Subsidence Velocity Research Articles

Surface Dynamic Damage Prediction Model of Horizontal Coal Seam Based on the Idea of Wave Lossless Propagation.

According to traditional concepts, the movement of overlying strata and surface damage caused by coal mining in horizontal coal seams are symmetrical in terms of spatial distribution. However, in a lot of engineering practices, this symmetry has not been discovered. We often use the symmetry function to establish the profile prediction function of the surface damage, which results in a large difference between the prediction result and the actual situation. To solve this problem, this paper takes subsidence velocity as an example. Firstly, the spatial distribution functions of subsidence velocity on both sides were deduced theoretically. Through comparison, it is found that the change rate of the spatial distribution curve of the coal pillar side subsidence velocity is smoother than that of the goaf side and the subsidence velocity curves are skewed to the left. Secondly, based on the idea of lossless propagation of harmonic waves and idealizing the propagation environment, the spatial propagation relationship of surface subsidence velocity in the time domain is established. Then, the Box–Cox transform function is introduced to improve the normal distribution probability density function, and a new dynamic subsidence prediction model based on the Box–Cox transformation is obtained, which is suitable for the full mining stage. The model is tested by practical cases, the prediction accuracy is better than 7%, and the prediction results can meet the needs of engineering prediction accuracy (10%). The results of this research can enrich the existing subsidence prediction theory and provide theoretical and technical support for the prediction of dynamic surface damage caused by similar mining.

Earthquake-induced landslide monitoring and survey by means of InSAR

Abstract. This study uses interferometric synthetic aperture radar (SAR) techniques to identify and track earthquake-induced landslides as well as lands prone to landslides, by detecting deformations in areas struck by earthquakes. The pilot study area investigates the Mila region in Algeria, which suffered significant landslides and structural damage (earthquake: Mw 5, 7 August 2020). DInSAR analysis shows normal interferograms with small fringes. The coherence change detection (CCD) and DInSAR analysis were able to identify many landslides and ground deformations also confirmed by Sentinel-2 optical images and field inspection. The most important displacement (2.5 m), located in the Kherba neighborhood, caused severe damage to dwellings. It is worth notice that CCD and DInSAR are very useful since they were also able to identify ground cracks surrounding a large zone (3.94 km2 area) in Grarem City, whereas the Sentinel-2 optical images could not detect them. Although displacement time-series analysis of 224 interferograms (April 2015 to September 2020) performed using LiCSBAS did not detect any pre-event geotechnical precursors, the post-event analysis shows a 110 mm yr−1 subsidence velocity in the back hillside of Kherba.

Use of InSAR in Linear Discontinuous Ground Deformation Generation Analysis: Case Study of a Mine in Poland

Linear Discontinuous Ground Deformations are defined as fissures and steps, as well as structural forms composed of them. They occur on the surface as a result of underground mining. Knowledge of LDGDs has been acquired through field observations which are subsequently described in the scientific publication. Records of LDGDs are made by using the classic surveying method. The paper reviews the created LDGDs in the years 2015–2019 in one of the mines of the USCB. The analysis covers the velocity of subsidence as a result of underground mining and the values of horizontal strains determined according to the Knothe-Budryk theory. The InSAR satellite technique was used to measure the subsidence. The subsidence was determined using the small baseline method – SBAS. The combination of the theoretical Knothe-Budryk model with the large-scale capabilities of InSAR may provide valuable material for a better understanding of the genesis of LDGD creation and their prediction.

Development of a mathematical model to monitoring the velocity of subsidence of charge material column in the blast furnace based on the parameters of gas pressure in the furnace tract

A problem of estimating the velocity of subsidence of a column of charge materials using non-contact methods was considered. This is important because the level of furnace charge materials and the velocity of their subsidence are main indicators of melting intensity determining the furnace productivity. The design of a blast furnace and its blast path were described and existing methods and means of controlling the velocity of charge materials in the blast furnace were analyzed. A mathematical model was presented for estimating the velocity of subsidence of charge materials in a blast furnace based on the magnitude and fluctuations of gas pressure along the furnace shaft height. The model is based on the fact that the furnace gases rise up in the furnace shaft through elementary channels in the column of charge materials consisting of a combination of capacitances and resistances. Volume of capacities and values of resistance of elementary channels are constantly changing. This changes hydraulic resistance to gas movement in the blast furnace. The system of differential equations describes the dependence of the amplitude of pressure fluctuations on the amplitude of change in coefficients of resistance and frequency of pressure fluctuations on the frequency of change in coefficients of resistance. The experimental data on velocity of the column of charge materials and fluctuations in the pressure differential in the furnace were processed and their significant relationship was shown to confirm the previous theoretical study results. To assess the model adequacy, the simulation method was used. The results of the simulation model work were confirmed by experimental data. The developed mathematical model can be introduced into production. This will make it more economical and safer through better and more predictable control and improved flexibility in operation under different production conditions.

Evolution Assessment of Mining Subsidence Characteristics Using SBAS and PS Interferometry in Sanshandao Gold Mine, China

Ground subsidence is a common geological phenomenon occurring in mining areas. As an important Chinese gold mine, Sanshandao Gold Mine has a mining history of 25 years, with remarkable ground subsidence deformation. Mining development, life security, property security and ecological protection all require comprehension of the ground subsidence characteristics and evolution in the mining area. In this study, the mining subsidence phenomenon of the Sanshandao Gold Mine was investigated and analyzed based on Persistent Scatterer Interferometry (PSI) and small baseline subset (SBAS). The SAR (synthetic aperture radar) images covering the study area were acquired by the Sentinel-1A satellite between 2018 and 2021; 54 images (between 22 February 2018 and 25 May 2021) were processed using the PSI technique and 24 images (between 11 April 2018 and 12 July 2021) were processed using the SBAS technique. In addition, GACOS (generic atmospheric correction online service) data were adopted to eliminate the atmospheric error in both kinds of data processing. The interferometric synthetic aperture radar (InSAR) results showed a basically consistent subsidence area and a similar subsidence pattern. Both InSAR results indicated that the maximum LOS (line of sight) subsidence velocity is about 49 mm/year. The main subsidence zone is situated in the main mining area, extending in the northwest and southeast directions. According to the subsidence displacement of several representative sites in the mining area, we found that the PSI result has a higher subsidence displacement value compared to the SBAS result. Mining activities were accompanied by ground subsidence in the mining area: the ground subsidence phenomenon is exacerbated by the increasing mining quantity. Temporally, the mining subsidence lags behind the increase in mining quantity by about three months. In summary, the mining area has varying degrees of ground subsidence, monitored by two reliable time-series InSAR techniques. Further study of the subsidence mechanism is necessary to forecast ground subsidence and instruct mining activities.

Land Subsidence in Beijing’s Sub-Administrative Center and Its Relationship with Urban Expansion Inferred from Sentinel-1/2 Observations

Beijing’s Sub-Administrative Center (BSAC) is located in the South-eastern Beijing Plain, which exhibits severe subsidence. The rapid urban expansion in recent years has aggravated land subsidence and threatens the safe operation of Beijing. First, this study applied the persistent scatterer-interferometric synthetic aperture radar (PS-InSAR) to extract BSAC subsidence time series data. Second, combined with the index-based built-up index (IBI), expansion intensity index (EII), and expansion gradient index (EGI), the spatiotemporal characteristics of urban expansion were retrieved from optical data. Finally, we examined the urban expansion effects on land subsidence at the regional and single-building scales. The results showed that the maximum subsidence velocity in the BSAC reached 121 mm/year from 2015 to 2018, and the urban construction land area increased by 22%. At the regional scale, there existed a positive correlation between land subsidence and EGI or EII. This indicated that urban expansion had a certain impact on land subsidence. Therefore, we further explored the relationship between construction and land subsidence at the single-building scale. The engineering construction effects on land subsidence were divided into three periods, namely, rapid settlement, rebound, and stable periods. Although construction had a significant influence on land subsidence, it did not cause subsidence mutation.

Multi-sensor remote sensing analysis of coal fire induced land subsidence in Jharia Coalfields, Jharkhand, India

The subsidence in coal mines induced by surface and subsurface fires leading to roof collapse, infrastructure loss, and loss of lives is a prominent concern. In the study, satellite imagery from thermal and microwave remote sensing data is used to deduce the effect of coal fires on subsidence in the Jharia Coalfields, India. The Thermal Infrared data acquired from the Landsat-8 (band 10) is used to derive the temperature anomaly maps. Persistent Scatterer Interferometry analysis was performed on sixty Sentinel-1, C-band images, the results are corrected for atmospheric error using Generic Atmospheric Correction Online Service for InSAR (GACOS) atmospheric modelling data and decomposed into vertical displacement values to quantify subsidence. A zone-wise analysis of the hazard patterns in the coalfields was carried out. Coal fire maps, subsidence velocity maps, and land cover maps were integrated to investigate the impact of the hazards on the mines and their surroundings. Maximum subsidence of approximately 20 cm/yr. and temperature anomaly of up to 25 °C has been observed. The findings exhibit a strong positive correlation between the subsidence velocity and temperature anomaly in the study area. Kusunda, Keshalpur, and Bararee collieries are identified as the most critically affected zones. The subsidence phenomenon in some collieries is extending towards the settlements and transportation networks and needs urgent intervention.

Monitoring, analyzing and predicting urban surface subsidence: A case study of Wuhan City, China

Wuhan, one of China's megacities with rapid development, is facing serious surface subsidence. In this study, we combined MT-InSAR, geo-detector, and LSTM (Long Short-Term Memory) to achieve the monitoring, analysis, and prediction of surface subsidence in the main urban districts of Wuhan. The effectiveness of MT-InSAR in monitoring surface subsidence was validated against leveling results. During the monitoring period, the maximum subsidence velocity and uplift velocity were −53.3 mm/year and 18.0 mm/year, respectively. We identified six subsidence regions and explored their deformation characteristics. Further, we analyzed the relationship between the surface subsidence and influencing factors using the geo-detector in a quantitative manner. Our study revealed that the distance to soft soils had the greatest explanatory power on the subsidence. However, we also confirmed that subsidence was affected via coupling effects from multiple factors, suggesting a complex reinforcing relationship among influencing factors. The interaction between the distance to soft soils and the distance to karst collapse prone areas had the largest joint explanatory power on subsidence. Further, we constructed a data-driven LSTM model to predict and analyze the subsidence. The results showed that the LSTM model achieved great performance and presented strong universality, suggesting that it can be used for subsidence prediction in large geographic areas.

DInSAR Monitoring of Surface Subsidence by Fusing Sentinel-1A and -1B Data to Improve Time Resolution in a Mining Area

Monitoring large gradient ground deformation due to temporal and spatial image decoherence has long been a challenge. We attempted an improvement using Sentinel-1A and Sentinel-1B C-band data fusion methods based on the variation law of subsidence velocity of ground leveling monitoring points. This approach improved the temporal resolution from 12 to 6 days. Using a mine in Datong, Shanxi Province, China as an example, 13 scenes of Sentinel-1A data and 12 scenes of Sentinel-1B data were fused and compared with ground-measured data. The results obtained were closer to the measured values than those obtained by single data set (Sentinel-1A or -1B only). Simultaneously, 61 scenes of Sentinel-1A data and 12 scenes of Sentinel-1B data were used to calculate the subsidence of the mining area over two years. The subsidence map was consistent with the actual leveling trend, which reflected the dynamic change of surface subsidence range in the mining area. This study provides an approach using DInSAR technology to monitor large gradient deformation in mining areas and provides an effective method to monitor of surface dynamic deformation.

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.

Spatio-temporal linking of multiple SAR satellite data from medium and high resolution Radarsat-2 images

A recent development in Interferometric Synthetic Aperture Radar (InSAR) technology is integrating multiple SAR satellite data to dynamically extract ground features. This paper addresses two relevant challenges: identification of common ground targets from different SAR datasets in space, and concatenation of time series when dealing with temporal dynamics. To address the first challenge, we describe the geolocation uncertainty of InSAR measurements as a three-dimensional error ellipsoid. The points, among InSAR measurements, which have error ellipsoids with a positive cross volume are identified as tie-point pairs representing common ground objects from multiple SAR datasets. The cross volumes are calculated using Monte Carlo methods and serve as weights to achieve the equivalent deformation time series. To address the second challenge, the deformation time series model for each tie-point pair is estimated using probabilistic methods, where potential deformation models are efficiently tested and evaluated. As an application, we integrated two Radarsat-2 datasets in Standard and Extra-Fine modes to map the subsidence of the west of the Netherlands between 2010 and 2017. We identified 18128 tie-point pairs, 5 intersection types of error ellipsoids, 5 deformation models, and constructed their long-term deformation time series. The detected maximum mean subsidence velocity in Line-Of-Sight direction is up to 15 mmyr-1. We conclude that our method removes limitations that exist in single-viewing-geometry SAR when integrating multiple SAR data. In particular, the proposed time-series modeling method is useful to achieve a long-term deformation time series of multiple datasets.

Monitoring of Land Subsidence in the Po River Delta (Northern Italy) Using Geodetic Networks

The Po River Delta (PRD, Northern Italy) has been historically affected by land subsidence due to natural processes and human activities, with strong impacts on the stability of the natural ecosystems and significant socio-economic consequences. This paper is aimed to highlight the spatial and temporal evolution of the land subsidence in the PRD area analyzing the geodetic observations acquired in the last decade. The analysis performed using a moving window approach on Continuous Global Navigation Satellite System (CGNSS) time-series indicates that the velocities, in the order of 6 mm/year, are not affected by significant changes in the analyzed period. Furthermore, the use of non-permanent sites belonging to a new GNSS network (measured in 2016 and 2018) integrated with InSAR data (from 2014 to 2017) allowed us to improve the spatial coverage of data points in the PRD area. The results suggest that the land subsidence velocities in the easternmost part of the area of interest are characterized by values greater than the ones located in the western sectors. In particular, the sites located on the sandy beach ridge in the western sector of the study area are characterized by values greater than −5 mm/year, while rates of about −10 mm/year or lower have been observed at the eastern sites located in the Po river mouths. The morphological analysis indicates that the land subsidence observed in the PRD area is mainly due to the compaction of the shallow layers characterized by organic-rich clay and fresh-water peat.

Spatial‐Temporal Ground Deformation Study of Baotou Based on the PS‐InSAR Method

AbstractGround subsidence is an emerging geological hazard in Baotou, Inner Mongolia. Four areas of Baotou with relatively large subsidence range and rate were selected for analysis. Focusing on investigation of ground subsidence using PS‐InSAR technology, a total of 43 frames of ALOS PALSAR images yielded a SAR data span from December 2006 to January 2011, allowing ground subsidence scope, subsidence velocity, time‐series deformation to be obtained. Major causes and influencing factors of the ground subsidence are closely related to soft soil consolidation and compaction and the decrease in the level of groundwater caused by increased development and utilization of groundwater.

Adjacent-Track InSAR Processing for Large-Scale Land Subsidence Monitoring in the Hebei Plain

Large-scale land subsidence has threatened the safety of the Hebei Plain in China. For tens of thousands of square kilometers of the Hebei Plain, large-scale subsidence monitoring is still one of the most difficult problems to be solved. In this paper, we employed the small baseline subset (SBAS) and NSBAS technique to monitor the land subsidence in the Hebei Plain (45,000 km2). The 166 Sentinel-1A data of adjacent-track 40 and 142 collected from May 2017 to May 2019 were used to generate the average deformation velocity and deformation time-series. A novel data fusion flow for the generation of land subsidence velocity of adjacent-track is presented and tested, named as the fusion of time-series interferometric synthetic aperture radar (TS-InSAR) results of adjacent-track using synthetic aperture radar amplitude images (FTASA). A cross-comparison analysis between the two tracks results and two TS-InSAR results was carried out. In addition, the deformation results were validated by leveling measurements and benchmarks on bedrock results, reaching a precision 9 mm/year. Twenty-six typical subsidence bowls were identified in Handan, Xingtai, Shijiazhuang, Hengshui, Cangzhou, and Baoding. An average annual subsidence velocity over −79 mm/year was observed in Gaoyang County of Baoding City. Through the cause analysis of the typical subsidence bowls, the results showed that the shallow and deep groundwater funnels, three different land use types over the building construction, industrial area, and dense residential area, and faults had high spatial correlation related to land subsidence bowls.

Land subsidence estimation using DinSAR method ALOS PALSAR image in Padang City West Sumatra, Indonesia

Land subsidence is a phenomenon that occurs in big cities around the world and in Indonesia. Padang as one of the largest cities in West Sumatera also facing land subsidence due to natural phenomena and human induced. Padang City is located at the west coast of Sumatera Island which is the junction point of three active plates that cause frequent earthquakes. Main goals of this research are to know the distribution of area affected by land subsidence, to know the estimated value of land subsidence and to know the value of the velocity of land subsidence in Padang area using DInSAR method. The data used in this study is ALOS PALSAR Image Level 1.1 of Padang city during 2007 to 2010 was obtained through JMRSL CERES Chiba University, Japan and collected through Alaska Satellite Facility website. Differential Interferometric Synthetic Aperture Radar (DInSAR) is a technique considered to be one of the most efficient technique for detecting land subsidence. The DInSAR method is used in mapping altitude changes developed into a land-subsidence map each year. The mapping results show the distribution of the areas affected by the maximum land subsidence in Padang area of West Sumatera are Padang Utara, Nanggalo, and Padang Barat Subdistricts. The land subsidence insignificant occurred is Padang Selatan and Lubuk Begalung Subdistricts. The estimated value of the land subsidence distribution in Padang area using DInSAR method has decreased significantly after the earthquake of September 30, 2009 in Padang Utara, Nanggalo and West Padang Subdistricts is around 0 - 32.70 cm, and the value of land subsidence velocity is around 0.13 - 12 cm/year. One of the expected effects of land subsidence can be increased in the area susceptible for flooding in Padang city.

Land subsidence induced by underground coal mining at Quang Ninh, Vietnam: persistent scatterer interferometric synthetic aperture radar observation using Sentinel-1 data

ABSTRACT Land subsidence occurs in Ha Long and Cam Pha cities due to human activities in which the underground coal mining exploitation plays a crucial responsibility. For mapping the spatial distribution of this phenomenon and monitoring its evolution over the time, the Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) approach was applied to 56 Sentinel-1A images, captured from June 2015 to June 2019. This approach allows monitoring ground displacement by continuously measuring the position of objects that persistently scatter radar beams. This interferometric synthetic aperture radar (InSAR) technique extracts deformation signals and it can be applied to areas where the discontinuous land subsidence is occurring. The mean land subsidence velocity map shows that two principal areas in Ha Long city including Ha Lam, Ha Trung, Ha Khanh, and Ha Tu wards, and Cam Pha city, specifically Mong Duong ward have been subsided in recent years with the maximum velocity of 14.5 mm year−1 and a cumulative displacement ranging from 30 to 50 mm in the Line Of Sight (LOS) direction over 4 years. Field investigation recognized the direct impact of this phenomenon on houses, infrastructures, and natural features located above the underground coal mining utilities. This hazard has a close relationship with the exploiting process of coal seams, which alternately lay inside the sedimentary layers of the Hon Gai formation.

Land Subsidence and Its Relations with Sinkhole Activity in Karapınar Region, Turkey: A Multi-Sensor InSAR Time Series Study.

The Karapinar basin, located in the Central Anatolian part of Turkey, is subjected to land subsidence and sinkhole activity due to extensive groundwater withdrawal that began in the early 2000s. In this study, we use Interferometric Synthetic Aperture Radar (InSAR), Global Navigation Satellite System (GNSS), and groundwater level data to monitor and better understand the relations between groundwater extraction, land subsidence, and sinkhole formation in the Karapinar basin. The main observations used in the study are InSAR-derived subsidence velocity maps calculated from both Sentinel-1 (2014–2018) and COSMO-SkyMed (2016–2017) SAR data. Our analysis reveals broad areas of subsidence with rates exceeding 70 mm/yr. The InSAR-derived subsidence was compared with GNSS data acquired by a continuously operating GNSS station located in the study area, which show a similar rate of subsidence. The temporal characteristic of both InSAR and GNSS time series indicate a long-term subsidence signal superimposed by seasonal variability, which follows the overall groundwater level changes, with over 80% cross-correlation consistency. Our results also indicate that sinkhole activity is limited to slow subsidence areas, reflecting strong cohesion of near-surface rock layers that resist subsidence but yield to collapse in response to aquifer system deformation induced by groundwater extraction.

Investigating Ground Subsidence and the Causes over the Whole Jiangsu Province, China Using Sentinel-1 SAR Data

Interferometric synthetic aperture radar (InSAR) mapping of localized ground surface deformation has become an important tool to manage subsidence-related geohazards. However, monitoring land surface deformation using InSAR at high spatial resolution over a large region is still a formidable task. In this paper, we report a research on investigating ground subsidence and the causes over the entire 107, 200 km2 province of Jiangsu, China, using time-series InSAR. The Sentinel-1 Interferometric Wide-swath (IW) images of 6 frames are used to map ground subsidence over the whole province for the period 2016–2018. We present processing methodology in detail, with emphasis on the three-level co-registration scheme of S-1 data, retrieval of mean subsidence velocity (MSV) and subsidence time series, and mosaicking of multiple frames of results. The MSV and subsidence time series are generated for 9,276,214 selected coherent pixels (CPs) over the Jiangsu territory. Using 688 leveling measurements in evaluation, the derived MSV map of Jiangsu province shows an accuracy of 3.9 mm/year. Moreover, subsidence causes of the province are analyzed based on InSAR-derived subsidence characteristics, historical optical images, and field-work findings. Main factors accounting for the observed subsidence include: underground mining, groundwater withdrawal, soil consolidations of marine reclamation, and land-use transition from agricultural (paddy) to industrial land. This research demonstrates not only the capability of S-1 data in mapping ground deformation over wide areas in coastal and heavily vegetated region of China, but also the potential of inferring valuable knowledge from InSAR-derived results.

HLSTM: Heterogeneous Long Short-Term Memory Network for Large-Scale InSAR Ground Subsidence Prediction

Accurate prediction of ground subsidence is of great significance for the prevention and mitigation of this type of geological disaster. It is still a challenge when wide area is concerned. In this article, a heterogeneous long short-term memory (HLSTM) network is proposed for large-scale ground subsidence prediction based on interferometric synthetic aperture radar (InSAR) data. First, the study area is divided into homogeneous subregions through spatial clustering of InSAR-derived subsidence velocity. Second, a specific LSTM model is constructed to capture complex nonlinear temporal correlations embedded in InSAR-derived subsidence time series for each subregion. Essentially both spatial heterogeneity and temporal correlation are incorporated into the HLSTM prediction. In the experiment part, the HLSTM predictor is validated using a subsidence monitoring result from 80 Sentinel-1 images acquired over Cangzhou, China, from 2017 to 2019. The HLSTM result shows the highest prediction accuracy through comparisons with the results from other seven methods.

Monitoring coal seam fires in Xinjiang using comprehensive thermal infrared and time series InSAR detection

ABSTRACT The combustion of underground coal seams has important effects on the national economy and strategic energy security of countries, and damages the environment, ecology, vegetation, and water resources. Xinjiang, China, is one of the most serious areas of coalfield fires in the world, and it is difficult for any single remote sensing detection method to meet the practical requirements for accurate detection of fire areas. In order to detect coalfield areas in Xinjiang more accurately and reliably, a detection method that integrates thermal infrared and radar remote sensing anomaly is proposed: The mono-window algorithm is used to retrieve the Land Surface Temperature (LST) using images from the Land Remote-Sensing Satellite System (Landsat) 8, the Adaptive Edge Threshold Algorithm (AETA) is used to extract the data characterized by LST anomalies, and Small Baseline Subsets Interferometric Synthetic Aperture Radar (SBAS-InSAR) is used to obtain the land surface subsidence information from Sentinel-1A images. Through the overlay analysis of the above-mentioned LST and subsidence information, the extraction of possible coal fire areas in the Jiangjun Gobi area of Xinjiang is realized. As well as according to the characteristic that underground coal fires melt snow in winter, areas where coal fires are unlikely to occur are excluded using the natural, true-colour images of Landsat 8. Finally, the proposed method is verified using the characteristics of the time series cumulative subsidence of the land surface in areas where coal fires are likely to occur, and by examining the coupling between subsidence velocity and anomalies in LST data. The results show that the proposed method can overcome the shortcomings of single-factor remote sensing detection to a certain extent, and has the ability to detect fire areas more accurately.