Ground Surface Deformation Research Articles

Ground Surface Deformation Analysis Integrating InSAR and GPS Data in the Karstic Terrain of Cheria Basin, Algeria

Karstic terrains are usually dominated by aquifer systems and/or underground cavities. Overexploitation of groundwater in such areas often induces land subsidence and sometimes causes sinkholes. The Cheria basin in Algeria suffers from severe land subsidence issues, and this phenomenon has been increasing in recent years due to population expansion and uncontrolled groundwater exploitation. This work uses GPS data and persistent scatterer interferometry synthetic aperture radar (PS-InSAR) techniques to monitor the land subsidence rate by employing Sentinel-1 satellite data for the period from 2016 to 2022. Our results demonstrate that the Cheria basin experiences both uplift and subsidence in places, with an overall substantial change in the land surface. The total cumulative subsidence over 6 years reached a maximum of 500 mm. Comparison of land deformation between PSI and GPS showed root mean square error (RMSE) values of about 2.83 mm/year, indicating that our analyzed results are satisfactorily reproducing the actual changes. Nonetheless, these results can be used to extract the susceptible zones for vertical ground displacement and evaluate the surface deformation inventory map of the region for reducing damages (e.g., human losses, economic impact, and environmental degradation) that may occur in the future (e.g., sinkholes) and can be further utilized in perspective for a sinkhole early warning system.

Monitoring Ground Surface Deformation of Ice-Wedge Polygon Areas in Saskylakh, NW Yakutia, Using Interferometric Synthetic Aperture Radar (InSAR) and Google Earth Engine (GEE)

As one of the best indicators of the periglacial environment, ice-wedge polygons (IWPs) are important for arctic landscapes, hydrology, engineering, and ecosystems. Thus, a better understanding of the spatiotemporal dynamics and evolution of IWPs is key to evaluating the hydrothermal state and carbon budgets of the arctic permafrost environment. In this paper, the dynamics of ground surface deformation (GSD) in IWP zones (2018–2019) and their influencing factors over the last 20 years in Saskylakh, northwestern Yakutia, Russia were investigated using the Interferometric Synthetic Aperture Radar (InSAR) and Google Earth Engine (GEE). The results show an annual ground surface deformation rate (AGSDR) in Saskylakh at −49.73 to 45.97 mm/a during the period from 1 June 2018 to 3 May 2019. All the selected GSD regions indicate that the relationship between GSD and land surface temperature (LST) is positive (upheaving) for regions with larger AGSDR, and negative (subsidence) for regions with lower AGSDR. The most drastic deformation was observed at the Aeroport regions with GSDs rates of −37.06 mm/a at tower and 35.45 mm/a at runway. The GSDs are negatively correlated with the LST of most low-centered polygons (LCPs) and high-centered polygons (HCPs). Specifically, the higher the vegetation cover, the higher the LST and the thicker the active layer. An evident permafrost degradation has been observed in Saskylakh as reflected in higher ground temperatures, lusher vegetation, greater active layer thickness, and fluctuant numbers and areal extents of thermokarst lakes and ponds.

Geodetic imaging of ground deformation and reservoir parameters at the Yangbajing Geothermal Field, Tibet, China

SUMMARYMonitoring and modeling ground surface deformation are crucial for the dynamic assessment of geothermal resources and sustainable exploitation in a geothermal field. In this study, we extract the deformation in the Yangbajing geothermal field by the small baseline-synthetic aperture radar interferometry (SBAS-InSAR) method using 141 Sentinel-1A images collected between March 2017 and November 2021. The InSAR result indicates both uplift and subsidence in the geothermal field. Subsequently, we use a dual-source model combining a dipping ellipsoid and a rectangular surface to model the shallow reservoir that contracted to cause the complex subsidence field in the north of the geothermal field. The shallow reservoir that expanded to cause the uplift in the south is modeled by an ellipsoid source. The parameters inversion is processed by the nonlinear Bayesian inversion method which has been applied to search the optimal parameters setting in a priori space and evaluate the uncertainties by the confidence intervals. To validate our inversion results, we collect the data from 31 wells including extraction and injection wells, detailed tectonic survey data and geothermal isotherms of the Yangbajing geothermal field. The modeled shallow reservoir in the north is within a 140 °C ground isotherm and a 160 °C underground isotherm. The thickness and depth of the reservoir slightly exceed the data from producing wells, probably due to the structural subsidence of the reservoir. The geometric structure is consistent with the channel faults that control the formation and development of the shallow reservoirs. The modeled reservoir under the rebound area in the south is also validated by comparing the data. Furthermore, we estimate the volume loss and recovery of the contracting and expanding reservoirs. We analyse the deformation mechanisms by considering the tectonic formation, the reservoir structure, and the extraction and rechargeability of the reservoirs. This research suggests the deformation pattern of shallow porous reservoirs that have similar layer composition and tectonic structure elsewhere in the world. Moreover, it provides a theoretical model to explore the parameters and volume change of geothermal reservoirs in plateau-embedded basins around the world. Our work is significant for the conservation and development of geothermal energy in geothermal fields that experience deformation, both subsidence and uplift.

Evolution of tunnel uplift and deformation induced by an upper and collinear excavation: A case study from Shenzhen metro

This paper presented a case study in Shenzhen metro where the evolution of the tunnel uplift and deformation was investigated based on the field observation. The deformation of tunnel, diagram wall and ground surface were carefully measured over 400 days. The tunnels had been significantly uplifted by 34 mm, while less convergence deformation was observed in each section. For the long excavation collinear to the underlying tunnel in Shenzhen granite residual soil, the superposition unloading of the other adjacent upper and collinear excavation activities has a more significant impact on the tunnel uplift compared to the excavation of upper section, which lead to more than half of the tunnel uplift amount. In addition, a slight twist deformation was observed in the tunnel section, which need to be focused in the evaluation of tunnel safety because it is a main contribution to the tunnel diseases. The well-document site data and results can provide systematic field data and useful engineering reference for similar projects.

An integrated approach for risk assessment of land subsidence in Xi'an, China using optical and radar satellite images

Land subsidence, induced by the over-exploitation of groundwater resources, is becoming a huge hazard in many large cities around the world. Risk assessment of the infrastructure under the threat of land subsidence plays a vital role in urban planning and design. In this study, an integrated approach that combines the land subsidence, the ground fissures, and the elements at risk is proposed. The ground surface deformation is studied with time-series Interferometric Synthetic Aperture Radar (InSAR), and the differential settlement is assessed by an index of angular distortion. Then, the elements that are potentially affected by the land subsidence are recognized through a land use classification analysis, which is based on a synergetic use of optical and radar images using an object-based approach. Finally, the risk due to land subsidence is assessed using a risk matrix that integrates the differential settlement, the ground fissures, and the land use classification results. To demonstrate the effectiveness of the proposed method, a risk assessment of the land subsidence in the City of Xi'an, China is conducted. Our results also illustrate the advantages of the synergetic land use classification over the pixel-based classification.

A Novel Deformation Extraction Approach for Sub-Band InSAR and Its Application in Large-Scale Surface Mining Subsidence Monitoring

Differential synthetic aperture radar interferometry (InSAR) is widely used to monitor ground surface deformation due to its wide coverage and high accuracy. However, the large-scale and rapid deformation that occurs in mining areas often leads to densely spaced interference fringes, thus, severely limiting the applicability of D-InSAR in mining subsidence monitoring. Sub-band InSAR can reduce phase gradients in interferograms by increasing the simulated wavelength, thereby characterising large-scale surface deformations. Nonetheless, accurate registration between non-overlapping sub-band images with conventional sub-band InSAR is challenging. Therefore, our study proposed a new sub-band InSAR deformation extraction method, based on raw full-bandwidth single-look complex image pair registration data to facilitate sub-band interferometric processing. Simulations under noiseless conditions demonstrated that the maximum difference between the sub-band InSAR-monitored results and real surface deformations was 26 mm (1.86% of maximum vertical deformation), which theoretically meets the requirements for mining subsidence monitoring. However, when modelling dynamic deformation with noise, the sub-band InSAR-simulated wavelength could not be optimised for surface deformation due to the limitation in current SAR satellite bandwidths, which resulted in significantly noisy and undistinguishable interference fringes. Nonetheless, this method could still be advantageous in high-coherence regions where surface deformation exceeds 1/5th of the simulated wavelength.

Integrated analysis of Hashtgerd plain deformation, using Sentinel-1 SAR, geological and hydrological data

Due to its proximity to Tehran, the Hashtgerd catchment in Iran is an important region that has experienced alarming subsidence rates in recent years. This study estimated the ground surface deformation in the Hashtgerd plain between 2015 and 2020 using Sentinel-1 SAR data and InSAR technique. The average LOS displacement of the ascending and descending tracks was − 23 cm/year and − 22 cm/year, respectively. The central area of the plain experienced the greatest vertical subsidence, with a more than − 100 cm cumulative displacement. The Karaj-Qazvin railway and highway that pass through this area have been damaged by subsidence, according to an analysis of profiles drawn along the transportation lines. The southern sections of Hashtgerd city have experienced a total displacement of − 30 cm/year over the course of about 6 years. The relationship between changes in groundwater level and subsidence rate in this region was examined using piezometer and precipitation data. Geoelectric sections and piezometric well logs were also utilized to investigate the geological characteristics of the Hashtgerd aquifer. According to the findings, the leading causes of subsidence were uncontrolled groundwater abstraction. This research highlights the need to comprehend the spatial distribution of confined aquifers and their effect on subsidence, which can aid in the development of a suitable management strategy to restore these aquifers.

Review on the Research and Applications of TLS in Ground Surface and Constructions Deformation Monitoring.

With the gradual maturity of the terrestrial laser scanners (TLS) technology, it is widely used in the field of deformation monitoring due to its fast, automated, and non-contact data acquisition capabilities. The TLS technology has changed the traditional deformation monitoring mode which relies on single-point monitoring. This paper analyzes the application of TLS in deformation monitoring, especially in the field of ground surface, dam, tunnel, and tall constructions. We divide the methods for obtaining ground surface deformation into two categories: the method based on point cloud distance and the method based on displacement field. The advantages and disadvantages of the four methods (M2M, C2C, C2M, M3C2) based on point cloud distance are analyzed and summarized. The deformation monitoring methods and precisions based on TLS for dams, tunnels, and tall constructions are summarized, as well as the various focuses of different monitoring objects. Additionally, their limitations and development directions in the corresponding fields are analyzed. The error sources of TLS point cloud data and error correction models are discussed. Finally, the limitations and future research directions of TLS in the field of deformation monitoring are presented in detail.

Editorial: Advanced big SAR data analytics and applications

As a technology of remote sensing and imaging geodesy, Synthetic Aperture Radar (SAR), which 11 can be spaceborne or airborne, has shown unique Earth observation capacity in recent decades. 12 Compared to optical remote sensing technology, SAR can work day and night without the need of 13 visible light, and possesses penetrating capacity to cloud, fog and some ground covers (e.g., vegetation, 14 ice, desert) to a certain degree. In particular, Interferometric SAR (InSAR) technology can be used to 15 monitor subtle ground surface deformation over large area with unprecedented resolution and accuracy, 16and has evolved into a routine method in the field of disaster and environmental monitoring.The volume of SAR data is growing at ever-increasing rates thanks to the lunch of numerous radar 18 satellites that can image the Earth under high resolution, multi-polarized and wide swath mode at short 19 repeat cycles. Such big SAR data, on one hand, challenge the conventional processing routines and 20 present opportunities for data-driven analysis technologies (e.g.

Prediction of Ground Surface Deformation Induced by Earthquake on Urban Area Using Machine Learning

Earthquakes can inflict significant damage to structures and infrastructures. This paper presents a machine learning model to predict ground surface deformation (GDS) induced by earthquake events. The data on historical GSD is extracted from radar product of Synthetic Aperture Radar (SAR) data of one-year over five magnitude earthquakes that occurred within 200 kilometers of the Kota Padang Regency, West Sumatra. Building topology data of its footprint area, distance from shoreline, elevation, and coordinate were incorporated as the main features in the dataset. The earthquake parameters were taken from the USGS earthquake data catalog. Four machine learning algorithms of Neural Network (NN), Random Forest (RF), k-Nearest Neighbors (kNN), and Gradient Boosting (GB) are applied. The GSD from the trained models is predicted and compared with the measured GSD from the SAR’s product. The performances of proposed algorithms are evaluated in terms of the statistical index. A new dataset from the earthquake event in March 2022 is used to predict the GSD and further test the performance of the trained models. Overall, the four machine learning algorithms have outstanding performance, with a coefficient determinant of more than 0.9. The kNN algorithm outperforms compared to others in delineating the GSD. The trained models gave deficient prediction performance on the new dataset with a correlation coefficient of 0.228 predicted by the RF algorithm. Additional earthquake datasets and more unique features will improve the performance of the machine learning algorithms.

Monitoring of ground surface deformation at Taimyrsky Mine using Sentinel-1 radar imaging for geodynamic risk assessment

The modern stage of mineral mining involves prediction of geotechnical risks. One of the major methods in this regard is the geodynamic zoning. The key target is to assess the cross-effect of mining operations and blocks structure of the Earth’s crust. This article presents the information on ground surface subsidence within the boundary of the mining lease of Taimyrsky Mine as a result of processing of paired images from Sentinel-1A sate llite. The implemented probabilistic kinematic analysis revealed some features of movements in overlying rock mass, in particular, local uplifts of ground surface. The detailed information on vertical deformations was obtained. Such approach enabled detecting the deformation areas subjected to the effect of the global tectonics which is, as a rule, neglected in geotechnical risk assessment while it directly affects mining safety. Despite the apparently consistent patterns resulted from processing of satellite images, the method InSAR is only used as a supplemental technique since the relevant regulatory framework is yet absent. In combination with the conventional surveying for monitoring ground surface deformations, the method InSAR enhances efficiency of monitoring and improves accuracy of geodynamic risk prediction in the course of mineral mining, inclusive of observations over the global tectonic processes. The probabilistic kinematic analysis allows for getting insight into the mechanism of overlying rock mass movement with regard to rock mass jointing and, jointly with InSAR, can be used in the artificial intelligence systems for learning models of prediction of overlying rock movement parameters during mineral mining.

Updating Inventory, Deformation, and Development Characteristics of Landslides in Hunza Valley, NW Karakoram, Pakistan by SBAS-InSAR

The Hunza Valley, in the northwestern Karakoram Mountains, North Pakistan, is a typical region with many towns and villages, and a dense population and is prone to landslides. The present study completed landslide identification, updating a comprehensive landslide inventory and analysis. First, the ground surface deformation was detected in the Hunza Valley by SBAS-InSAR from ascending and descending datasets, respectively. Then, the locations and boundaries were interpreted and delineated, and a comprehensive inventory of 118 landslides, including the 53 most recent InSAR identified active landslides and 65 landslides cited from the literature, was completed. This study firstly named all 118 landslides, considering the demand for globally intensive research and hazard mitigation. Finally, the deformation, spatial–topographic development, and distribution characteristics in the Hunza Valley scale and three large significant landslides were analyzed. Information on 72 reported landslides was used to construct an empirical power law relationship linking landslide area (AL) to volume (VL) (VL = 0.067 × AL1.351), and this formula predicted the volume of 118 landslides in this study. We discovered that the landslides from the literature, which were interpreted from optical images, had lower levels of velocity, area, elevation, and height. The SBAS-InSAR-detected active landslide was characterized by higher velocity, larger area, higher elevation, larger slope gradient, larger NDVI (normalized difference vegetation index), and greater height. The melting glacier water and rainfall infiltration from cracks on the landslide’s upper part may promote the action of a push from gravity on the upper part. Simultaneously, the coupling of actions from river erosion and active tectonics could have an impact on the stability of the slope toe. The up-to-date comprehensive identification and understanding of the characteristics and mechanism of landslide development in this study provide a reference for the next step in landslide disaster prevention and risk assessment.

Evidence of ground ice melting detected by InSAR and in situ monitoring over permafrost terrain on the Qinghai‐Xizang (Tibet) Plateau

AbstractThe thawing of ice‐rich permafrost has attracted considerable attention in recent years. In this study, we analyzed both the ground surface deformation time series spanning 6 years, derived through the SBAS‐InSAR technique on the Qinghai‐Xizang (Tibet) Plateau (QTP), and the long‐term active layer soil temperature and moisture in situ observations and their relationships. The results showed that long‐term subsidence velocity directly represents the melting of ground ice instead of the thickening rate of the active layer by a quantitative analysis of both terrain subsidence velocity and active layer thickening rate and the increase in liquid water at the bottom of the active layer. Ice‐poor permafrost thawing does not result in distinct subsidence, although the active layer deepening rate can be very high. The spatial analysis reveals that long‐term deformation velocities are large in the foothills and on gentle slopes (1–5 degrees) and are closely related to geomorphological conditions, which could regulate the soil properties and ground ice content. These findings improve the understanding of the thawing degradation of icy permafrost and promote method developments for the automated mapping of ground ice melting in permafrost environments.

Study and Prediction of Surface Deformation Characteristics of Different Vegetation Types in the Permafrost Zone of Linzhi, Tibet

Permafrost and alpine vegetation are widely distributed in Tibet, which is a sensitive area for global climate change. In this study, we inverted the surface deformation from 22 May 2018 to 9 October 2021 in a rectangular area within the city of Linzhi, Tibet, using the Sentinel1-A data and two time-series interferometric system aperture radar (InSAR) techniques. Then, the significant features of surface deformation were analyzed separately according to different vegetation types. Finally, multiple machine learning methods were used to predict future surface deformation, and the results were compared to obtain the model with the highest prediction accuracy. This study aims to provide a scientific reference and decision basis for global ecological security and sustainable development. The results showed that the surface deformation rate in the study area was basically between ±10 mm/a, and the cumulative surface deformation was basically between ±35 mm. The surface deformation of grassland, meadow, coniferous forest, and alpine vegetation were all significantly correlated with NDVI, and the effect of alpine vegetation, coniferous forest, and grassland on permafrost was stronger than that of the meadow. The prediction accuracy of the Holt–Winters model was higher than that of Holt′s model and the ARIMA model; it was expected that the ground surface would keep rising in the next two months, and the ground surface deformation of alpine vegetation and the coniferous forest was relatively small. The above studies indicated that the surface deformation in the Tibetan permafrost region was relatively stable under the conditions of alpine vegetation and coniferous forest. Future-related ecological construction needs to pay more attention to permafrost areas under grassland and meadow conditions, which are prone to surface deformation and affect the stability of ecosystems.

Performance of the three-dimensional laser scanning method to monitor the moisture content of similar material models

In mining safety and other fields, similar material simulation is the main research method to study the movement and deformation of rock formation and ground surface. However, the inaccurate subsidence laws could be obtained because the strength of the composition materials like gypsum and lime is easily affected by moisture. Therefore, it is crucial to monitor the moisture content when carrying simulation experiments. This paper discussed the feasibility of indirectly measuring the moisture content of similar material models using the three-dimensional (3D) laser scanning reflection intensity through three experiments on similar material specimens. The results showed that the laser reflection intensity was sensitive to the moisture content, incidence angle, and distance with three different relationships and the influence of the two factors could be weakened through the established correction models. However, it was recommended restricting the incidence angle to less than 20° and setting the distance from 4 to 10 m to reduce the complexity of correction. The accuracy of this method reached 1.1% under the monitoring condition of 4 m and the normal incidence, which could meet the requirements for monitoring the moisture content of similar material models. The research results of the paper provide a new method to monitor the moisture content in similar material models.

Contribution of ground ice melting to the expansion of Selin Co (lake) on the Tibetan Plateau

Abstract. Selin Co, located within permafrost regions surrounded by glaciers, has exhibited the greatest increase in water storage among all the lakes on the Tibetan Plateau over the last 50 years. Most of the increased lake water volume has been attributed to increased precipitation and the accelerated melting of glacier ice, but these processes are still not sufficient to close the water budget with the expansion of Selin Co. Ground ice meltwater released by thawing permafrost due to continuous climate warming over the past several decades is regarded as another source of lake expansion. This study presents the first attempt to quantify the water contribution of ground ice melting to the expansion of Selin Co by evaluating the ground surface deformation. We monitored the spatial distribution of surface deformation in the Selin Co basin using the small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) technique and compared the results with the findings of field surveys. Then, the ground ice meltwater volume in the watershed was calculated based on the cumulated settlement. Finally, this volume was compared with the lake volume change during the same period, and the contribution ratio was derived. SBAS-InSAR monitoring during 2017–2020 illustrated widespread and large subsidence in the upstream section of the Zhajiazangbu subbasin, where widespread continuous permafrost is present. The terrain subsidence rate was normally between 5 and 20 mm a−1, indicating rapid ground ice loss in the region. The ground ice meltwater was released at a rate of ∼57×106 m3 a−1, and the rate of increase in lake water storage was ∼485×106 m3 a−1 during the same period, with ground ice meltwater contributing ∼12 % of the lake volume increase. This study contributes to explaining the rapid expansion of Selin Co and equilibrating the water balance at the watershed scale. More importantly, the proposed method can be extended to other watersheds underlain by permafrost and help in understanding the hydrological changes in these watersheds.

A novel fuzzy approach to gas pipeline risk assessment under influence of ground movement

The gas transport infrastructure is frequently localized in areas subjected to anthropogenic movements and strains. The potential impact of the ground movements on the gas pipeline in the aspect of its damage can be properly assessed e.g. by predicting strains, taking into account the causes of terrain movement. On the other hand, the hazard is also related to technological factors like design of the pipeline. The presented method is based on artificial intelligence methods allowing for evaluation of probability of failure risk in gas supply pipeline sections. The Mamdani fuzzy inference was used in this study. Uncertainty of variables characterizing the resistance of the gas pipeline and predicted continuous deformations of ground surface were accounted for in the model by using triangular-shaped membership functions. Based on the surface deformations and gas pipeline resistance and the inference model one can make prediction when the gas pipeline is hazarded. There were estimated two the most hazarded parts for two pipelines. We proved that the proposed model can contribute to the protection, costoptimization of the designed pipelines and to the repairs of the existing gas pipelines.

Nonlocal regularized numerical analyses for passive failure of tunnel head in strain-softening soils

This work looks into the passive failure of tunnel head in strain-softening soils modeled using a nonlocal constitutive model. The Drucker–Prager yield criterion and plastic potential are used, and an over-nonlocal approach is utilized to regularize the ill-posed boundary value problems emerging from material softening and strain localization inelasticity. The nonlocal variable is incorporated through a Helmholtz-type partial different equation (PDE), instead of nonlocal integration. A nonlocal implicit gradient enhancement is proposed, and its numerical implementation is discussed. The proposed methodology is verified to produce mesh-independent strain-softening responses accompanied by localized deformation. The passive failure analysis of tunnel head is conducted to study key parameters influencing plastic strain accumulations and ground surface deformation. It is revealed that the strain-softening mechanism can promote local concentrated passive deformation and substantial ground surface movement near the tunnel head. Increasing the friction angle increases face supporting force, but only affects the inelastic deformation in a minimal way. The increase in the dilation angle widens the extent of horizontal soil deformation and vertical ground deformation, while a larger cover depth suppresses the passive failure response of shallow tunneling.

Study on the Combined Mining Scheme for Coal Resources under High-Voltage Pylons and the Reinforcement for Pylons

The increasing use of high-voltage transmission wires requires more and more high-voltage pylons, and sometimes, constructing pylons in mining areas is very urgent. To ensure the safe operation of pylons, coal pillars with large side lengths are usually used to provide sufficient support; however, this results in a huge waste of coal. Eight high-voltage pylons are arranged on the ground surface corresponding to the location of working face 1110 of Sima Coal Mine in Shanxi Province, China, which cannot be mined by traditional methods. Taking this as the engineering background, the failure mode of high-voltage pylon is first analyzed. Using FLAC3D numerical simulations, the influence of five different mining plans on ground surface deformation in working face 1110 is evaluated, and the vertical settlement and horizontal deformation in different areas of the ground surface, as well as the variation law of horizontal strain and slope are analyzed. According to the numerical simulation results, the range of thickness-limiting mining or backfill mining in working face 1110 is shown in scheme 3, and the key regions in the mining process are determined. Secondly, the strengthening scheme of high-voltage pylons is designed, that is, the four foundations of high-voltage pylons are connected as a whole with steel supports and steel connectors so as to improve the structural strength of the high-voltage pylon. Finally, the position change in the foundation of high-voltage pylons was monitored for 22 consecutive months. The results show that the maximum settlement of the high-voltage tower foundation is 3.1 m, which is consistent with the actual mining thickness; The high-voltage pylon was stably moved, and the change in transmission line tension and total length was usually less than 1.0%. The combined mining scheme and foundation strengthening scheme can ensure the safe operation of high-voltage pylons and provide a new method for the stability control of ground buildings in coal mining subsidence area.

Influence of Open-Pit Coal Mining on Ground Surface Deformation of Permafrost in the Muli Region in the Qinghai-Tibet Plateau, China

The Qinghai-Tibet Plateau (QTP) is the largest mid-to low latitude and high-altitude permafrost. Open-pit coal mining and other activities have caused serious damage to the alpine ecological environment and have accelerated the degradation of permafrost on the QTP. In this study, the influence of open-pit coal mining on the time series ground surface deformation of the permafrost in the Muli region of the QTP was analyzed from 19 January 2018 to 22 December 2020 based on Landsat, Gaofen, and Sentinel remote sensing data. The primary methods include human-computer interactive visual interpretation and the small baseline subsets interferometric synthetic aperture radar (SBAS-InSAR) method. The results showed that the spatial distribution of displacement velocity exhibits a considerably different pattern in the Muli region. Alpine meadow is the main land use/land cover (LULC) in the Muli region, and the surface displacement was mainly subsidence. The surface subsidence trend in alpine marsh meadows was obvious, with a subsidence displacement velocity of 10–30 mm/a. Under the influence of changes in temperature, the permafrost surface displacement was characteristics of regular thaw subsidence and freeze uplift. Surface deformation of the mining area is relatively severe, with maximum uplift displacement velocity of 74.31 mm/a and maximum subsidence displacement velocity of 167.51 mm/a. Open-pit coal mining had resulted in the destruction of 48.73 km2 of natural landscape in the Muli region. Mining development in the Muli region had increased the soil moisture of the alpine marsh meadow around the mining area, resulting in considerable cumulative displacement near the mining area and the acceleration of permafrost degradation.