Monitoring surface deformation of permafrost in Wudaoliang Region, Qinghai–Tibet Plateau with ENVISAT ASAR data

Li, Rongxing; Li, Zhenshi; Han, Jiangping; Lü, Ping; Qiao, Gang; Meng, Xianglian; Tu, Hao; Zhou, Fanqin

doi:10.1016/j.jag.2021.102527

Cited by 16 publications

(21 citation statements)

References 32 publications

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“…Wang et al used TerraSAR data to obtain deformation results for the Beiluhe Basin from 2014 to 2016 [29] and found that the overall deformation rate in the basin is −15 mm/yr to 0 mm/yr, which is consistent with our results. Li et al used ENVISAT data to obtain the deformation results for Wudaoliang region from 2006 to 2009 [19] and found that the total deformation rate of this area is between −15 mm/yr and 15 mm/yr, which is consistent with the results of this paper. In general, the results of this study are consistent with the previous studies, and the small differences may be related to the differences in the observation periods of the data, which further illustrates the validity of the results of this paper.…”

Section: Comparisons With Previous Studiessupporting

confidence: 86%

“…Time-series InSAR has proven an established remote sensing technique to detect small surface deformations with high precision, and at high resolution, and has been successfully applied to monitor surface deformation in the permafrost regions of Siberia, Alaska, and the QTP [14][15][16][17][18][19][20]. In the Alaska North Slope region, Liu et al used ERS data to obtain the surface deformation results based on time-series InSAR technology, indicating that time-series InSAR technology can provide a new means of observation for permafrost system dynamics and permafrost state monitoring [14].…”

Section: Introductionmentioning

confidence: 99%

“…Li et al used the time-series InSAR technology to obtain time-series deformation results for the Wudaoliang area of the Qinghai-Tibet Railway and verified the InSAR deformation results by using the GPS leveling data of 24 points. The results show that the time-series InSAR technology can be effectively applied to the surface deformation monitoring of permafrost in the QTP [19]. Chen et al used Sentinel-1 data to obtain the time-series deformation results of the area along the Qinghai-Tibet Railway, and combined them with environmental factors such as terrain, vegetation, and ground ice to analyze the main influencing factors of linear deformation rate and seasonal deformation amplitude in the study area [20].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, the number of satellites with InSAR capability and the volume of associated data have increased significantly, and the improvements in data quality and in processing methods have greatly improved the capability and application range of InSAR in ground deformation monitoring [18][19][20]. In particular, the Sentinel-1 satellite constellation is capable of conducting earth observations with a revisit period of 6-12 days, making it an important data source in ground deformation monitoring [21,22].…”

Section: Introductionmentioning

confidence: 99%

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Monitoring Regional-Scale Surface Deformation of the Continuous Permafrost in the Qinghai–Tibet Plateau with Time-Series InSAR Analysis

Jiang

Niu

et al. 2022

Remote Sensing

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As an important indicator of permafrost degradation, surface deformation is often used to monitor the thawing and freezing process in the permafrost active layer. However, due to the large area of the continuous permafrost of the Qinghai–Tibet Plateau (QTP) and the large amount of data processed by conventional time-series InSAR, previous studies have mostly focused on local area investigations, and regional characteristics of surface deformation of the continuous permafrost area on the QTP are still unclear. In this paper, we characterized surface deformation in space and time over the main continuous permafrost area on the QTP, by analyzing 11 ascending and 8 descending orbits of Sentinel-1 SAR data acquired between 2018 and 2021 with the time-series InSAR processing system LiCSAR. The reliability of the InSAR deformation results was verified by a combination of leveling measurement data, the intercomparison of overlapping area results, and field verification. The results show that the permafrost regions of the central QTP exhibited the most significant linear subsidence trend. The subsidence trend of permafrost on the QTP was mainly related to the thermal stability of permafrost, and the regions with larger subsidence rates were concentrated in sub-stable, transitional and unstable permafrost areas. We also found that, according to analysis of time-series displacement, the beginning and ending times of permafrost thawing were highly spatially heterogeneous, with the time of maximum thawing depth varying between mid-October and mid-November, which was probably attributed to the active layer thickness (ALT), water content in the active layer, and vegetation cover in these regions. This study is of great significance for understanding the changing trend of permafrost on the QTP under the background of climate change. In addition, this study also demonstrates that combination of Sentinel-1 SAR images with the LiCSAR system has significant potential for detecting permafrost deformation with high accuracy and high efficiency at regional and global scales.

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Section: Comparisons With Previous Studiessupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Monitoring Regional-Scale Surface Deformation of the Continuous Permafrost in the Qinghai–Tibet Plateau with Time-Series InSAR Analysis

Jiang

Niu

et al. 2022

Remote Sensing

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“…However, the time-related characteristics of F-T in AL, such as the onset of freezing/thawing and thawing duration, are the main factors determining vegetation growth and energy exchange between land and air [76,79] and have not been explored yet. Many factors influence the amplitude and temporal variability of seasonal deformation amplitude (SDA), such as spatial location [71,78,80,81], topography [82][83][84][85], vegetation [70,75], ground thermal regime variability [76,79], soil water content [8,74,77,80,86], soil particle size [87,88], active layer thickness (ALT) [8,64,76,89,90], etc. These factors also lack detailed analysis as well.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of Freeze–Thaw Cycles in an Endorheic Basin on the Qinghai-Tibet Plateau Based on SBAS-InSAR Technology

et al. 2022

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The freeze–thaw (F-T) cycle of the active layer (AL) causes the “frost heave and thaw settlement” deformation of the terrain surface. Accurately identifying its amplitude and time characteristics is important for climate, hydrology, and ecology research in permafrost regions. We used Sentinel-1 SAR data and small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) technology to obtain the characteristics of F-T cycles in the Zonag Lake-Yanhu Lake permafrost-affected endorheic basin on the Qinghai-Tibet Plateau from 2017 to 2019. The results show that the seasonal deformation amplitude (SDA) in the study area mainly ranges from 0 to 60 mm, with an average value of 19 mm. The date of maximum frost heave (MFH) occurred between November 27th and March 21st of the following year, averaged in date of the year (DOY) 37. The maximum thaw settlement (MTS) occurred between July 25th and September 21st, averaged in DOY 225. The thawing duration is the thawing process lasting about 193 days. The spatial distribution differences in SDA, the date of MFH, and the date of MTS are relatively significant, but there is no apparent spatial difference in thawing duration. Although the SDA in the study area is mainly affected by the thermal state of permafrost, it still has the most apparent relationship with vegetation cover, the soil water content in AL, and active layer thickness. SDA has an apparent negative and positive correlation with the date of MFH and the date of MTS. In addition, due to the influence of soil texture and seasonal rivers, the seasonal deformation characteristics of the alluvial-diluvial area are different from those of the surrounding areas. This study provides a method for analyzing the F-T cycle of the AL using multi-temporal InSAR technology.

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A refined parallel stacking InSAR workflow for large-scale deformation fast extraction—a case study of Tibet

Wang

Zhang

Chen

et al. 2022

Geocarto International

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Monitoring surface deformation of permafrost in Wudaoliang Region, Qinghai–Tibet Plateau with ENVISAT ASAR data

Cited by 16 publications

References 32 publications

Monitoring Regional-Scale Surface Deformation of the Continuous Permafrost in the Qinghai–Tibet Plateau with Time-Series InSAR Analysis

Monitoring Regional-Scale Surface Deformation of the Continuous Permafrost in the Qinghai–Tibet Plateau with Time-Series InSAR Analysis

Characteristics of Freeze–Thaw Cycles in an Endorheic Basin on the Qinghai-Tibet Plateau Based on SBAS-InSAR Technology

A refined parallel stacking InSAR workflow for large-scale deformation fast extraction—a case study of Tibet

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