional environmental varieties.
2022
ESSD
Retrogressive thaw slumps along the Qinghai–Tibet Engineering Corridor: a comprehensive inventory and their distribution characteristics
Zhuoxuan Xia, Lingcao Huang, Chengyan Fan, Shichao Jia, and 5 more authors
The important Qinghai–Tibet Engineering Corridor (QTEC) covers the part of the Highway and Railway underlain by permafrost. The permafrost on the QTEC is sensitive to climate warming and human disturbance and suffers accelerating degradation. Retrogressive thaw slumps (RTSs) are slope failures due to the thawing of ice-rich permafrost. They typically retreat and expand at high rates, damaging infrastructure, and releasing carbon preserved in frozen ground. Along the critical and essential corridor, RTSs are commonly distributed but remain poorly investigated. To compile the first comprehensive inventory of RTSs, this study uses an iteratively semi-automatic method built on deep learning to delineate thaw slumps in the 2019 PlanetScope CubeSat images over a ∼ 54 000 km2 corridor area. The method effectively assesses every image pixel using DeepLabv3+ with limited training samples and manually inspects the deep-learning-identified thaw slumps based on their geomorphic features and temporal changes. The inventory includes 875 RTSs, of which 474 are clustered in the Beiluhe region, and 38 are near roads or railway lines. The dataset is available at https://doi.org/10.5281/zenodo.6397029 (Xia et al., 2021a), with the Chinese version at DOI: https://doi.org/10.11888/Cryos.tpdc.272672 (Xia et al. 2021b). These RTSs tend to be located on north-facing slopes with gradients of 1.2–18.1∘ and distributed at medium elevations ranging from 4511 to 5212 m a.s.l. They prefer to develop on land receiving relatively low annual solar radiation (from 2900 to 3200 kWh m−2), alpine meadow covered, and loam underlay. Our results provide a significant and fundamental benchmark dataset for quantifying thaw slump changes in this vulnerable region undergoing strong climatic warming and extensive human activities.
2021
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Research Progress of InSAR Technology in Permafrost Research
Shichao Jia, Tingjun Zhang, Chengyan Fan, Lin Liu, and 1 more author
Permafrost is gradually degraded with climate warming， which seriously affects the stability of engineering construction in permafrost regions. Therefore， real-time and accurate monitoring of permafrost changes is urgent. Synthetic Aperture Radar Interferometry （InSAR）， as a new type of earth observation technology， can monitor the surface of permafrost regions on a large scale at all times and in all weather， and become an effective monitoring method. This paper aims to introduce the research progress and future development trends of InSAR technology in permafrost regions in the past two decades. Firstly， the basic principle of InSAR technology and SAR system are introduced. Then， based on the development of InSAR technology， the application of D-InSAR and multi-temporal InSAR in permafrost regions is outlined. It also summarizes the currently developed freeze-thaw models and analyzes the influencing factors of surface deformation in permafrost regions. Finally， look forward to the future development trend and main problems of InSAR technology in permafrost monitoring， in order to provide scientific research personnel with a systematic application introduction.
