Permafrost Deformation Monitoring Along the Qinghai-Tibet Plateau Engineering Corridor Using InSAR Observations with Multi-Sensor SAR Datasets from 1997–2018

Zhang, Zhengjia; Wang, Mengmeng; Wu, Zhijie; Liu, Xiuguo

doi:10.3390/s19235306

Cited by 43 publications

(30 citation statements)

References 61 publications

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“…ese InSAR techniques have been used in a wide range of deformation monitoring applications, such as urban ground settlement [31][32][33], mine subsidence [34][35][36][37][38][39][40][41], earthquakes and plate movements [42][43][44][45], volcanic eruptions [46][47][48], infrastructure deformation [49][50][51], glacial drift [52][53][54][55], permafrost deformation [56][57][58][59][60], and landslides [61][62][63]. Compared to other MT-InSAR techniques, SBAS-InSAR has the advantage of being able to overcome atmospheric interference and requires a relatively small amount of data [14,16,21].…”

Section: Introductionmentioning

confidence: 99%

Deformation Monitoring in an Alpine Mining Area in the Tianshan Mountains Based on SBAS‐InSAR Technology

Zhou

et al. 2021

Advances in Materials Science and Engineering

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The fragile habitat of alpine mining areas can be greatly affected by surface disturbances caused by mining activities, particularly open-pit mining activities, which greatly affect the periglacial environment. SBAS-InSAR technology enables the processing of SAR images to obtain highly accurate surface deformation information. This paper applied SBAS-InSAR technology to obtain three years of surface subsidence information based on the 89-scene Sentinel-1A SLC products, covering a mining area (tailings and active areas) in the Tianshan Mountains and its surroundings from 25th December 2017 to 2nd January 2021. The data were adopted to analyze the characteristics of deformation in the study region and the mining areas, and the subsidence accumulation was compared with field GNSS observation results to verify its accuracy. The results showed that the study area settled significantly, with a maximum settlement rate of −44.80 mm/a and a maximum uplift rate of 28.04 mm/a. The maximum settlement and accumulation of the whole study area over the three-year period were −129.39 mm and 60.49 mm, respectively. The mining area had a settlement value of over 80 mm over the three years. Significantly, the settlement rates of the tailings and active areas were −35 mm/a and −40 mm/a, respectively. Debris accumulation in the eastern portion of the tailings and active areas near the mountain was serious, with accumulation rates of 25 mm/a and 20 mm/a, respectively, and both had accumulation amounts of around 70 mm. For mine tailing pile areas with river flows, the pile locations and environmental restoration should be appropriately adjusted at a later stage. For gravel pile areas, regular cleaning should be carried out, especially around the mining site and at the tunnel entrances and exits, and long-term deformation monitoring of these areas should be carried out to ensure safe operation of the mining site. The SBAS-InSAR measurements were able to yield deformations with high accuracies over a wide area and cost less human and financial resources than the GNSS measurement method. Furthermore, the measurement results were more macroscopic, with great application value for surface subsidence monitoring in alpine areas.

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Section: Introductionmentioning

confidence: 99%

Deformation Monitoring in an Alpine Mining Area in the Tianshan Mountains Based on SBAS‐InSAR Technology

Zhou

et al. 2021

Advances in Materials Science and Engineering

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“…As the highest elevation permafrost region in the world, the Qinghai-Tibet Plateau (QTP) permafrost is quickly degrading due to global warming, climate change, and human activities. The seventh article [ 7 ], “Permafrost Deformation Monitoring Along the Qinghai-Tibet Plateau Engineering Corridor Using InSAR Observations with Multi-Sensor SAR Datasets from 1997–2018”, presents an application using a time-series InSAR technique with multiple SAR datasets to monitor the permafrost ground deformation along the QTEP from 1997 to 2018. GaoFen-3 is a new Chinese InSAR remote sensing satellite.…”

Section: Special Issue Contentsmentioning

confidence: 99%

InSAR Signal and Data Processing

Xing

Lü

2020

Sensors

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“…Over the past three or four decades, permafrost has experienced wide degradation in the context of climate warming and increasing anthropogenic activities, which is characterized by rising of ground temperatures, increasing of active layer thickness (ALT), decreasing of maximum frozen soil depth (MFSD), as well as the disappearance of isolated permafrost [3,[8][9][10][11][12][13]. The variation in permafrost exerts significant influences on the alterations of hydrological cycles [14][15][16], thermokarst-inducing processes [17], exacerbation of biogeochemical cycles [18,19], changes in landscapes and geomorphologies [17,20], as well as losses of stabilization of surface hydrothermal dynamics [21,22]. The degradation of permafrost and its adverse consequences have attracted widespread attention from stakeholders in governmental policy and planning and residents, as well as among scientific communities.…”

Section: Introductionmentioning

confidence: 99%

Mapping Frozen Ground in the Qilian Mountains in 2004–2019 Using Google Earth Engine Cloud Computing

Yuan

Li²,

Ran

et al. 2021

Remote Sensing

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The permafrost in the Qilian Mountains (QLMs), the northeastern margin of the Qinghai–Tibet Plateau, changed dramatically in the context of climate warming and increasing anthropogenic activities, which poses significant influences on the stability of the ecosystem, water resources, and greenhouse gas cycles. Yet, the characteristics of the frozen ground in the QLMs are largely unclear regarding the spatial distribution of active layer thickness (ALT), the maximum frozen soil depth (MFSD), and the temperature at the top of the permafrost or the bottom of the MFSD (TTOP). In this study, we simulated the dynamics of the ALT, TTOP, and MFSD in the QLMs in 2004–2019 in the Google Earth Engine (GEE) platform. The widely-adopted Stefan Equation and TTOP model were modified to integrate with the moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) in GEE. The N-factors, the ratio of near-surface air to ground surface freezing and thawing indices, were assigned to the freezing and thawing indices derived with MODIS LST in considerations of the fractional vegetation cover derived from MODIS normalized difference vegetation index (NDVI). The results showed that the GEE platform and remote sensing imagery stored in Google cloud could be quickly and effectively applied to obtain the spatial and temporal variation of permafrost distribution. The area with TTOP < 0 °C is 8.4 × 104 km2 (excluding glaciers and lakes) and accounts for 46.6% of the whole QLMs, the regional mean ALT is 2.43 ± 0.44 m, while the regional mean MFSD is 2.54 ± 0.45 m. The TTOP and ALT increase with the decrease of elevation from the sources of the sub-watersheds to middle and lower reaches. There is a strong correlation between TTOP and elevation (slope = −1.76 °C km−1, p < 0.001). During 2004–2019, the area of permafrost decreased by 20% at an average rate of 0.074 × 104 km2·yr−1. The regional mean MFSD decreased by 0.1 m at a rate of 0.63 cm·yr−1, while the regional mean ALT showed an exception of a decreasing trend from 2.61 ± 0.45 m during 2004–2005 to 2.49 ± 0.4 m during 2011–2015. Permafrost loss in the QLMs in 2004–2019 was accelerated in comparison with that in the past several decades. Compared with published permafrost maps, this study shows better calculation results of frozen ground in the QLMs.

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Permafrost Deformation Monitoring Along the Qinghai-Tibet Plateau Engineering Corridor Using InSAR Observations with Multi-Sensor SAR Datasets from 1997–2018

Cited by 43 publications

References 61 publications

Deformation Monitoring in an Alpine Mining Area in the Tianshan Mountains Based on SBAS‐InSAR Technology

Deformation Monitoring in an Alpine Mining Area in the Tianshan Mountains Based on SBAS‐InSAR Technology

InSAR Signal and Data Processing

Mapping Frozen Ground in the Qilian Mountains in 2004–2019 Using Google Earth Engine Cloud Computing

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