Small Baseline Subset Interferometric Synthetic Aperture Radar Research Articles

Preliminary Identification of Geological Hazards from Songpinggou to Feihong in Mao County along the Minjiang River Using SBAS-InSAR Technique Integrated Multiple Spatial Analysis Methods

Landslides and collapses are common geological hazards in mountainous areas, posing significant threats to the lives and property of residents. Therefore, early identification of disasters is of great significance for disaster prevention. In this study, we used Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology to process C-band Sentinel-1A images to monitor the surface deformation from Songpinggou to Feihong in Maoxian County, Sichuan Province. Visibility analysis was used to remove the influence of geometric distortion on the SAR images and retain deformation information in the visible area. Hot spot and kernel density analyses were performed on the deformation data, and 18 deformation clusters were obtained. Velocity and slope data were integrated, and 26 disaster areas were interpreted from the 18 deformation clusters, including 20 potential landslides and 6 potential collapses. A detailed field investigation indicated that potential landslides No. 6 and No. 8 had developed cracks and were severely damaged, with a high probability of occurrence. Potential collapse No. 22 had developed fissures, exposing a dangerous rock mass and posing significant threats to the lives and property of residents. This study shows that the proposed method that combines visibility analysis, InSAR deformation rates, and spatial analysis can quickly and accurately identify potential geological disasters and provide guidance for local disaster prevention and mitigation.

Accuracy verification and evaluation of small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) for monitoring mining subsidence

ABSTRACT This study investigated the role of the number of differentialinterferograms and coherent threshold values on the accuracy of SBAS InSAR (small baseline subset interferometric synthetic aperture radar) results for specific applications in Jiyang Coal. Fifty-eight imageswere utilized to form fourdifferential interferogram timeseries with different numbers of interferograms and coherence thresholds. The four SBAS InSAR-monitored results, mining information of 15 working faces, and levelling-monitored results of 260 levelling points werecompared.The greater number of differential interferograms and lower coherent threshold values could better reflect the spatial distribution and variation trend of mining subsidence and demonstrate the advantages of SBAS InSAR. However, an excessive number of differential interferograms and excessively low coherent threshold values would increase the data processingdifficulty and the differences between SBAS InSAR- and levelling-monitoredresults. Location, spatial distributionandscopeofSBAS InSAR-monitored mining subsidence were consistent with the mining progress of the working faces.The accuracy ofSBASInSAR-monitored subsidence values followed a certain spatio-temporal variation law. The variation trend of absolute differences between SBAS InSAR-and levelling-monitored subsidence values was similar to the shape of the levelling-monitoredsubsidence basin, which was helpful to study the correction method of SBAS InSAR-monitored results.

The Liu-Type Estimator Based on Parameter Optimization and its Application in SBAS Deformation Model Inversion

A situation in which an image is combined with multiple images to form interferometric pairs is often observed in small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) deformation inversion, and this situation leads to a near linear correlation between the column vectors of the model design matrix. The Liu-type estimator introduces the parameters <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> into the normal equation to reduce the condition number of the design matrix and to improve the fitting properties. As the parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> is mainly used to reduce ill-posed problems of the design matrix, the value of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> is not limited. However, the value of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> , as determined by existing methods, is usually too large or too small. Since the calculation of the mean square error involves true values, the parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> is often affected by errors in the estimation results, which leads to the decreased accuracy of Liu-type estimation results. To determine the optimal value of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> , an iterative Liu-type estimator is proposed to eliminate errors. Then, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> -curve optimization method and iterative Liu-type estimator are combined to achieve the optimal <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> . The reliability and accuracy of the methods are analyzed through SBAS-InSAR deformation experiments. The experimental results show that after using the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> -curve method and an iterative operation to optimize <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> , the accuracy of the Liu-type estimator based on parameter optimization is clearly improved compared with that of the ridge estimator and the Liu-type estimator.

Land Deformation Monitoring in Lanzhou City Based on SBAS-InSAR Technology

With the continuous advancement of urban construction, the original natural landscapes such as wetlands, vegetation, and soil are converted into artificial landscapes such as buildings and roads, resulting in a wide range of changes in urban surface. Monitoring urban surface changes is of great significance to the healthy development of cities and the prevention of geological disasters. The traditional land deformation monitoring technology has the disadvantages of small monitoring range, large workload and low efficiency. Interferometric Synthetic Aperture Radar technology can effectively solve the defects in the traditional deformation monitoring technology. This paper takes Lanzhou as the research area, selects the Sentinel-1A data of 25 scenes from 2014 to 2016, and uses the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) for land deformation monitoring. The sedimentation observation results obtained by the SBAS-InSAR technique was analyzed with the methods of statistical analysis and time series analysis. The results show that: (1) The overall urban area of Lanzhou City has been slightly sunk, and the funnel in the deformation area is mainly concentrated in the mountainous areas, new residential buildings and subway stations. (2) From the perspective of each region, Shajingyiin Anning District, near XuanshengRundi in Jiuzhou, near Xiaodaping Driving Test Center, and near Xuanmagou-Badaoping Village in Chengguan, near Donggang Cargo Center, near Fulongping, near Hendafeicuihuating in Qilihe District, near Lanzhou West Railway Station and other places all showed strong subsidence trends, and the area with the highest deformation rate is Xiaodaping, which maximum average annual deformation velocity can reach 30.8mm/a, and the cumulative deformation is as high as 65.9mm.(3) The land deformation of Lanzhou City shows a non-linear downward trend, and the deformation gradually spreads in the east-west direction. Eventually, deformation also occurred in some foothills in the north and south, and in some urban areas. (4) The main driving factors for settlement in the urban area of Lanzhou are loess soil, rail transportation and urbanization.

Predicting mining-induced dynamic deformations for drilling solution rock salt mine based on probability integral method and weibull temporal function

ABSTRACT Long-term dynamic monitoring and sustainable prediction of rock salt mines is extremely important in preventing potential geological damages. However, the future prediction of the mining-induced surface displacement after the underground mining extraction cannot be achieved with single Multi-Temporal Differential Interferometric Synthetic Aperture Radar (MT-InSAR) technique, which can only reveal the deformation history during the period of Synthetic Aperture Radar (SAR) acquisition dates. In this paper, a novel dynamic model, namely Dynamic Probability Integral Method (DPIM), based on the integration of Probability Integral Method (PIM) and Weibull temporal function, is proposed in order to predict the future dynamic subsidence for the period which can not covered by the SAR acquisitions. Firstly, the time series deformation over the test salt mine are generated by Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique with use of 43 Sentinel-1 images, and then the functional relationship between the derived deformation and DPIM is established; Subsequently, the unknown parameters, including the PIM parameters and the Weibull temporal parameters are estimated following the genetic algorithm; Finally, the dynamic surface deformation occurring during the entire period of the underground extraction of the test rock salt mine is predicted. Both simulation and real deformation data over Xinhua (a typical rock salt mine in Hunan province, China) have been investigated. The scenario using the simulated data shows that the overall root-mean-square error of DPIM-predicted subsidence is ±3 mm. The real data experimental results show that the maximum predicted vertical subsidence over the rock salt mine was up to 246 mm. The root-mean-square error with comparison to the levelling measurements is estimated as ±7 mm.

Spatial-Temporal Evolution of Land Subsidence and Rebound over Xi’an in Western China Revealed by SBAS-InSAR Analysis

Land subsidence is one of the major urban geological hazards, which seriously restricts the development of many cities in the world. As one of the major cities in China, Xi’an has also been experiencing a large area of land subsidence due to excessive exploitation of groundwater. Since the Heihe Water Transfer Project (HWTP) became fully operational in late 2003, the problem of subsidence has been restrained, but other issues, such as ground rebounds, have appeared, and the effect of the underground space utilization on land subsidence remains unsolved. The spatial-temporal pattern of land subsidence and rebound in Xi’an after HWTP and their possible cause have so far not been well understood. In this study, the evolutionary characteristics of land subsidence and rebound in Xi’an city from 2007–2019 was investigated using Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-SAR) technology to process the Advanced Land Observing Satellite (ALOS) and Sentinel-1A SAR datasets, and their cause and the correlation with groundwater level changes and the underground space utilization were discussed. We found that the land subsidence rate in the study area slowed from 2007–2019, and the subsidence area shrank and gradually developed into three relatively independent and isolated subsidence areas primarily. Significant local rebound deformation up to 22 mm/y commenced in the groundwater recharge region during 2015–2019. The magnitude of local rebound was dominated by the rise in groundwater level due to HWTP, whereas tectonic faults and ground fissures control the range of subsidence and the uplift area. The influence of building load on surface deformation became increasingly evident and primarily manifested by slowing the subsidence reduction trend. Additionally, land subsidence caused by the disturbances during the subway construction period was stronger than that in the operational stage. Future land subsidence in Xi’an is predicted to be alleviated overall, and the areas of rebound deformation will continue increasing for a limited time. However, uneven settlement range may extend to the Qujiang and Xixian New District due to the rapid urban construction. Our results could provide a scientific basis for land subsidence hazard mitigation, underground space planning, and groundwater management in Xi’an or similar regions where severe ground subsidence was induced by rapid urbanization.

On Time-Series InSAR by SA-SVR Algorithm: Prediction and Analysis of Mining Subsidence

Given the increasingly serious geological disasters caused by underground mining in the Hancheng mining area in China and the existing problems with mining subsidence prediction models, this article uses the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology to process 109 Sentinel-1A images of this mining area from December 2015 to February 2020. The results show that there are three subsidences: one in Donganshang, one in south of Zhuyuan village, and one in Shandizhaizi village. In the basin, the maximum annual average subsidence rate is 300 mm/a, and the maximum cumulative subsidence is 1000 mm. The SBAS-InSAR results are compared with Global Positioning System (GPS) observation results, and the correlation coefficient is 74%. Finally, a simulated annealing (SA) algorithm is used to estimate the optimal parameters of a support vector regression (SVR) prediction model, which is applied for mining subsidence prediction. The prediction results are compared with the results of SVR and the GM (1, 1). The minimum value of the coefficient of determination for prediction with SA-SVR model is 0.57, which is significantly better than that those of the other two prediction methods. The results indicate that the proposed prediction model offers high subsidence prediction accuracy and fully meets the requirements of engineering applications.

Post-seismic deformation mechanism of the July 2015\xa0MW 6.5 Pishan earthquake revealed by Sentinel-1A InSAR observation

On 3 July 2015, the Mw 6.5 Pishan earthquake occurred at the junction of the southwestern margin of the Tarim Basin and the northwestern margin of the Tibetan Plateau. To understand the seismogenic mechanism and the post-seismic deformation behavior, we investigated the characteristics of the post-seismic deformation fields in the seismic area, using 9 Sentinel-1A TOPS synthetic aperture radar (SAR) images acquired from 18 July 2015 to 22 September 2016 with the Small Baseline Subset Interferometric SAR (SBAS-InSAR) technique. Postseismic LOS deformation displayed logarithmic behavior, and the temporal evolution of the post-seismic deformation is consistent with the aftershock sequence. The main driving mechanism of near-field post-seismic displacement was most likely to be afterslip on the fault and the entire creep process consists of three creeping stages. Afterward, we used the steepest descent method to invert the afterslip evolution process and analyzed the relationship between post-seismic afterslip and co-seismic slip. The results witness that 447 days after the mainshock (22 September 2016), the afterslip was concentrated within one principal slip center. It was located 5–25 km along the fault strike, 0–10 km along with the fault dip, with a cumulative peak slip of 0.18 m. The 447 days afterslip seismic moment was approximately 2.65 × 1017 N m, accounting for approximately 4.1% of the co-seismic geodetic moment. The deep afterslip revealed that a creeping process from steady-state “secondary” creeping to accelerating “tertiary” creep in the deep of fault. The future seismic hazard deserves further attention and research.

Analysis of surface deformation and driving forces in Lanzhou

Abstract Surface deformation has become an important factor affecting urban development. Lanzhou is an important location in the Belt and Road Initiative, an international development policy implemented by the Chinese government. Because of rapid urbanization in Lanzhou, surface deformation occurs easily. However, the spatial-temporal characteristics of surface deformation and the interaction of driving forces behind surface deformation in Lanzhou are unclear. This paper uses small baseline subset InSAR (SBAS-InSAR) technology to obtain the spatial-temporal characteristics of surface deformation in Lanzhou based on 32 Sentinel-1A data from March 2015 to January 2017. We further employ a geographical detector (geo-detector) to analyze the driving forces (single-factor effects and multifactor interactions) of surface deformation. The results show that the central urban area of Lanzhou was stable, while there was surface deformation around Nanhuan road, Dongfanghong Square, Jiuzhou, Country Garden, Dachaiping, Yujiaping, Lanzhou North Freight Yard, and Liuquan Town. The maximum deformation rate was −26.50 mm year−1, and the maximum rate of increase was 9.80 mm year−1. The influence factors of surface deformation in Lanzhou was a complex superposition relationship among various influencing factors, not a result of the single factor. The interaction between the built-up area and land cover types was the most important factor behind surface deformation in Lanzhou. This paper provides the reference data and scientific foundation for disaster prevention in Lanzhou.

Analysis of the Contribution Rate of the Influencing Factors to Land Subsidence in the Eastern Beijing Plain, China Based on Extremely Randomized Trees (ERT) Method

As a common geological hazard, land subsidence is widely distributed in the Eastern Beijing Plain. The pattern of evolution of this geological phenomenon is controlled by many factors, including groundwater level change in different aquifers, compressible layers of different thicknesses, and static and dynamic loads. First, based on the small baseline subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique, we employed 47 ENVISAT ASAR images and 48 RADARSAT-2 images to acquire the ground deformation of the Beijing Plain from June 2003 to November 2015 and then validated the results using leveling benchmark monitoring. Second, we innovatively calculated additional stress to obtain static and dynamic load information. Finally, we evaluated the contribution rate of the influencing factors to land subsidence by using the Spearman’s rank correlation coefficient (SRCC) and extremely randomized trees (ERT) machine learning methods. The SBAS-InSAR outcomes revealed that the maximum deformation rate was 110.7 mm/year from 2003 to 2010 and 144.4 mm/year from 2010 to 2015. The SBAS-InSAR results agreed well with the leveling benchmark monitoring results; the correlation coefficients were 0.97 and 0.96 during the 2003–2010 and 2013–2015 periods, respectively. The contribution rate of the second confined aquifer to the cumulative land subsidence was 49.3% from 2003 to 2010, accounting for the largest proportion; however, its contribution rate decreased to 23.4% from 2010 to 2015. The contribution rate of the third confined aquifer to the cumulative land subsidence increased from 2003 to 2015. Although the contribution of additional stress engendered from static and dynamic loads to the cumulative land subsidence was slight, it had a significant effect on the uneven land subsidence, with a contribution rate of 33.8% from 2003 to 2010 and 23.1% from 2010 to 2015. These findings provide scientific support for mitigating hazards associated with land subsidence.

The performance of LS and SVD methods for SBAS InSAR deformation model solutions

ABSTRACT For the small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) technique, the construction and subsequent robust solution of a deformation model is a key factor in obtaining monitored surface deformation results with high precision and high reliability. Here, the performance of the least squares (LS) and singular value decomposition (SVD) methods for the robust solution of SBAS InSAR deformation models are compared via tests with simulation and real SAR data. The LS method is used to solve the SBAS InSAR deformation models of 62 and 48 multi-temporal differential interferogram series; the SVD method is used to solve the SBAS InSAR deformation models of 60, 41, 58 and 53 multi-temporal differential interferogram series; the solved deformation results of the six series by the LS and SVD methods are compared and verified with the simulated deformation values and global positioning system (GPS) measurements. The results indicate that there is a moderate ill-posed degree in solving the SBAS InSAR deformation model by the LS method. The LS method can correctly retrieve the deformation information without considering any errors; however, in the case of serious random error, the deformation information acquired through the LS method is different from that of the simulation and is affected by the error of the multi-temporal differential interferometric phase series. The LS-solved results of real SAR datasets of two series are consistent, but are not in good agreement with the results of five GPS measurements. When the number of subsets is two, all types of deformation information solved by the SVD method follow the same rules as the results solved by the LS method. However, when the number of subsets increases to three and four, the stability of the SVD method becomes very poor; the SVD method can then only correctly solve the distribution of deformation in the study area, and the other solved deformation information, such as deformation velocity, is no longer credible.

A New Weighting Method by Considering the Physical Characteristics of Atmospheric Turbulence and Decorrelation Noise in SBAS-InSAR

Time series of ground subsidence can not only be used to describe motion produced by various anthropocentric and natural process but also to better understand the processes and mechanisms of geohazards and to formulate effective protective measures. For high-accuracy measurement of small baseline subset interferometric synthetic aperture radar (SBAS-InSAR), atmospheric turbulence and decorrelation noise are regarded as random variables and cannot be accurately estimated by a deterministic model when large spatio-temporal variability presents itself. Various weighting methods have been proposed and improved continuously to reduce the effects of these two parts and provide uncertainty information of the estimated parameters, simultaneously. Network-based variance-covariance estimation (NVCE) and graph theory (GT) are the two main weighting methods which were developed on the basis of previous algorithms. However, the NVCE weighting method only focuses on the influence of atmospheric turbulence and neglects the decorrelation noise. The GT method weights each interferogram in a time series by using the Laplace transformation. Although simple to implement, it is not reasonable to have an equal weight for each pixel in the same interferogram. To avoid these limitations, this study presents a new weighting method by considering the physical characteristics of atmospheric turbulence and decorrelation noise in SBAS-InSAR images. The effectiveness of the proposed method was tested and validated by using a set of simulated experiments and a case study on a Hawaiian island. According to the GPS-derived displacements, the average RMSE of the results from the new weighting method was 1.66 cm, indicating about an 8% improvement compared with 1.79, 1.80 and 1.80 cm from the unweighted method, the NVCE method and the GT method, respectively.

Time-Series Analysis of Subsidence in Nanning, China, Based on Sentinel-1A Data by the SBAS InSAR Method

Recent research has demonstrated that the Sentinel-1 constellation can be used for continuous tracking of ground deformation phenomena. In this study, the spatial–temporal subsidence characteristics in Nanning were investigated with 18 Sentinel-1A TOPS synthetic aperture radar (SAR) images acquired from 25 June 2015 to 16 December 2016 based on the small baseline subset interferometric SAR (SBAS InSAR) technique. The results showed that the annual average surface deformation rates in Nanning ranged from − 48 mm/year to 20 mm/year, and the maximum deformation was detected in the Langdong area. The SBAS-derived results were validated by Nanning continuously operating reference station (CORS) and levelling measurement data. The correlation coefficient and root-mean-square error (RMSE) between SBAS-derived and levelling-derived mean deformation rates were 0.79 and 2 mm/year, respectively. The maximum discrepancy and the RMSE amounted to 7 mm/year and 4 mm/year comparing the SBAS time-series with the CORS-measured displacement. The verification using levelling and CORS implied high reliability and precision of surface subsidence derived by SBAS InSAR. Our analysis revealed that surface subsidence in Nanning was mainly caused by large-scale urban construction, which should be paid enough attention to avoid further aggravation. With the help of the meteorological data, we also found that the subsidence in Nanning was closely related to climatic anomalies in 2015. This research work will provide important theoretical and practical reference value for urban planning and construction in Nanning.

Non-differential water vapor estimation from SBAS-InSAR

Water vapor is the most variable constituent in the atmosphere and plays an important role in climate studies, mesoscale meteorology modeling and numerical weather forecasting. Being able to penetrate clouds, interferometric synthetic aperture radar (InSAR) shows great potential in atmospheric water vapor mapping. But InSAR can only measure differential water vapor between two acquisitions. In this paper, we formulate a general framework by constructing the Gauss-Markov model and developing the estimation method to retrieve the non-differential water vapor from Small BAseline Subset InSAR (SBAS-InSAR). To address the rank-deficiency in the Gauss-Markov model, we propose a new constraint, i.e., the temporal mean of water vapor being invariant. Simulated and real data experiments are conducted to validate the effectiveness of the framework and the advantages of the proposed constraint. The results show that the new constraint can offer an estimation more robust than the two traditional ones, i.e., the temporal mean of water vapor being zero and single or multiple epoch water vapor referencing. In addition, we found that there exists a constant bias, which equals to the temporal mean of water vapors, between the solutions under the new constraint and that under the constraint of the temporal mean of water vapor being zero. Finally, the possible methods to evaluate the temporal mean of water vapor are discussed.

MONITORING TIANJIN LAND SUBSIDENCE BY SBAS-INSAR BASED ON SENTINEL-1A SAR IMAGES

Abstract. In order to understand the spatial-temporal evolution of land subsidence in Tianjin, in this study, we applied the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to process 36 Sentinel-1A images acquired between 2015 and 2018 released by European Space Agency (ESA). The results show that during the study period, most of the regional land subsidence rate in study area ranged from −18 to 9 mm/a from 2015 to 2018, and the maximum subsidence rate exceeded 75 mm/a, the largest subsidence center is located in Wang qingtuo Town, Xiqing District, Tianjin. Furthermore, the SBAS-InSAR-derived result was verified by levelling data. The alignment was relatively high, and the maximum and minimum deviation were 6.4 mm and 3.3 mm, respectively, demonstrating that the SBAS-InSAR technique is feasible to monitor land subsidence in Tianjin area. The main influencing factors with respect to subsidence show different depending on different region. Additionally, the severe land subsidence in Tianjin is mainly caused by rapid urban development and urban surface load increase.

Land Subsidence Related to Coal Mining in China Revealed by L-band InSAR Analysis.

Geological disasters, including ground deformation, fractures and collapse, are serious problems in coal mining regions, which have threatened the sustainable development for local industry. The Ordos Basin is most known for its abundant coal resources. Over-mining the underground coal resources had induced land deformation. Detecting the evolution of the land deformation features and identifying the potential risk are important for decision-makers to prevent geological disasters. We analyzed land subsidence induced by coal mining in a 200 area in the Ordos Basin for the time period 2006–2015. ALOS-1 PALSAR images from December 2006 to January 2011 and ALOS-2 PALSAR-2 images from December 2014 to July 2015, optical remotely sensed images and coal mining information were collected. The small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) method and differential interferometric synthetic aperture radar (D-InSAR) method, GIS and statistical analysis were adopted. Results show that the maximum subsidence rate and cumulative subsidence along the line of sight (LOS) were −65 mm/year and −246 mm, respectively, from December 2006 to January 2011. The maximum cumulative subsidence was −226 mm from December 2014 to July 2015. The new boundary of the mining goafs from 2014 to 2015 and the most dangerous risk region were mapped. Moreover, the effect of large-scale mining coal, with the production volume exceeds 1.2 million tons per year, with the operation time more than 20 years on land subsidence was found greater than small and medium-scale coal mines and reached −59 mm/year. The recently established small-sized and medium-sized coal mines show high land subsidence. This study will contribute to better understand the land subsidence process in mining region and provide scientific support for government to prevent land subsidence.

Land Subsidence Response to Different Land Use Types and Water Resource Utilization in Beijing-Tianjin-Hebei, China

The long-term overexploitation of groundwater leads to serious land subsidence and threatens the safety of Beijing-Tianjin-Hebei (BTH). In this paper, an interferometric point target analysis (IPTA) with small baseline subset InSAR (SBAS-InSAR) technique was used to derive the land subsidence in a typical BTH area from 2012 to 2018 with 126 Radarsat-2 and 184 Sentinel-1 images. The analysis reveals that the average subsidence rate reached 118 mm/year from 2012 to 2018. Eleven subsidence features were identified: Shangzhuang, Beijing Airport, Jinzhan and Heizhuanghu in Beijing, Guangyang and Shengfang in Langfang, Wangqingtuo in Tianjin, Dongguang in Cangzhou, Jingxian and Zaoqiang in Hengshui and Julu in Xingtai. Comparing the different types of land use in subsidence feature areas, the results show that when the land-use type is relatively more complex and superimposed with residential, industrial and agricultural land, the land subsidence is relatively more significant. Moreover, the land subsidence development patterns are different in the BTH areas because of the different methods adopted for their water resource development and utilization, with an imbalance in their economic development levels. Finally, we found that the subsidence changes are consistent with groundwater level changes and there is a lag period between land subsidence and groundwater level changes of approximately two months in Beijing Airport, Jinzhan, Jingxian and Zaoqiang, of three months in Shangzhuang, Heizhuanghu, Guangyang, Wangqingtuo and Dongguang and of four months in Shengfang.

Adaptively Selecting Interferograms for SBAS-InSAR Based on Graph Theory and Turbulence Atmosphere

The spatial-temporal baseline threshold method is commonly used to select interferograms for the Small BAseline Subset interferometric synthetic aperture radar (SBAS-InSAR) technique. However, this selection strategy is rather empirical and prone to including highly contaminated interferograms or excluding those with high quality. To overcome these limitations, this study first derives the relationship between the measurement accuracy of unknown parameters and the number of selected interferograms with their corresponding qualities. Subsequently, an adaptive interferogram selection method is proposed on the basis of Graph Theory (GT) and the turbulence atmospheric effects of interferogram. This proposed method first identifies and deletes the SAR image that is severely polluted by atmospheric phase. Second, high-quality interferograms are selected for SBAS-InSAR based on their corresponding turbulence atmospheric variance. Compared with the traditional selection method, this approach can significantly reduce the effect of turbulence atmosphere on SBAS-InSAR. A set of simulated experiments and real Sentinel-1A data in Hawaii, United States, validate the good performance of the proposed method.

Surface Deformation Retrieving Over Soft Clay Based on an Improved Time Series InSAR Model: A Case Study of Dongting Lake Area, China

The infrastructures built on soft clay in the Dongting Lake area are more prone to settlement and instability due to its significant rheological properties. It is of great importance to conduct a long-term surface deformation monitoring over this area. The most commonly used Synthetic Aperture Radar Interferometry (InSAR) deformation models are based on combinations of one or several pure empirical mathematical functions without considering the physical and mechanical characteristics of the observed objects. In this work, we propose an improved deformation model based on the functional relationship between strain and time in the Maxwell rheological model. The rheological parameters of elastic modulus and viscosity are introduced into a traditional empirical seasonal model. The improved model is applied for the investigation of the spatial-temporal surface evolution over the Dongting Lake area with the Small Baseline Subset InSAR (SBAS-InSAR) technology and TerraSAR-X satellite imagery. With the proposed model, the rheological parameters and the time series deformation are estimated, with the maximum accumulated subsidence estimated as 38 mm. Through the analysis of the generated results, we find that the lower the viscosity and elastic modulus are, the higher the deformation is. Temporally, the overall deformation follows a generally subsiding trend with a seasonal recovery of 5 mm from October 2012 to November 2012 and 12 mm from January 2013 to February 2013. To compensate for the deficiency of the unavailability of external geodetic measurements over this area, three different accuracy indexes (residual phase, temporal coherence, and high-pass deformation) are utilized to evaluate the modeling accuracy. The results of the improved model are also compared to three traditional models (seasonal model, cubic polynomial model, and linear model). The comparison shows that the improved model is highly recommended in this area because of its better accuracy.

Locating and monitoring of landslides based on small baseline subset interferometric synthetic aperture radar

Due to the effects of rugged terrain and vegetation cover, improving the locating and monitoring accuracy of time series interferometric synthetic aperture radar (TS-InSAR) in detecting the development of landslides in mountainous and valley areas has become a problem that needs to be solved. Our study uses the ground local incident angle (GLIA) to locate noneffective monitoring areas that are affected by steep terrain as well as to improve the locating accuracy of TS-InSAR technology in the effective coverage area. At the same time, the improved small baseline subset InSAR (SBAS-InSAR) method is used to improve the density of interferometer targets as well as to solve the problem of insufficient permanent scatterers due to the effects of vegetation coverage. A geometric model of GLIA was established. Ascending and descending synthetic aperture radar (SAR) data from the Advanced Land Observation Satellite (ALOS) were used for calculating the value of GLIA. The relationships of the GLIA and the interference characteristics of InSAR data were analyzed, and the locations of noneffective areas were determined. Finally, 19 ascending pass SAR data scenes acquired by the ALOS-1 satellite were processed through using the improved SBAS-InSAR method, and the detailed time series moving displacement information from 2007 to 2011 was mapped in Wudongde hydropower reservoir. Furthermore, the potentially moving landslide areas and landslide hazard areas were located in the effective interference areas. The active Jinpingzi landslide was investigated in detail, and the single-point monitoring results of SBAS-InSAR were compared with the electronic total station (ETS) measurement results. The conclusion shows that the monitoring results of SBAS-InSAR were in agreement with the ground field survey and the single-point ETS monitoring, and the applicability of the model and algorithm proposed was proved. Our study provides a reference for the early identification and high-precision monitoring of landslides in mountainous and valley areas.