SBAS-InSAR Technique Research Articles

Monitoring and Analysis of Surface Deformation in the Buzhaoba Open-Pit Mine Based on SBAS-InSAR Technology

The Buzhaoba open-pit mine is an important lignite production base in Yunnan Province, China. As mining activities have continued to progress, varying degrees of deformation have occurred in different areas of the Buzhaoba open-pit mine, threatening normal coal production and mine safety. To comprehensively investigate the characteristics of surface deformation and its influencing factors at the Buzhaoba open-pit mine, this study employed the following methods: first, the SBAS-InSAR technique was used to process 86 Sentinel-1A ascending and descending orbit remote sensing images from 2020 to 2023, obtaining LOS surface deformation information for the mining area; second, leveling observation data were used to validate the accuracy of the SBAS-InSAR results, and based on the principle of two-dimensional deformation decomposition, the east–west and vertical surface deformation information of the mining area was obtained; finally, the temporal variation characteristics and influencing factors of the Buzhaoba open-pit mine were analyzed. The study results indicate that (1) the maximum LOS surface deformation rates in the ascending and descending orbits of the mining area were −42.1 mm/a and −114.0 mm/a, respectively; (2) the correlation coefficient between the SBAS-InSAR monitoring results and the leveling observation results was 0.938, confirming the reliability of the SBAS-InSAR monitoring results; (3) the maximum east–west and vertical deformation rates obtained from the two-dimensional deformation decomposition were −103.4 mm/a and −189.2 mm/a, respectively, with the surface deformation in the east–west direction being more pronounced; (4) internal factors such as stratigraphic lithology and geological structures, as well as atmospheric rainfall, have a certain degree of influence on the surface deformation of the Buzhaoba open-pit mine. Therefore, the research results of this study can provide important data support and theoretical references for safety management and disaster prevention in the mining area.

Spatiotemporal Evolution Analysis of Surface Deformation on the Beihei Highway Based on Multi-Source Remote Sensing Data

Under the interference of climate warming and human engineering activities, the degradation of permafrost causes the frequent occurrence of geological disasters such as uneven foundation settlement and landslides, which brings great challenges to the construction and operational safety of road projects. In this paper, the spatial and temporal evolution of surface deformations along the Beihei Highway was investigated by combining the SBAS-InSAR technique and the surface frost number model after considering the vegetation factor with multi-source remote sensing observation data. After comprehensively considering factors such as climate change, permafrost degradation, anthropogenic disturbance, and vegetation disturbance, the surface uneven settlement and landslide processes were analyzed in conjunction with site surveys and ground data. The results show that the average deformation rate is approximately −16 mm/a over the 22 km section of the study area. The rate of surface deformation on the pavement is related to topography, and the rate of surface subsidence on the pavement is more pronounced in areas with high topographic relief and a sunny aspect. Permafrost along the roads in the study area showed an insignificant degradation trend, and at landslides with large surface deformation, permafrost showed a significant degradation trend. Meteorological monitoring data indicate that the annual minimum mean temperature in the study area is increasing rapidly at a rate of 1.266 °C/10a during the last 40 years. The occurrence of landslides is associated with precipitation and freeze–thaw cycles. There are interactions between permafrost degradation, landslides, and vegetation degradation, and permafrost and vegetation are important influences on uneven surface settlement. Focusing on the spatial and temporal evolution process of surface deformation in the permafrost zone can help to deeply understand the mechanism of climate change impact on road hazards in the permafrost zone.

Triggering of Land Subsidence in and Surrounding the Hangjiahu Plain Based on Interferometric Synthetic Aperture Radar Monitoring

In the early stages, uncontrolled groundwater extraction led to the Hangjiahu (HJH) Plain becoming one of the areas with the most severe land subsidence in China. Since the beginning of this century, comprehensive measures have been taken to control the continuous aggravation of large land subsidence patterns in some areas; however, urban land subsidence issues, influenced by various factors, still persist and exhibit complex geographical distribution characteristics. In this study, we utilized Sentinel-1A images and the SBAS-InSAR technique to capture surface deformation over the HJH Plain in Zhejiang from 16 March 2017 to 20 January 2023. Through a comparative analysis with geological conditions, changes in surface mass loading, rainfall and groundwater, and land use types, we discussed the contributions of natural and anthropogenic factors to land subsidence. Augmented with optical remote sensing images and field investigations, we conducted a correlation analysis of the land subsidence status. The preliminary findings suggest that changes in surface mass loading and short-term heavy rainfall under extreme weather conditions can lead to periodic land subsidence changes in the region. Additionally, extensive infrastructure construction triggered by urbanization has resulted in significant and sustained land subsidence deformation. The research findings play an important guiding role in formulating scientifically effective strategies for land subsidence prevention and control, as well as urban planning and construction.

Integrated Assessment of Coastal Subsidence in Nansha District, Guangzhou City, China: Insights from SBAS-InSAR Monitoring and Risk Evaluation

Monitoring and assessing coastal subsidence is crucial to mitigating potential disaster risks associated with rising sea levels. Nansha District in Guangzhou City, representing global coastal soft-soil urban areas, faces significant challenges related to ground subsidence. However, the current understanding of the status, causative factors, and risk (includes subsidence susceptibility and vulnerability) assessment of ground subsidence in Nansha District is unclear. To address this gap, we utilized the SBAS-InSAR technique, analyzing 49 Sentinel-1A images from December 2015 to June 2019, for systematic ground subsidence monitoring. Subsequently, we assessed subsidence risk using a comprehensive index method and a risk matrix. Our findings indicate that subsidence velocity primarily ranged from −40 to −5 mm/a, with a spatial pattern of increasing subsidence from inland to coastal areas. The cumulative subsidence process unfolded in four distinct stages. The genesis of land subsidence was linked to an endogenous geological context dominated by soft-soil deposition, influenced by external factors such as surface loading and groundwater extraction. High-risk zones were concentrated in key engineering development areas, transportation pipeline trunk lines, and densely populated regions, demanding special attention. This study provides a foundational resource for disaster prevention and control strategies in Nansha District and similar coastal cities.

InSAR time series analysis of natural and anthropogenic coastal plain subsidence: A case of Hangjiahu plain

The early excessive groundwater exploitation caused extensive land subsidence in the Hangjiahu Plain (HJHP), threatening geological stability and infrastructure. Government restrictions on groundwater exploitation led to considerable changes in surface subsidence. To explore the distribution and causes of surface deformation after restrictions on groundwater exploitation, we used 46 Sentinel-1A TOPS images to detect the spatiotemporal distribution of surface deformation in the HJHP area from January 2019 to October 2022 by SBAS-InSAR technique and verified it with leveling results. Results indicated the following: (1) The uneven surface subsidence in the HJHP was relatively apparent, with the localized subsidence concentrated in a few areas. During InSAR monitoring, the maximum subsidence velocity reached −21.0 mm/yr. The most severe subsidence area was in the Shengze town industrial park, with remarkable subsidence bowls and a maximum subsidence of −85.8 mm. (2) Results were verified by comparing the InSAR results with leveling, and the results were in good agreement, indicating the reliability of the InSAR results. (3) Comprehensive analysis of the spatial distribution characteristics of surface subsidence, geological data and rainfall changes revealed that fault activity and rainfall changes had varying degrees of effect on surface subsidence in the HJHP area. (4) The comparison with land use data indicated that the built area was the dominant mechanism of surface subsidence in the study area. In addition, the effect of industrial activities on the surface cannot be ignored. The study results provide scientific data support for emergency disaster prevention work in the HJHP.

Urbanization and land subsidence: multi-decadal investigation combined SBAS-InSAR and multi-factors in Shanghai, China

Situated in the Yangtze River Delta’s alluvial plain, Shanghai has faced intensified land subsidence problems since the economic reforms of the 1990s. However, previous studies have lacked long time-series land subsidence monitoring and an analysis of multifactorial interactions in Shanghai over the past years. This study analyzed Shanghai’s land subsidence from 1992 to 2020 using SAR data from ERS-1/2, ENVISAT ASAR, and Sentinel-1A, applying the SBAS-InSAR technique. The geo-detector method was used to identify key factors affecting land subsidence, including groundwater, urban structure, metro development, and population dynamics. The results showed that (1) the utilization of multi-sensor SAR data enables the comprehensive analysis of urban land subsidence over an extended temporal series, facilitating the acquisition of its spatiotemporal distribution; (2) the extent of subsidence in Shanghai was gradually spreading from the core to the outskirts, and the rate of subsidence was gradually decreasing during 1992-2020 period; (3) groundwater was the most influential factor on land subsidence, and the interaction between groundwater and metro had a stronger influence on land subsidence.

Surface Subsidence over a Coastal City Using SBAS-InSAR with Sentinel-1A Data: A Case of Nansha District, China

The loss of life and property in economically developed areas due to geological hazards caused by intense ground subsidence is incalculable. As one of the fastest growing areas in the Guangdong-Hong Kong-Macao Greater Bay Area, the study of ground subsidence in Nansha will help to provide a scientific basis for urban planning and improve the capacity of monitoring and prevention of ground subsidence. The combination of coastal soft soil foundation and urbanization conditions creates a certain risk of land subsidence. We chose Nansha District, the geographical center of the Greater Bay Area, as the study area to analyze its surface subsidence characteristics in recent years. The 20-view Sentinel-1A data and SBAS-InSAR technique were used to monitor the ground subsidence in Nansha from 2017 to 2023. The main rate of ground subsidence in Nansha ranges from −19.4 to 7.7 mm/yr and is distributed in the urban area, along the rivers, in the construction area, and in the reclamation area. As of 4 May 2023, the average ground settlement in Nansha is 10.05 mm and the maximum settlement can be up to 142.45 mm. The 6-year total settlement at all four settlement intensities is greater than 60 mm, with the highest value exceeding 110 mm. The cumulative settlement increases with time, but inverse settlement and no settlement also occur at points where settlement is severe. For settlement caused by soft soil consolidation, it is recommended that drainage pipes be installed to accelerate drainage as a means of stabilizing settlement. For settlement caused by groundwater extraction and additional loads on the road surface, it is recommended to rationally extract groundwater and reinforce the foundation of the road surface with severe settlement.

Multi-temporal InSAR and Sentinel-1 for assessing land surface movement of Joshimath town, India

This study deals with the spatio-temporal measurement of land movement in Joshimath town using multi-temporal SBAS-InSAR technique. A network of 424 small-baseline interferograms was generated using 111 Sentinel-1 images acquired during May 2019–April 2023. Spatial distribution of line of sight displacement (LOSD) shows south-eastern Pekamarwadi, southern Gandhinagar and central Sunil wards are majorly affected; Manoharbagh, Singhdhar, and Lowerbazar moderately affected; northern Ravigram minor affected; and Parsari ward has no sign of land movement during investigation period. The observed negative values of mean LOS velocity and acceleration in southern Gandhinagar and central Sunil indicate these patchy areas are still susceptible and riskier for land stability. The SBAS-InSAR results were validated with CORS data during January 2022–March 2023. Trends show the gradual increase in LOSD from January to November 2022, rapid increase started from November 2022 and nearly ended mid January 2023, which indicates the initiation of movement stabilization. Accuracy assessment was performed in terms of Nash–Sutcliffe efficiency coefficient (NSE), R 2 , RMSE, and MAE, and the estimated values are 0.9896, 0.9495, 1.7534 cm, and 1.4028 cm, respectively. The analysis supports that CORS and SBAS-InSAR observed LOSD are in good agreement and reveals the true story of the land movement of Joshimath.

An Approach for Monitoring Shallow Surface Outcrop Mining Activities Based on Multisource Satellite Remote Sensing Data

Monitoring mine activities can help management track the status of mineral resource exploration and mine rehabilitation. It is crucial to the sustainable development of the mining industry and the protection of the geological environment in mining areas. To monitor the mining activities of shallow surface outcrops in the arid and semi-arid regions of northwest China, this paper proposes a remote sensing monitoring approach of mining activities based on deep learning and integrated interferometric synthetic aperture radar technique. This approach uses the DeepLabV3-ResNet model to identify and extract the spatial location of the mine patches and then uses object-oriented analysis and spatial analysis methods to optimize the mine patch boundaries. SBAS-InSAR technique is used to obtain the time-series deformation information of the mine patches and is combined with the multi-temporal optical imagery to analyze the mining activities in the study area. The proposed approach has a recognition accuracy of 95.80% for the identification and extraction of mine patches, with an F1-score of 0.727 at the pixel level, and the average area similarity for all patches is 0.78 at the object-oriented level. The proposed approach possesses the capability to analyze mining activities, indicating promising prospects for engineering applications. It provides a reference for monitoring mining activities using multisource satellite remote sensing.

Monitoring and analysis of surface deformation in alpine valley areas based on multidimensional InSAR technology

Joshimath has received much attention for its massive ground subsidence at the beginning of the year. Rapid urbanization and its unique geographical location may have been one of the factors contributing to the occurrence of this geological disaster. In high mountain valley areas, the complex occurrence mechanism and diverse disaster patterns of geological hazards highlight the inadequacy of manual monitoring. To address this problem, the inversion of deformation of the Joshimath surface in multiple directions can be achieved by multidimensional InSAR techniques. Therefore, in this paper, the multidimensional SBAS-InSAR technique was used to process the lift-track Sentinel-1 data from 2020 to 2023 to obtain the two-dimensional vertical and horizontal deformation rates and time series characteristics of the Joshimath ground surface. To discover the causes of deformation and its correlation with anthropogenic activities and natural disasters by analyzing the spatial and temporal evolution of surface deformation. The results show that the area with the largest cumulative deformation is located in the northeastern part of the town, with a maximum cumulative subsidence of 271.2 mm and a cumulative horizontal movement of 336.5 mm. The spatial distribution of surface deformation is based on the lower part of the hill and develops towards the upper part of the hill, showing a trend of expansion from the bottom to the top. The temporal evolution is divided into two phases: gentle to rapid, and it is tentatively concluded that the decisive factor that caused the significant change in the rate of surface deformation and the early onset of the geological subsidence hazard was triggered by the 4.7 magnitude earthquake that struck near the town on 11 September 2021.

Monitoring Ground Displacement in Mining Areas with Time-Series Interferometric Synthetic Aperture Radar by Integrating Persistent Scatterer/Slowly Decoherent Filtering Phase/Distributed Scatterer Approaches Based on Signal-to-Noise Ratio

During the interferometric synthetic aperture radar (InSAR)-based ground displacement monitoring in mining areas, the overlying land is mainly covered by low vegetation and arable land, which makes interferograms acquired by InSAR techniques easily susceptible to decorrelation, resulting in the quantity and density of highly coherent points (CPs) are not enough to reflect the spatial location and spatio-temporal evolution process of ground displacement, which is hardly meeting requirements of high-precision ground displacement monitoring. In this study, we developed an approach for monitoring ground displacement in mining areas by integrating Persistent Scatterer (PS), Slowly Decoherent Filtering Phase (SDF), and Distributed Scatterer (DS) based on signal-to-noise ratio (SNR) to increase the spatial density of CPs. A case study based on a mining area in Heze was carried out to verify the reliability and feasibility of the proposed method in practical applications. Results showed that there were four significant displacement areas in the study area and the quantity of CPs acquired by the proposed method was maximum 6.7 times that of conventional PS-InSAR technique and maximum 2.3 times that of SBAS-InSAR technique. The density of CPs acquired by the proposed method increased significantly. The acquired ground displacement information of the study area was presented in more detail. Moreover, the monitoring results were highly consistent with ground displacement results extracted by PS-InSAR and SBAS-InSAR methods in terms of displacement trends and magnitudes.

Locating and characterizing potential rainfall-induced landslides on a regional scale based on SBAS-InSAR technique

Locating and characterizing potential rainfall-induced landslides on a regional scale based on SBAS-InSAR technique

Land Subsidence in a Coastal City Based on SBAS-InSAR Monitoring: A Case Study of Zhuhai, China

The superimposed effects of sea level rise caused by global warming and land subsidence seriously threaten the sustainable development of coastal cities. In recent years, an important coastal city in China, Zhuhai, has been suffering from severe and widespread land subsidence; however, the characteristics, triggers, and vulnerability assessment of ground subsidence in Zhuhai are still unclear. Therefore, we used the SBAS-InSAR technique to process 51 Sentinel-1A images to monitor the land subsidence in Zhuhai during the period from August 2016 to June 2019. The results showed that there was extensive land subsidence in the study area, with a maximum rate of −109.75 mm/yr. The surface had sequentially undergone a process of minor uplift and decline fluctuation, sharp settlement, and stable subsidence. The distribution and evolution of land subsidence were controlled by tectonic fractures and triggered by the thickness of soft soil, the intensity of groundwater development, and the seasonal changes of atmospheric precipitation. The comprehensive index method and the analytic hierarchy process were applied to derive extremely high subsidence vulnerability in several village communities and some traffic arteries in Zhuhai. Our research provides a theoretical basis for urban disaster prevention in Zhuhai and the construction planning of coastal cities around the world.

SBAS-InSAR-Based Landslide Susceptibility Mapping Along the North Lancang River, Tibetan Plateau

Landslides pose huge challenges to the economic activities in mountainous areas at present, while large numbers of landslide disasters have developed in the Hengduan Mountains area in the eastern part of the Tibetan Plateau. Accurate landslide susceptibility mapping (LSM) serves as a critical measure to predict the serious risks that may be encountered in engineering activities. However, previous landslide susceptibility assessment can only play a limited role in the real-time analysis of current activities of slopes. In this study, the deformation rates of the slopes along the Lancang River were determined using the SBAS-InSAR technique. Meanwhile, the landslide susceptibility along the north Lancang River was assessed using the frequency ratio (FR), random forest and FR-RF models, and the precision of the assessment results was verified according to receiver operating characteristic curves (ROCs). Finally, a refined landslide susceptibility map was developed by integrating the deformation rates and landslide susceptibility indexes (LSIs) using a contingency matrix. As indicated by the deformation rates calculated using the SBAS-InSAR technique according to ascending and descending data show that the RADARSAT-2 descending data yielded more precise deformation results. The area-under-the-curve (AUC) values of the three assessment models were 0.866, 0.897, and 0.916, respectively, indicating that the assessment results obtained with the FR-RF model are the most precise. In the upgraded landslide susceptibility map, the areas with high and very high landslide susceptibility increased by 2.97%. Meanwhile, a total of 563,430 grid cells showed an increase in landslide susceptibility, accounting for 11.15% of all the grid cells. Most especially, the Xueru and Ritong areas exhibited a significant increase in landslide susceptibility, and it has been verified by remote sensing images and field surveys that both areas are subject to landslide risks. Therefore, the upgraded landslide susceptibility map has a better prediction performance and can provide valuable support for the decision making in the construction of major engineering facilities and the prevention and remediation of landslides.

Investigation of Sentinel-1-derived land subsidence using wavelet tools and triple exponential smoothing algorithm in Lagos, Nigeria

Lagos has a history of long-term groundwater abstraction that is often compounded by the rising indiscriminate siting of private borehole and water well. This has resulted in various forms of environmental degradation, including land subsidence. Prediction of the temporal evolution of land subsidence is central to successful land subsidence management. In this study, a triple exponential smoothing algorithm was applied to predict the future trend of land subsidence in Lagos. Land subsidence time series was computed with SBAS-InSAR technique with Sentinel-1 acquisitions from 2015 to 2019. Besides, Matlab wavelet tool was implemented to investigate the periodicity within land displacement signal components and to understand the relationship between the observed land subsidence, and groundwater level change and that of soil moisture. Results show that land subsidence in the LOS direction varied approximately between − 94 and 15 mm/year. According to the wavelet-based analysis result, land subsidence in Lagos is partly influenced by both groundwater-level fluctuations and soil moisture variability. Evaluation of the proposed model indicates good accuracy, with the highest residual of approximately 8%. We then used the model to predict land subsidence between the years 2020 and 2023. The result showed that by the end of 2023 the maximum subsidence would reach 958 mm, which is approximately a 23% increase.

LARGE-SCALE SUBSIDENCE GEOHAZARD MONITORING WITH SENTINEL-1 SAR INTERFEROMETRY IN CENTRAL LISHUI (CHINA)

Abstract. Ground subsidence has become a serious problem along with the rapid urban expansions. Compared with traditional point-based ground survey techniques (GPS, levelling measurement and in-situ sensors), SAR Interferometry are quite appreciated for large-scale subsidence monitoring with long term and high accuracy. In this study, we focused on large-scale subsidence geohazard monitoring of central Lishui (China) and extracted subsidence velocity map of Liandu District. 57 Sentinle-1 SAR images from April 2019 to September 2020 are analysed with SBAS-InSAR technique. The overall subsidence of Liandu is significantly correlated with the distributions of construction engineering sites with displacement velocity of approximately 30–60 mm/yr. Various types of urban ground subsidence could be identified, including the overall settlement of large construction site, the slope deformation of construction excavation, significant settlement of refuse landfill and mountain crossing tunnel, and small deformation of highvoltage towers in mountainous areas. Our results indicated that the rapid urban developments are the dominant impact factors of subsidence in Lishui, China.

Flood Inundation Analysis in Penang Island (Malaysia) Based on InSAR Maps of Land Subsidence and Local Sea Level Scenarios

Penang Island is an important economic center in Malaysia and most of its population live in the coastal areas. Although previous studies have shown that it is vulnerable to rising sea levels, the combination of sea-level rise and local land subsidence would be devastating. Therefore, the objective of this study is to apply the local land subsidence model to estimate the inundated areas which relate to sea level rise by 2100. Land subsidence is quantified by the SBAS-InSAR technique on the basis of Sentinel-1 radar images for both ascending and descending tracks. For the first time, the geostatistical analyst method is used to merge the different track results and create the land subsidence models, the results show this method can maximize land deformation fields and minimize deformation errors. According to the land deformation results, all of the coastlines in the east of the island have differing medium levels of subsidence, especially in reclaimed lands and building areas. Lastly, the bathtub model is used to quantify the inundated areas by combing regional sea-level rise projection and local land subsidence models under CoastalDEM in 2100 projections. The results of this study indicate land subsidence that would increase 2.0% and 5.9% of the inundated area based on the different scenarios by 2100 projections.

Surface subsidence monitoring in mining area of SBAS-InSAR based on Sentinel-1A

In this study, the surface subsidence caused by underground mining is monitored by the technique of SBAS-InSAR. The second west mining area of Longshou mine, Jinchang Jinchuan Cu-Ni sulfide mine, Gansu province, is selected as the research area for the experiment. The 29 scene elevation rail Sentinel-1A image data from 2019.03-2020.3 are analyzed for the sequence analysis of the SBAS-InSAR. The vertical subsidence rate and cumulative subsidence results of the surface sequence of the mining area are obtained. According to the study, the minimum error of cumulative sedimentation between SBAS-InSAR and D-InSAR is 0.1mm, the maximum error is 21.37mm, and the median error is ±6.65mm. The minimum error of cumulative settlement between SBAS-InSAR and levelling is 0.66mm, the maximum is 23.74mm, and the median error is ±10.79mm. The results show that the application of the SBAS-InSAR technique in the monitoring of surface subsidence in the mining area is reliable, which provides an important basis for the subsequent safe mining in the mining area.

A New Method to Predict Gully Head Erosion in the Loess Plateau of China Based on SBAS-InSAR

Gully head erosion causes serious land degradation in semiarid regions. The existing studies on gully head erosion are mainly based on measuring the gully volume in small-scale catchments, which is a labor-intensive and time-consuming approach. Therefore, it is necessary to explore an accurate method quantitatively over large areas and long periods. The objective of this study was to develop a model to assess gully head erosion in the Loess Plateau of China using a method based on the SBAS-InSAR technique. The gully heads were extracted from the digital elevation model and validated by field investigation and aerial images. The surface deformation was estimated with SBAS-InSAR and 22 descending ALOS PALSAR datasets from 2007 to 2011. A gully head erosion model was developed; this model can incorporate terrain factors and soil types, as well as provides erosion rate predictions consistent with the SBAS-InSAR measurements (R2 = 0.889). The results show that gully head erosion significantly depends on the slope angle above the gully head, slope length, topographic wetness index, and catchment area. The relationship between these factors and the gully head erosion rate is a power function, and the average rate of gully head erosion is 7.5 m3/m2/year, indicating the high erosional vulnerability of the area. The accuracy of the model can be further improved by considering other factors, such as the stream power factor, curvature, and slope aspect. This study indicates that the erosion rate of gully heads is almost unaffected by soil type in the research area. An advantage of this model is that the gully head area and surface deformation can be easily extracted and measured from satellite images, which is effective for assessing gully head erosion at a large scale in combination with SBAS-InSAR results and terrain attributes.

Extraction and analysis of saline soil deformation in the Qarhan Salt Lake region (in Qinghai, China) by the sentinel SBAS-InSAR technique

The instability of saline soil foundation affects the safety of artificial construction, and may cause ground collapse, building destruction and road damage. It is fundamental to reduce the potential engineering geological disasters by exploring the dynamic evolution of saline soil. Most of the previous researches of saline soil were conducted by simulated experiments and traditional geodetic surveying methods. Restricted to the limited sampling points, the spatiotemporal evolution characteristics of saline soil were difficult to find out in a large scale. This paper exploited SBAS-InSAR method to extract the deformation of the Qarhan Salt Lake (in Qinghai, China) section along Qinghai-Tibet railway, based on 119 image data acquired by Sentinel-1A from 2015 to 2020. The results showed that the deformation trends varied frequently in this saline mud flat. Between the adjacent areas with different deformation trends along Qinghai-Tibet railway, discontinuities caused by uplift and subsidence were very obvious. Besides, among the areas with brine exploitation or artificial construction, the maximum subsidence rate reached50 mm/yr, and the maximum cumulative subsidence exceeded 320 mm in the latest 5 years. In the saline mud flat closed to the rivers and lakes, the deformation trend was continuous uplift. Nevertheless, there were obvious seasonal deformation characteristics in those areas far away from the water body. Further analysis found out a sharply subsidence caused by the salt collapsibility appeared in rainy seasons. While an uplift trend induced by the salt swelling or frost heave was remarkable in dry seasons. Subsequently, the relationships were analyzed between the time series deformation and external environmental factors. Furthermore, the deformation mechanism of saline soilin the Qarhan Salt Lake region was interpreted then. In general, this study provides complete spatiotemporal evolution information of saline soil, and demonstrates the deformation characteristics of saline soil in the Qarhan Salt Lake region successfully. Related results would contribute to the safety monitoring for large-scale infrastructure construction in the saline soil areas.