The role of the en echelon Karakorum-Jiali fault zone (KJFZ) in accommodating eastward extrusion of the Tibetan Plateau remains a subject of ongoing debate. To clarify the present-day strain accumulation along its eastern section (encompassing the Gyaring Co, Beng Co, and Jiali faults), we integrated Sentinel-1 InSAR and GNSS velocities to derive a comprehensive three-dimensional crustal deformation field. Our analysis revealed distributed dextral shear across the Lhasa terrane east of the Yadong-Gulu rift, a sharp contrast to the concentrated shear west of this rift. Both the Beng Co fault and the Gyaring Co fault exhibit a dextral slip rate of similar to 3 mm/ yr and extend beyond their previously mapped traces. Quantifying the slip rate of the Jiali fault proved challenging due to the smooth deformation gradient across it; the shear strain is primarily concentrated to its south along the western segment (from Nagqu to Xiama), yet shifts to the north along the central segments (from Jiali to Yigong). This spatial variation suggests that the Bianba Lhorong fault to the north is likely the easternmost strand of the KJFZ. Furthermore, we identified focused uplift of 2-3 mm/yr along the central segments of the Jiali fault, potentially driven by reverse faulting and/or deglaciation unloading. Such a present-day strain partitioning pattern indicates that the Tibetan crust's eastward-increasing lateral extrusion is collectively accommodated by the approximately E-W trending dextral strike-slip active faults situated between the KJFZ and the Himalayan arc, implying lower slip rate than the previously proposed 10-20 mm/yr for the KJFZ.

The Jiali Fault, a major active tectonic structure within the Sichuan-Xizang and Yunnan-Xizang corridors, plays a critical role in assessing safety hazards for key engineering projects and mitigating the cascading effects of earthquakes and geological disasters. However, its activity, nature of motion, and slip rate remain debated. To better understand its present-day deformation, this work deployed a supplementary GNSS network in the west-central section of the fault zone starting in 2013, partially filling the station gap in the near-field. Integrating our data with the velocity fields from existing GNSS networks reveals clear segmentation in the Jiali Fault's present-day kinematic behavior. The western segment (Xiangmao Township to Xarma Township) is characterized by dominant horizontal motion, exhibiting a right-lateral strike-slip rate of 4.9 1.2 mm.a (for a locking depth of 28.5 +/- 16.7 km) and a horizontal shortening rate of 3.2 +/- 0.5 mm.a(1). The central segment (Jiali County to Yigong Township) shows reduced horizontal motion but significant uplift (4 similar to 6mm.a(1)) near the fault trace, suggesting a transfer of strike-slip shear strain to neighboring active faults and a transition towards predominantly vertical fault motion. The rapid uplift along the Jiali Fault is likely attributed to multiple mechanisms, including fault thrusting and surface mass loss (e.g., glacier melting and erosion). These findings contribute to a refined understanding of strain partitioning and earthquake potential along active faults within the Lhasa terrane.

The Kumamoto earthquake is analyzed, mainly on the basis of InSAR data combined with strong earthquake and GNSS data, using a variety of joint InSAR methods and multisource data solution methods and by comprehensively considering the normalization and weighting of multisource data. The three-dimensional (3D) deformation field is determined. The results show that the joint solution with multisource data can improve the accuracy of the 3D solution deformation results to a certain extent. According to the 3D solution results, the maximum east–west deformation caused by the 2016 Kumamoto earthquake was approximately 2 m; the manifestations in the north–south direction were mainly characterized by expansion and stretching; the northwestern side subsided vertically, with a maximum subsidence of 2 m; and the southeastern side was uplifted. The horizontal deformation characteristics reveal that the earthquake was dominated by right-lateral strike-slip; the strike was NE–SW oriented, and the Futagawa fault has several normal fault properties. By analyzing the co-seismic 3D deformation field, seismogenic faults can be better understood, which provides a foundation for studying seismic mechanisms.

On August 8, 2017, a 7.0-magnitude earthquake occurred in Jiuzhaigou County, Ngawa Prefecture, Sichuan Province, China. This earthquake followed the Wenchuan earthquake in 2008 and the Lushan earthquake in 2013, both of which were strong earthquakes with magnitudes of 7.0 or above in Sichuan Province. The epicenter of this earthquake was in Zhangzha Town, Jiuzhaigou County. It is very important to interpret the spatial distribution of landslides quickly after an earthquake for disaster emergency rescue. The distribution of geological disasters in an earthquake area is obtained based on the interpretation of high-resolution remote sensing images after an earthquake. The main geological disasters are small landslides and collapses. In terms of the results of the spatial distribution of disasters, we analyzed the spatial distribution law and control factors of coseismic disasters (elevation, slope angle, slope aspect, peak ground acceleration, and proximity to faults). The study shows that the geological hazards are relatively developed along the gully, with an obvious fault effect, and concentrated within 2 km of the seismogenic fault. Based on the above foundation, a particle swarm optimization (PSO)–BP neural network model for predicting landslide susceptibility was established by optimizing the initial weight and threshold of a BP neural network using the PSO algorithm. The landslide susceptibility assessment considers eight factors contributing to landslide occurrence, including elevation, slope angle, slope aspect, proximity to stream network, lithology, density of geological boundaries, proximity to faults, and proximity to the road network. The validity and accuracy of the model was tested by calculating the area under the receiver operating characteristic curve, which was 0.918. The experimental results showed that the PSO–BP neural network model exhibited satisfactory accuracy in predicting landslide susceptibility.

Nowadays, real-time monitoring of highway operation by unmanned aerial vehicle (UAV) technology is one of the research frontiers for urban remote sensing. In general, the existing stitching algorithms can meet the basic requirements in terms of accuracy, but their splicing speed cannot meet the real-time stitching requirements of UAV. The cause is that the time consumption sharply increases when stitching plenty of UAV images—this is the bottleneck problem. Herein, we proposed a novel splicing method based on the Superpoint network and a self-designed algorithm of matrix iteration. In this method, we take advantage of an advanced deep learning algorithm—Superpoint to efficiently extract image feature points for calculating the geometric transformation matrix, and make the Superpoint model more suitable for highway. More importantly, for the purpose of further improving the stitching speed and realizing real-time stitching for a large number of UAV images, we specially designed an algorithm of matrix iteration to accurately represent the image transformation relationships, i.e., a matrix is iterated through each adjacent transformation matrix relationship. It is the first time that an algorithm of transformation matrix iteration has been designed to address the bottleneck problem in stitching plenty of UAV images. As a result, the experiments indicate that the proposed method has remarkably enhanced the stitching speed and accuracy for plenty of UAV images. Notably, even in the condition of no air triangulation parameters, it can realize real-time stitching.

After an earthquake, efficiently and accurately acquiring information about damaged buildings can help reduce casualties. Earth observation data have been widely used to map affected areas after earthquakes. However, fine post-earthquake assessment results are needed to manage recovery and reconstruction and to estimate economic losses. In this paper, for quantification and precision purposes, a method of earthquake-induced building damage information extraction incorporating multi-source remote sensing data is proposed. The method consists of three steps： (1) Analysis of multisource features that describe texture, colour, and geometry,(2) rough set theory is carried out to further determine the feature parameters, (3) Logistic regression model(LRM) was built to describe the relationship between the occurrence and absence of destroyed buildings within an individual object. Old Beichuan County (centered at approximately 31.833︒N, 104.459° E), China, the area most devastated by the Wenchuan earthquake on May 12, 2008, is used to test the proposed hypothesis. Multi-source remote sensing imagery include optical data, synthetic aperture radar (SAR) data, and digital surface model (DSM) data generated by interpolating light detection and ranging (LiDAR) point cloud data. Through comparison with the ground survey, the experimental results show that the detection accuracy of the proposed method is 94.2%; the area under the receiver operating characteristic (ROC) curve is 0.827. The efficiency of the proposed method is demonstrated using 6 modes of data combination acquired from the same area in old Beichuan County. The approach is one of the first attempts to extract damaged buildings through the fusion of three types of data with different features. The approach addresses multivariate regression methodologies and compares the potential of features for application in the damage detection field.

Earthquake loss assessment is an important part of earthquake emergency preparedness,emergency response,and reconstruction.With the increased awareness of earthquake risk and the increasing demand for earthquake protection and disaster reduction,earthquake disaster loss assessment technology has undergone rapid development in recent years.Moreover,as remote sensing technology has entered the era of big data,remote sensing data are beginning to be widely used in earthquake loss assessment.This study reviews and summarizes the development of earthquake loss assessment and its use in remote sensing techniques.In particular,we initially reviewed the development of earthquake loss assessments and compared and analyzed the differences between loss calculation methods and the main functions of earthquake loss assessment software platforms at home and abroad.Second,we summarize the calculation methods for estimating casualties,injuries,and economic loss according to whether structural damage is considered.Third,we summarize the development of emergency earthquake loss assessment methods and earthquake loss prediction methods based on remote sensing.Finally,we analyzed the application prospects of NTL remote sensing data as a spatialization tool for population and GDP data for earthquake disaster loss.The following conclusions can be drawn.(1)In recent years,the calculation granularity of the domestic earthquake disaster loss estimation system has gradually improved.The applied structural damage estimation method has changed from the traditional empirical earthquake damage matrix to the fragile curve,and the system application scenario has developed from the post-earthquake period to full-time application.(2)A seismic loss assessment based on macro-data and historical earthquake cases is easy to calculate,but its reusability needs to be improved.Comparatively,various sophisticated methods for building loss information involve logical reasoning,but they are restricted by varying degrees of data completeness.(3)Post-earthquake loss assessment and earthquake damage prediction technologies based on remote sensing have gradually improved.The current development trends include methods for acquiring multisource remote sensing data and intelligent remote sensing data analysis.However,current earthquake loss assessment work is limited by incomplete data,which hinders the promotion of new methods,the lack of a unified national business platform,and the lack of uncertainty. The following suggestions are proposed:(1)further develop the role of remote sensing data in the entire process of earthquake disaster loss estimation;(2)build a professional,high-quality,and national unified earthquake disaster risk management platform;and(3)enrich and develop the reporting mechanism of earthquake disaster assessment results from the perspective of the identified audience.

In this paper, an automatic aftershock forecasting system for China is presented. Based on a parameter-free historical analogy method, this system can produce short-term aftershock forecast, including seismic sequence types and the magnitude of the largest aftershock, within a few minutes after a major earthquake and can further provide scientists and government agencies with a set of background information for consultation purposes. First, the system construction concept and operation framework are described, and an evaluation of the forecast performance of the system is then conducted considering earthquakes from 2019 to 2021 in mainland China. The results indicate that the sequence type classification precision reaches 83.5%, and the magnitude of more than 90% of the aftershocks is smaller than that of upper range forecast. This system is fast and easy to control, and all the reports and maps can be produced approximately 5 min after earthquake occurrence. Practical use verifies that the application of this system has greatly improved the efficiency of post-earthquake consultation in mainland China.

Abstract In nature, the vertical and horizontal deformation components happen simultaneously for most geohazards, which sometimes bring disasters to human beings. As an advanced radar interferometry technique, InSAR (Interferometric Synthetic Aperture Radar) can efficiently obtain ground deformation information at a global scale, but it can only obtain the deformation along radar LOS (line of sight) direction. To extract vertical and horizontal deformation components, the existing methods need at least three-track InSAR LOS measurements or azimuth measurements. However, it is generally unlikely to acquire a three-track SAR dataset covering the same region during the same time range. Herein, through mathematical deduction, we find out that both vertical and horizontal deformation components can be extracted just from two-track InSAR LOS measurements. and the analytical expressions are presented. Furthermore, the proposed method is validated by experiments. It is the first time that both vertical and horizontal deformation components have been extracted just from two-track InSAR LOS measurements without using any other measurements. Hence, it can greatly enhance the three-dimensional information acquisition ability of radar interferometry.

We present a method to quantitatively analyze the characteristics of clusters and extract cluster centers in aftershock clouds to study the corresponding structural information. Based on a cluster center approach, a 3D rupture surface is constructed based on the aftershocks of the Wenchuan earthquake. The geometric characteristics of the rupture surfaces show that the Longmenshan fault zone should be divided into seven segments from south to north, and for most of the rupture surfaces, there are two discontinuities at depths of 10 and 20 km. According to the cluster characteristic distance of each rupture branch, the number of aftershocks within the cluster distance is counted. The statistical results show that 22% of the aftershocks of the Wenchuan earthquake occurred on the rupture surface parallel to the main fault and that the rest occurred along other nonparallel rupture surfaces or were scattered. The complex branches of rupture surfaces and the existence of rupture surfaces penetrating the 10 km deep discontinuity layer are two common characteristics of the XI intensity area. The change in tendency of the fracture surface between depths of 10 and 20 km may restrain the continued northward extension of the XI intensity area.

研究表明地震会引起大气中甲烷气体异常,本研究选取川滇固定区域,以2021年9月四川泸县地震为例,基于美国对地观测卫星AQUA/EOS上搭载的高光谱传感器大气红外探测仪(AIRS)获取的甲烷气体产品,采用成熟的RST算法开展地震前后甲烷异常信息提取,并对2008年以来区域内6级以上地震开展甲烷异常指数时序分析.研究结果表明:甲烷异常与地震有一定对应关系,主要表现为甲烷打破区域历史时空特征分布规律,随孕震过程总体呈现出起始增强—异常加强—高峰—衰减—平静的变化特征.异常幅度与震级无明显的关系,但是异常持续时间可能与震级有关,即地震引起的甲烷异常并不是偶发的,具备一定异常持续时间.异常可能对应一定区域内的地震,后续需综合分析区域内构造地质情况、震级、不同研究区域半径,开展更深入的研究.川滇局部区域基于遥感手段开展甲烷气体地震异常监测具有一定的可行性,这与该区域本身富含大量烃类气体有关,地震的发生会促使地下海量烃类气体沿岩石裂隙、断裂带、不整合面等薄弱地带快速运移、扩散释放至大气中.本研究区域以外不具备油气藏条件、构造地质差异大等情况是否可开展甲烷地震监测,监测效能等尚需通过大量工作开展深入分析.

Interferometric synthetic aperture radar (InSAR) has been effectively used to monitor surface deformation in a mining area with millimeter-level accuracy. On March 27, 2022, a tailings dam failure occurred in Shanxi Province, China, causing significant damage to surrounding houses, woodland, and roads below the tailings pond. We obtained the surface deformation map of the tailings dam before the catastrophic failure using the InSAR time-series method with a full resolution of Sentinel-1 A. This paper employed a GPU-assisted InSAR processing method for 91 Sentinel-1 images in Interferometric Wide Swath (IW) mode acquired from January 8, 2019, to March 17, 2022. The InSAR results show that during the 25 months preceding the tailings dam failure, Dam-II experienced an average cumulative LOS deformation of nearly 80 mm, while Dam-I experienced a significant deformation of more than 140 mm in the LOS direction. The analysis combining the deformation and rainfall results shows that rainfall significantly affects tailings pond deformation. In general, the deformation evolution has a high correlation with the rainfall annually, but the maximum deformation rate occurs with a delay of about one month compared to the peak rainfall. InSAR technology can significantly improve the monitoring capability of tailings dam failure and other landslide disasters, but it is limited by the observation frequency of the satellite. Thus, improving the temporal resolution of SAR data may assist in predicting tailings dam failure times more accurately.

SAR tomography (TomoSAR) extends SAR interferometry (InSAR) to image a complex 3D scene with multiple scatterers within the same SAR cell. The phase calibration method and the super-resolution reconstruction method play a crucial role in 3D TomoSAR imaging from multi-baseline SAR stacks, and they both influence the accuracy of the 3D SAR tomographic imaging results. This paper presents a systematic processing method for 3D SAR tomography imaging. Moreover, with the newly released TanDEM-X 12 m DEM, this study proposes a new phase calibration method based on SAR InSAR and DEM error estimation with the super-resolution reconstruction compressive sensing (CS) method for 3D TomoSAR imaging using COSMO-SkyMed Spaceborne SAR data. The test, fieldwork, and results validation were executed at Zipingpu Dam, Dujiangyan, Sichuan, China. After processing, the 1 m resolution TomoSAR elevation extraction results were obtained. Against the terrestrial Lidar ‘truth’ data, the elevation results were shown to have an accuracy of 0.25 ± 1.04 m and a RMSE of 1.07 m in the dam area. The results and their subsequent validation demonstrate that the X band data using the CS method are not suitable for forest structure reconstruction, but are fit for purpose for the elevation extraction of manufactured facilities including buildings in the urban area.

The management of seismic risk is an important aspect of social development. However, urbanization has led to an increase in disaster-bearing bodies, making it more difficult to reduce seismic risk. To understand the changes in seismic risk associated with urbanization and then adjust the risk management strategy, remote-sensing technology is necessary. By identifying the types of earthquake-bearing bodies, it is possible to estimate the seismic risk and then determine the changes. For this purpose, this study proposes a set of algorithms that combine deep-learning models with object-oriented image classification and extract building information using multisource remote sensing data. Following this, the area of the building is estimated, the vulnerability is determined, and, lastly, the economic and social impacts of an earthquake are determined based on the corresponding ground motion level and fragility function. Our study contributes to the understanding of changes in seismic risk caused by urbanization processes and offers a practical reference for updating seismic risk management, as well as a methodological framework to evaluate the effectiveness of seismic policies. Experimental results indicate that the proposed model is capable of effectively capturing buildings’ information. Through verification, the overall accuracy of the classification of vulnerability types reaches 86.77%. Furthermore, this study calculates social and economic losses of the core area of Tianjin Baodi District in 2011, 2012, 2014, 2016, 2018, 2020, and 2021, obtaining changes in seismic risk in the study area. The result shows that for rare earthquakes at night, although the death rate decreased from 2.29% to 0.66%, the possible death toll seems unchanged, due to the increase in population.

沂沭断裂带为郯庐断裂带山东段,是郯庐断裂带中活动性最强的一条断裂.对活动断层进行精细解译具有重要意义.本文收集了沂沭断裂带东地堑的KH-4B卫星影像、历史航片数据、高分2号影像等,对沂沭断裂带东地堑的3条主干断裂进行了遥感解释和构造地貌学分析,获取了更精细的断层分布.结果表明,昌邑—大店断裂(F1),总体NE走向,线性特征突出,沿断层处多发育陡坎、跌水等,多见由断层活动形成的串珠状水塘;白芬子—浮来山断裂(F2)走向NNE,历史影像中色调异常明显,显示部分河流右旋位错;安丘—莒县断裂(F5)走向NNE,大体沿沭河发育,地表形成系列串珠状湖泊.跨3条主干断裂的冲沟均出现明显右旋位错,F5断裂最为明显.另外,沿断裂带测量了多个冲沟位错,包括水平位错和垂直位错,与野外调查相近.相关工作可以为下一步的钻探和物探提供参考.

近年来随着我国页岩气大规模开采,四川盆地南部活动构造相对稳定的地区出现了一系列微震和有感地震,甚至是破坏性地震.这些地震是否为工业开采所诱发,目前已有研究从时空相关性给出了一些统计推断,本文则从形变观测角度分析页岩气开采能否产生可以检测到的地面形变,以揭示形变信息与页岩气开采的关系,尝试为页岩气开采提供有效的监测手段.基于长波ALOS-2卫星雷达数据对长宁页岩气区块近两三年内的InSAR地表形变展开探测,检测页岩气大规模生产可能造成的地面形变及其基本特征,同时使用Sentinel-1卫星雷达数据分析页岩气开发活跃时段内的形变时间序列信息.结果显示:考虑到不同观测技术的误差水平和观测角度差异,两种卫星数据均反映了一致的地表形变分布,且形变场与页岩气开采井的空间分布有很好的对应关系;压裂注液过程会造成地表快速隆升,生产过程中随着流体扩散地表会出现沉降和水平运动,初步揭示出页岩气生产过程中地面形变的非稳态变形特征.这表明在四川盆地南部复杂的形变观测条件下,InSAR技术是页岩气开采有效的监测手段,能够弥补地震学观测的不足.

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In order to obtain differential interference processing results, the capabilities of X-UAVSAR are evaluated to optimize the system in subsequent flight tests. The plane positioning accuracy of the first flight test data is evaluated based on the R-D model with external DEM data, the flight baseline and coherence of the repeat-pass SAR images are calculated to evaluate the interferometry capability, and the SAR image is classified to evaluate the quantity of information and classification performance. The results show that: the accuracy of plane positioning, especially absolute positioning, is lower; the test data meets the basic interference processing requirements, but the actual processing is more difficult, and the SAR image information is rich, which can meet the requirements of rapid classification. For the subsequent flight, on the premise of meeting the weight requirements of the aircraft, the inertial navigation device with higher accuracy is selected as far as possible, and the flight should be carried out at different flight altitudes and with low vegetation coverage.

The middle segment of the Tan-Lu fault zone (MTLFZ) is a large-scale active fault zone in the eastern Chinese mainland, and the 1668 Tancheng M8.5 earthquake occurred in its eastern graben. In this study, wavelet-based multi-scale analysis, Moho inversion, and gravity profile modeling are utilized to invert the high-precision Bouguer gravity anomaly of the MTLFZ and adjacent areas, and the fine crustal structure and deformation features are analyzed to understand the deep seismogenic mechanism. The results indicate that the regional gravity field can be subdivided into five blocks. The MTLFZ, as the tectonic boundary, is a NNE-trending gentle gravity gradient zone or a high anomaly zone with the highest gradient value of 0.6 mGal/km. In plane, the sedimentary layer to the upper crust of the Tan-Lu fault zone (TLFZ) shows a gravity pattern of "two grabens and one horst" on the north of Suqian, and the middle-lower crust is characterized by a long and narrow intermittent low anomaly zone, while the uppermost mantle is displays an accumulation of high anomaly materials. In profile, the TLFZ cuts through the Moho interface to the upper mantle and serves as a channel for upwelling of high density materials into the lower crust from mantle, where density value of lower crust is nearly 3.0 g/cm3, which is significantly higher than both the sides. The regional Moho depth increases from 30.8 km in the east to 36.0 km in the west, and an abrupt change is observed along the TLFZ, where the Moho interface is severely uplifted in the Juxian-Tancheng and Suqian-Jiashan areas. The gravity results reveal several NW or NWW active faults on the west side of TLFZ that intersect with it, which decreases the stress of the western graben. In contrast, the eastern graben is relatively rigid due to the lack of intersecting active faults. Moreover, the deep fault of the TLFZ displays a similar declination as the shallow branch faults of the eastern graben with little distortion, so the stress acts more easily and the hot mantle materials upwell more efficiently to induce major earthquakes in the eastern graben. It is interpreted that the 1668 Tancheng earthquake occurred through this mechanism: the Moho interface is strongly uplifted in the Tancheng area where the mantle material upwelled into the crust along the TLFZ, and the strain continued to accumulate due to crustal structure features of the eastern graben.

Interferometric synthetic aperture radar (InSAR) can monitor large-scale small deformation. Because the Sentinel-1 satellite has a stable orbit control and the data coherence in Qinghai–Tibet Plateau is good, we utilize data from Sentinel-1 to analyze the slip deformation of the Gyaring Co fault (GCF) in the central Tibetan Plateau. Data are obtained from ascending and descending tracks covering the research area, and the deformation results are obtained by the stacking and analysis of time series. The results demonstrate that the GCF exhibit slow slip overall. An analysis of different sections indicates that the fault displays both right-lateral strike-slip and normal faulting behaviors, and the movement is particularly obvious in the middle section of the GCF. Furthermore, we investigate the contemporary slip rate of the GCF using GPS data and construct two velocity profiles perpendicular to the fault strike at the southeastern and northwestern ends of the fault. The southeastern profile shows ~ 4 mm/year of right-lateral strike-slip movement and a modest (< 1 mm/year) amount of crustal thickening across the fault, while the northwestern profile shows much slower (~ 1 mm/year) right-lateral strike-slip motion and 0.5 mm/year of crustal extension. The GPS results are consistent with the InSAR deformation map derived using Sentinel-1 A/B data from 2014 to 2017. Our results support the distributed crustal motion model in which most crustal deformation (shortening/extension/strike-slip) occurs on various active faults in the central Tibetan Plateau rather than being concentrated on several fast-moving fault zones, e.g., the GCF-BCF. Finally, we analyze the distribution of historical earthquakes and the gravity and aeromagnetic fields. We speculate that a fault may exist north of Gyaring Co Lake that may be an extension of the fault north of Mujiu Co Lake.