DInSAR Method Research Articles

Utilization of Sentinel Image Multitemporal Data for Landslide Potential Identification in Pujon Sub-District

Landslides are one of the most common disasters in Indonesia. Landslides are often triggered by high rainfall and occur for several days. Unstable soil structure is very easy to experience landslides. The case study of this research is in Pujon Sub-district, Malang Regency. Pujon sub-district has a hilly and highland topography. Its hilly-mountainous relief and steep slopes cause Pujon Sub-district to experience frequent natural disasters, especially landslides. The research was conducted by processing Sentinel 1 image using DInSAR method to obtain data on land surface change and weighting scoring method to obtain information on landslide prone areas. The processing of DInSAR method produces the value of vertical land surface change. The largest increase in land surface with a displacement value of 0.2972 m. And the largest land subsidence is -0.2234 m. Such movement can be an indicator of landslide occurrence. The GIS method produces 3 classes of landslide vulnerability level, namely low, medium and high in each year in Pujon sub-district. The average landslide prone area in the last 5 years is 15081.1331 ha. The processing results of DInSAR method and weighting scoring method can describe the landslide prone areas in Pujon Sub-district which is expected to be useful for landslide mitigation efforts.

Impact of the Urbanization Process on the Subsidence Phenomena Using Remote Sensing in the Inner Districts of Ho Chi Minh City, Vietnam

Abstract Subsidence in Ho Chi Minh city (HCM city) occurs in many places, the current reason no longer comes from natural disasters but mainly from human activities (groundwater exploitation, ground improvement,…). Especially in innercity districts, during high tide or heavy rain, many areas are locally flooded, concentrated in places with high construction density. To monitor the subsidence phenomenon in urban areas, the advent of remote sensing technology is an effective tool, helping researchers and managers capture information quickly, accurately and continuously. In this study, the DInSAR method was used to determine the rate of subsidence in urban districts of HCM city. DInSAR is a popular method for estimating land displacement based on the principles of Interferometric Synthetic Aperture Radar (InSAR) using different time series data. We used C-band SAR Sentinel 1 data in the period 2015 - 2023 to analyze subsidence, the results showed that subsidence hot spots were concentrated in District 7, Binh Thanh District and part of Go Vap District at high speeds from 2 - 3 cm/year. Over time, the phenomenon of subsidence with a value of > 2cm/year was distributed in Binh Tan and Tan Phu districts following the trend of new urban expansion to the West of HCM city. Additionally, Sentinel 2 imaging data was also used in this study to demonstrate that areas with high construction density have high subsidence rates. From there, it can be seen that the urbanization process is one of the causes of subsidence in HCM city.

Analisis Bencana Longsor akibat Gempa bumi Cianjur 2022 dengan DInSAR

Indonesia is a country with a high potential for disasters such as earthquakes, which usually cause changes in the shape/position of the earth's surface (deformation). The Cianjur area has a seismic vulnerability level value based on maximum ground acceleration, maximum intensity and earthquake return period. On Monday, November 21, 2022 at 13.21 WIB there was an earthquake with a magnitude of 5.6 M in the Cianjur area of West Java based on BMKG data, until November 22, 2022 there were 140 aftershocks with magnitudes of 1.2-4.2 and an average depth of approximately 10 km. As a result, causing subsidence, the purpose of this study is to determine the magnitude of subsidence in landslides due to the 2022 Cianjur earthquake using the DInSAR method. Vertical land subsidence (displacement data) due to the earthquake from DInSAR observations on displacement data, which ranged up to -101mm vertically with two soil types andosol and cambisol Overlay analysis of soil type and displacement data showed the highest area of displacement, found a match based on information circulating that Cugenang Sub-district is the most severely affected area (the existence of a new fault "Cugenang").

Surface deformation analysis due to the Poso earthquake on May 29, 2017 using the DInSAR method

Abstract Deformation can be a significant parameter in determining the presence and impact of an earthquake. The amount of deformation can be obtained from SAR image data using the InSAR and DinSAR methods. The DinSAR (Differential Interferometric Synthetic Aperture Radar) method is a well-developed method for observing subsidence and uplift with high accuracy in centimeters (cm). In this study, SAR imagery is used to detect surface deformation caused by the earthquake was happened on May 29, 2017, at 21:35:23 WIB in the Poso Regency, Central Sulawesi. The data used is Sentinel-1 satellite imagery data in single-look complex (SLC) format consisting of Master image recorded on May 19, 2017 (10 days before the main earthquake occurred) and Slave image recorded on May 31, 2017 (2 days after the main earthquake occurred). The interferogram formed during the Poso earthquake is around the main earthquake directions from the Southwest, South, to the Southeast. The amount of deformation generated in the deformation phase (wrapped phase) is in the form of negative and positive phase values. Negative phase values indicate areas experiencing deformation in the form of subsidence. The positive phase values indicate areas experiencing uplift. The results of unwrapping the SAR imagery obtained a maximum uplift deformation value of 0.0663 meters, spread over the areas of North Pesisir Poso District, Lore Peore District, Central Lore District, South Coastal Poso District, and East Lore District. The maximum subsidence deformation values (0.076 meters) that are quite large are spread in the North Coastal Poso District, Poso Coastal District, Lage District, and Lore Tengah District.

Uncovering a Seismogenic Fault in Southern Iran through Co-Seismic Deformation of the Mw 6.1 Doublet Earthquake of 14 November 2021

On 14 November 2021, a doublet earthquake, each event of which had an Mw of 6.1, struck near Fin in the Simply Folded Belt (SFB) in southern Iran. The first quake occurred at 12:07:04 UTC, followed by a second one just a minute and a half later. The SFB is known for its blind thrust faults, typically not associated with surface ruptures. These earthquakes are usually linked to the middle and lower layers of the sedimentary cover. Identifying the faults that trigger earthquakes in the region remains a significant challenge and is subject to high uncertainty. This study aims to identify and determine the fault(s) that may have caused the doublet earthquake. To achieve this goal, we utilized the DInSAR method using Sentinel-1 to detect deformation, followed by finite-fault inversion and magnetic interpretation to determine the location, geometry, and slip distribution of the fault(s). Bayesian probabilistic joint inversion was used to model the earthquake sources and derive the geometric parameters of potential fault planes. The study presents two potential fault solutions—one dipping to the north and the other to the south. Both solutions showed no significant difference in strike and fault location, suggesting a single fault. Based on the results of the seismic inversion, it appears that a north-dipping fault with a strike, dip, and rake of 257°, 74°, and 77°, respectively, is more consistent with the geological setting of the area. The fault plane has a width of roughly 3.6 km, a length of 13.4 km, and a depth of 5.6 km. Our results revealed maximum displacements along the radar line of sight reaching values of up to −360 mm in the ascending orbit, indicating an unknown fault with horizontal displacements at the surface ranging from −144 to 170 mm and maximum vertical displacements between −204 and 415 mm. Aeromagnetic data for Iran were utilized with an average flight-line spacing of 7.5 km. The middle of the data observation period was considered to apply the RTP filter, and the DRTP method was used. We calculated the gradient of the residual anomaly in the N-S direction due to the direction of the existing faults and folds. The gradient map identified the fault and potential extension of the observed anomalies related to a fault with an ENE-WSW strike, which could extend to the ~ E-W. We suggest that earthquakes occur in the sedimentary cover of the SFB where subsurface faulting is involved, with Hormuz salt acting as an important barrier to rupture. The multidisciplinary approach used in this study, including InSAR and magnetic data, underscores the importance of accurate fault characterization. These findings provide valuable insights into the seismic hazard of the area.

Pemetaan Perubahan Permukaan Tanah di Kawasan Pulau Nias dengan Menggunakan Data Sentinel - 1A IW

The determination of changes in the land surface is an event caused by changes in the volume of the rock layer below. and geological processes such as tectonic and volcanic activity, removal of material from the subsurface such as mining and natural causes such as the occurrence of holes in limestone. The purpose of this study is to determine the magnitude of land surface changes that occur in the Nias Island area caused by earthquakes. The data used in the processing stage with the DinSAR method in 2022 recording, with specifications of dual polarization VV + VH, beam mode IW (interferometric wide) and flight direction ascending. Sentinel 1 data used in this study are 4 pairs of scans, where each pair of scans consists of one scans being the master and another scans being the slave. The master image is the SAR image before the earthquake, while the slave image is after the earthquake. The magnitude of land surface changes that occurred on Nias Island, based on the 2022 earthquake, the largest uplift was the earthquake on December 30, 2022, with a range of values (1.012042) mm with an area of 72,641,981 Hectares. The largest subsidence occurred in the earthquake on December 30, 2022, with a range of values ranging from (-1.373125) mm to (-1.235427) mm with an area of 61347,891 Hectares.

Preliminary Derived DInSAR Coseismic Displacements of the 2022 Mw 5.7 Stolac Earthquake

On 22 April 2022, a Mw 5.7 earthquake was generated near Stolac (Bosnia and Herzegovina). The mainshock was succeeded by several aftershocks, three of which were significant. Two Mb 4.3 earthquakes occurred on 23 April 2022, and a Mw 4.8 earthquake was generated on 24 April 2022. Available data from fault mechanism solutions revealed that the mainshock activated a reverse fault, while the aftershock generated a normal fault with a right-lateral component. The Balkan Peninsula stands as one of the most active geodynamic areas in Central and Eastern Europe due to its location within the collision zone between Eurasian and African tectonic plates and the Anatolian microplate. Recorded earthquakes in Bosnia and Herzegovina are related to the energy generated by the subduction of the African tectonic plate under Eurasia. Furthermore, the seismicity of Bosnia and Herzegovina, particularly its southern part, is profoundly influenced by the subduction of the Adriatic microplate under the Dinarides. The Dinarides are a mainly fold and thrust belt that extends from the Southern Alps in the northwest to the Hellenides in the southeast and make dominant the tectonic system of Bosnia and Herzegovina. In this study, two pairs of SAR images obtained from the Sentinel-1 satellite mission were utilized to generate satellite LOS surface displacements using the DInSAR method. Moreover, LOS displacements were decomposed into vertical and east–west horizontal components by combining ascending and descending satellite orbits. Ultimately, the InSAR results were analyzed and compared with the data obtained from the CROPOS CORS GNSS station in Metković (MET3).

LAND SUBSIDENCE DYNAMICS IN MALAYSIA BASED ON TIME-SERIES VERTICAL DEFORMATION USING MODIFIED D-INSAR SENTINEL-1

Land subsidence in urban areas is geohazard that can be caused by tectonic movements, changes in aquifer networks, or anthropogenic activities such as excessive groundwater extraction, mining, tunnelling, and plantations. The degree of land subsidence can be monitored using time-series vertical deformation data extracted from Sentinel-1 satellite imagery using the modified D-InSAR method. This study aims to determine the land subsidence dynamics of 16 cities in Malaysia based on time-series vertical deformation data, including Kota Bahru, Kuala Terengganu, George Town and Butterworth, Alor Setar, Kangar, Ipoh, Seremban, Malacca, Kuala Lumpur, Putra Jaya, Shah Alam, Kuantan, Johor Bahru, Kinabalu, Bandar Labuan (Victoria), and Kuching. The time-series vertical deformation data used in this study were extracted between 2014-2022. Negative values of vertical deformation indicate that land subsidence is occurring, while positive values of vertical deformation are indicative of regional uplift. The overall rate of land subsidence in Malaysia is between -0.5 cm to -6.0 cm, while the average uplift rate is between +0.5 cm to +4.5 cm. An analysis of the data extracted reveals that the city that is most vulnerable to land subsidence is Johor Bahru, followed by Kuala Terengganu, Seremban, Kuala Lumpur, Shah Alam, Malacca, and Kuantan, while the city that has the lowest risk of land subsidence is Kangar. In contrast, cities that are vulnerable to regional uplift are Kinabalu and Bandar Labuan (Victoria). The results of this study can be used to guide urban planning initiatives, allowing them to consider any threats that might be posed by land subsidence.

Identification of Sea Level Rise and Land Subsidence Based on Sentinel 1 Data in the Coastal City of Pekalongan, Central Java, Indonesia

Sea level rise is a pure impact of climate change. However, the process of studying sea level rise must include local factors that influence such as land subsidence. This study focuses on sea level rise using the CEEMDAN method and land subsidence using the DInSAR method. The location of this research is Pekalongan, Central Java, Indonesia. Tidal data used in this study was for five years, from 2016 to 2020, obtained from the Geospatial Information Agency (BIG). Then the data used to study land subsidence in this study uses Sentinel-1 Synthetic Aperture Radar (SAR) data in 2015, 2016, 2017, and 2020. Pekalongan is an area with mixed diurnal tidal types with Formzahl number 1.7. The sea level rise in Pekalongan is relatively high, at 10.6 mm/year. Then the land subsidence that occurred in Pekalongan is the phenomenon that has the most influence on the occurrence of coastal flooding in the region. The average land subsidence on the coast of Pekalongan is 5.37 cm/year. In addition, the sampling results in 6 areas showed that the most significant decrease was in Area 2, with a decrease of -7.91 cm/year. Based on this research, land subsidence is the most considerable influence on flooding in Pekalongan compared to sea level rise.

МОНІТОРИНГ ВЕРТИКАЛЬНИХ ЗМІЩЕНЬ ЗЕМНОЇ ПОВЕРХНІ ПРАВОБЕРЕЖЖЯ КАНІВСЬКОГО ВОДОСХОВИЩА

Monitoring of vertical displacements of the earth's surface on the right bank of the Kaniv Reservoir in the Vytatchiv-Stajky region was carried out using the differential radar interferometry (DinSAR) technique. According to the results of observations during the spring period from 2015 to 2023, active landslide areas are displayed. The DinSAR method is briefly described, emphasising data filtering steps for landslide activation mapping. A high data correlation was recorded, and the presence of zones of active shifts on the shore of the reservoir was confirmed. The spread and intensity of landslide manifestations are determined by the peculiarities of the geological and geomorphological structure of the territory, its tectonic, neotectonic and seismic regimes, and hydrological and climatic conditions. Limitations of the method arising from the temporal decorrelation of the radar signal in regions with a large amount of vegetation are determined. Due to the significant decorrelation between the obtained results of forested and watered areas, the DinSAR technique, a digital elevation model (DEM), analysis of base surface maps and the results of spectral index calculations were combined to identify regions of active landslides caused by waterlogging of the Dnieper slopes. The study demonstrates the feasibility of using DinSAR to detect and monitor surface deformation.

Glacier elevation change during two periods in the Lenglongling mountains derived from bistatic SAR interferometry

Bistatic SAR interferometry is a feasible technique of deriving glacier height changes. Early studies on glacier change in the Qilian Mountains showed that the glacier area declined, terminus retreated, and flow velocity slowed down. In this study, five pairs of X-band bistatic TerraSAR-X/TamDEM-X images from 2014 to 2019 and an iterative D-InSAR method respect to SRTM DEM of 2000 were employed, which improved the reliability and accuracy of glacier height changing observations. From 2000 to 2014, the height of glaciers in the Lenglonglin Mountains decreased by (–0.64 ± 0.06) m year−1. Glaciers in the Gangshika peak and its surrounding region thinned at the rate of (–0.68 ± 0.09) m year−1 from 2014 to 2019. The values observed using remote sensing was in accordance with RTK–GPS measured values. Stable precipitation and increasing temperature since 1990 could be responsible for the quick glacier mass loss.

Monitoring of Land Surface Change in Padang City Using Dinsar Sentinel-1a Method

Padang City is the capital city of West Sumatra Province which is located on the west coast of the island of Sumatra which is generally associated with tectonic earthquakes. This condition causes the city of Padang to become a disaster-prone area, one of which is land surface changes. The earthquake that occurred caused shocks to the rock and soil layers, causing water below the earth's surface to come out and resulting in changes to the soil surface. Besides, changes in soil surface are also caused by several things, including excessive groundwater extraction and soil type factors. To reduce the bad impacts, it is necessary to monitor the ground surface and to reduce the risk of a disaster. In a broad scope, the use of SAR imagery using the DinSAR method can monitor changes in the land surface in the city of Padang. The data used were Sentinel -1A imagery based on 3 earthquakes with a strength of more than 5 magnitudes centered on the Mentawai Islands, on September 8, 19, and 21 October 2020. From this research, the results obtained from the earthquake 8 September 2020 with satellite recording data 28 August (slave) and September 9, 2020 (master), there was land subsidence with a range of 0 - 25 mm along the coast of Padang City. The 19 and 21 October 2020 earthquakes with satellite recording data of 27 October 2020 (slave) and 15 October 2020 (master) obtained almost even surface subsidence with a range of 0 - 40 mm throughout the residential area of ​​Padang City.

Land Subsidence Assessment for Wind Turbine Location in the South-Western Part of Madagascar

Finding a suitable location is a key factor for long-term investment in wind turbine energy. It includes understanding the area of interest, such as the subsidence of the land. Land subsidence is a gradual decrease in the surface of the Earth due to natural and/or induced causes. It can cause damage, such as settlement problems in the ground near infrastructure including buildings and wind turbines, thus not being a suitable place for long-term investment. Here, we show a case study of land subsidence prediction and assessment of the Atsimo Andrefana region, the great south-western part of Madagascar, using theoretical simulation and satellite images from the Sentinel-1 mission using D-InSAR method. The predicted land subsidence related to the depletion of groundwater reservoirs in the Atsimo Andrefana region is around 12 mm. We found ~5 mm of subsidence related to the growing city of Toliary and with an average subsidence of 124 mm and the highest record of 167 mm in the most southern part of the region for a period of 6 months. The spatial distribution of land subsidence allows us to choose the ideal location for wind turbine settlement, where land subsidence is not that severe, i.e., the areas with subsidence relatively low of equal or less than 10 mm within 6 months of observation, based on the processed data. Such results are essential for future environmentally friendly investments in the affected region, as the demand for green energy will always grow.

Monitoring of Maskun landslide and determining its quantitative relationship to different climatic conditions using D-InSAR and PSI techniques

Climate change has resulted in severe landslides in Maskun, Iran. This study evaluates and monitors the displacement caused by the landslide mass in Bam using Interferometry Synthetic Aperture Radar (DInSAR) and Persistent Scatterer Interferometry (PSI) techniques, as well as identifies relationships between climatic conditions and mass displacement. Temperature and precipitation data from 2007 to 2019 were combined with satellite images and the DInSAR method was used to determine the mass displacement differences after selecting eighteen radar images from the ASAR sensor of the ENVISAT satellite. Additionally, Sentinel 1 satellite images were acquired and analyzed using the PSI method from November 5, 2014, to June 24, 2019. The highest displacement level at the surface of the Maskun landslide mass was then extracted. The ASAR images show a monthly displacement rate of 7.3 mm. The smallest displacement, on the other hand, occurred between May and September 2009, at a rate of 3.1 mm/month. PSI results also revealed that the maximum Line Of Sight (LOS) velocities detected by PSI are −64.5 mm/yr (away from the satellite) and 32.45 mm/yr (toward the satellite). Rainfall is one of the main triggers for increasing the deformation of the Maskun landslide according to the time-series analysis.

Mud volcano as a feature of emergence in Caspian Sea

An eruption occurred on Dashli Island, 75 km from Baku, on 4th of July 2021, at 21:51 local time. The island is known as the mud volcano and has a history of eruption. We suspected that mud volcano eruption causes emergence on this island. Thus, the effect of this 2021 eruption is investigated using a remote sensing technique. Processed Sentinel-1 and 2 images are employed for this aim. We considered pre- and post-eruption scenarios to evaluate the effect of this eruption on the island. Satellite image classification is used to calculate shoreline changes. Results show that Dashli Island with an area of about 8.55 ha before eruption is now expanded to about 21.8 ha (about 155% increase). The DInSAR method is used to estimate the ground displacement of the island. According to the results, a two-year-displacement before the eruption was between 0.18 and 0.2 m, while a five-month-displacement after the eruption is estimated to be between 0.32 and 0.4 m. Considering ground displacement pre- and post-eruption we estimated 62000 m3 land gaining, due to emergence. We concluded that mud volcano can be counted as a feature of emergence in Dashli Island.

Land subsidence detection in Jakarta Province using Sentinel-1A Satellite Imagery

The land surface in Jakarta Province is thought to have experienced relatively continuous subsidence because of natural processes and artificial activities. This research was carried out to evaluate the rate of land subsidence in Jakarta Province. Based on this research, it can be shown from the Sentinel-1A satellite images that there has been landed subsidence. The data used are two pairs of Sentinel-1A Single Looking Complex (SLC) images acquired in 2019 and 2020. The data was processed using the DInSAR method to examine the rate of land subsidence. The results show that the land subsidence rate in Jakarta Province during the 2019-2020 period varies from 1.8 cm to -10.7 cm/year. The literature data results in 2016 experienced a decrease in land subsidence with a significant value of -12.6 cm/year. Land subsidence in 2017 averaged -1.8 cm/year. The land subsidence results from 2019 to 2020 have a value that tends to be lower than in 2016 of - 3.62 cm/year. Land subsidence occurs mostly in coastal areas and near estuaries caused by the nature of alluvial deposition materials. It has caused damages to road infrastructure in several regions of Jakarta Province, such as Mutiara Beach, West Cengkareng, and Pademangan.

Investigation of Fahlian aquifer subsidence and its effect on groundwater loss

Land subsidence is one of the natural and geological hazards that can occur naturally or as a result of human activities such as long-term groundwater abstraction and traditional agriculture. In the last two decades, following climate change and successive droughts, as well as improper management of water resources, the uncontrolled abstraction of groundwater and the increase in population growth have caused land subsidence in Fars province, especially the Fahlian Basin in the northwest of the province. In general, the present study aimed to monitor and measure land subsidence using radar interferometry and also to analyze the relationship between groundwater level changes and land subsidence in the Fahlian Basin. DINSAR method was used to estimate the displacement of the ground surface and produce a map of the average displacement speed. The results of interferometric data show the continuous occurrence of subsidence in the agricultural lands of the region. The average rate of this deformation is about 4 cm per year, and in most parts, the amount of subsidence during the three consecutive years 2016, 2017, and 2018 is equal to 0.09, 0.11, and 0.12 cm, respectively. Also, the results of the study of groundwater level drop changes in 12 piezometric wells for the period 2009–2017 are −0.36 to −10. The overall correlation between groundwater level changes and subsidence levels was estimated at 75%, indicating the dependence of subsidence and groundwater decline in the region.

Deformation analysis of 2020 mw 5.7 Karlıova, Turkey, earthquake using DInSAR method with different incidence angle SAR data

Earthquakes, one of the biggest natural disasters, affect the regions to which it occurs to a high degree. Determining the mechanisms of the earthquake that occurred in the light of this information is very important for both the region and the subsequent earthquakes. Interferometric Synthetic Aperture Radar (InSAR) is a commonly used method for determining co-seismic surface deformations. Especially in areas where there is no Global Navigation Satellite System (GNSS) receiver and teleseismic data source, results can be obtained quickly and effectively with InSAR. In this study, the co-seismic surface deformation caused by the Mw 5.7 earthquake in Karliova (Bingol), Turkey on June 14, 2020, was determined with Sentinel-1 SLC images with different incidence angles. Since Karliova is located in the region where North Anatolian Fault (NAF) and East Anatolian Fault (EAF) lines intersect, the information given by the earthquakes in this region is very important and carefully monitored. As the InSAR technique has not been applied to earthquakes that have Mw <6 in this region, two ascending and two descending orbits were used in the study to ensure results. In the study, the amount of displacement in the line of sight (LOS) direction was determined approximately 25–30 cm. In addition, 4 different horizontal and vertical results were obtained with the combination of ascending and descending orbits. Maximum horizontal displacement created by the earthquake was obtained as 13 cm to the East, and 15 cm to the West. Moreover, in the vertical direction, uplift up to 10 cm in the northern part of the fault and subsidence up to 10 cm in the southern part of the fault were determined. According to these results, the earthquake was determined as right strike slip fault mechanism compatible with NAF tectonic structure.

Research on InSAR Monitoring Precision Analysis of Coal Mining Influence Based on Long Time Sequence

In this paper, in view of the scope of coal mining subsidence, the magnitude of subsidence deformation and the impact on buildings (structures), InSAR technology is selected for monitoring, time series analysis method combined with D-InSAR method for processing, and Sentinel- 1 Satellite IW data and RADARSAT-2 satellite XF data have been monitored for four years in the mining-affected area and its surrounding areas. The results show that there are obvious subsidence ranges on the surface of the current mining area and the unstable settlement area. The Shen District has been in a stable state in recent years, and the time sequence analysis for more than 3 years has verified the high accuracy and reliability of the monitoring results. The analysis of the monitoring results shows that the InSAR technology can be used for mining subsidence monitoring, especially when determining the subsidence boundary and whether it is stable or not, it has its technical superiority.

An Improved Multi-Platform Stacked D-InSAR Method for Monitoring the Three-Dimensional Deformation of the Mining Area

The acquisition of information on fine surface three-dimensional deformation in a goaf is of great significance for the in-depth understanding of the law of mining subsidence and guiding the safe production and ecological restoration of the mining area. In this paper, three platform SAR satellite images are used for stacked D-InSAR processing to obtain the information on surface deformation in three line-of-sight directions. An improved three-dimensional decomposition model is proposed based on the difference between the COSMO-SkyMed and TerraSAR-X satellite heading angles, which are very small. The proposed method is verified by evaluating the three-dimensional deformation of the ground surface during the mining process at the 132610 working face in Fengfeng Mining District, Handan City, Hebei Province. The accuracy of the three-dimensionally decomposed vertical settlement results is verified with the leveling data of the same period. The accuracy of 0.82 cm is achieved, and the maximum subsidence is approximately 16 cm. Combining the high-precision terrain information obtained from the unmanned aerial vehicle photogrammetry data and the deformation law of inclined coal seam mining, the horizontal movement of the 132610 working face is analyzed to prove the feasibility of the proposed method.