Fracture zones are geological formations resulting from the strong movement of the Earth’s crust, often manifesting as fragile and sensitive areas. These zones are closely linked to natural disasters such as earthquakes and landslides. Accurate extraction of fracture zones is crucial for quantitative studies of earthquake faults, providing a scientific basis for risk assessment and decision-making in earthquake prevention and mitigation. Thus, an in-depth study to determine their distribution patterns and surface geometry is essential for understanding earthquake dynamics and mechanisms.

This paper addresses the shortcomings of existing methods in extracting fracture zones from LiDAR point clouds, which often suffer from incomplete extraction, poor continuity, and high error rates. We propose a method based on a multi-scale neural network with RS-Conv to improve the automatic extraction of fault zones in complex terrain regions. Fracture zones exhibit complex morphologies and scale features; therefore, single-scale neighborhood point sets fail to reveal their intrinsic structural information fully. Our approach begins by constructing neighborhood point sets at different spatial scales to comprehensively examine geometric features at various levels within the point cloud. The RS-Conv operator effectively portrays the spatial relationship between the center point and neighboring points. We then build a multi-scale neural network model using the RS-Conv operator as the convolution module. This model captures the spatial relationships in the point cloud, efficiently extracting deep features at different scales. The extracted multi-scale features are concatenated to form a richer and more comprehensive feature representation, which is inputted into a fully connected layer to classify the centroid and solve the fracture zone extraction problem. We compared our method with the Tensor Decomposition and Deep Neural Networks(DNN)methods using the ISPRS point cloud dataset, the Sichuan-Yunnan point cloud dataset, and the Xianshuihe dataset. Results show that our method achieves the highest classification accuracy across all three datasets. Specifically, our method’s total classification error is only 0.3%, a reduction of 0.91% -2.79%compared to other methods. This significant error reduction demonstrates the accuracy, stability, and reliability of our proposed method in handling complex point cloud data. The main conclusions of this study are as follows:

(1)The construction of neighborhood point sets at different scales reveals that the combination of these scales significantly impacts the model’s classification performance. Selecting appropriate scale combinations is crucial for optimizing the model’s classification accuracy, facilitating better distinction between fracture zone points and non-fracture zone points.

(2)Compared to traditional and machine learning methods, the deep learning network model developed in this study shows significant advantages in extracting fracture zones from point clouds. The model can automatically learn deep features from point cloud data and process large-scale, high-dimensional point cloud datasets, thereby achieving more accurate fracture zone extraction in complex terrain conditions.

(3)Comparative experiments on different datasets further demonstrate the proposed method’s generalization ability. It is effective not only in extracting fracture zones under single terrain conditions but also in maintaining stable performance across multiple terrain conditions. This adaptability enhances the extraction of fracture zones in various terrain scenarios.

In conclusion, the method proposed in this paper offers a novel approach to fracture zone extraction. It achieves higher classification accuracy compared to existing traditional and machine learning methods, effectively addressing the challenge of fracture zone extraction in complex terrain areas.

MODIS land surface temperature(LST)products are of great value in the exchange of atmospheric matter and energy, climate change research, and detection of thermal anomalies as earthquake precursors. However, due to the influence of the cloud, there are a large number of missing values in the MODIS LST data products, limiting its wide application. Therefore, in this study we propose a method of surface temperature reconstruction based on mixed model: SCLSTM(SSA-CLSTM). Compared with traditional methods, this method does not need to establish a complex regression relationship model. In addition, since CNN can fully extract local features of one-dimensional time series data, and LSTM can fully learn long-term time series features of data, the combination of CNN and LSTM is capable of fully learning potential features of data.

Firstly in this study, the trend value of LST time series is extracted by SSA model to fill the missing pixel, and the initial reconstruction of LST is realized. Then, CLSTM(that is, 1DCNN, three-layer stacked LSTM)model is used to learn the local temporal characteristics and long-term dependence of the data, and the iterative prediction of the surface temperature of the missing pixel is realized to complete the fine reconstruction of the data. Based on the experimental results in Hotan region of Xinjiang and Wenchuan region of Sichuan, it can be proved that compared with the other two existing reconstruction methods based on mixed models, the reconstructed return data error is minimum, and the consistency with the original data is the highest. The RMSE of this method can be reduced to 0.712K, the minimum is 0.695K, and the correlation between the reconstructed return data and the original data can reach more than 0.95. In addition, the reliability of the method is further verified by the measured surface temperature data of the meteorological station. In summary, the proposed method provides a new technical means and ideas for deep learn-based reconstruction work, and also provides a solid data foundation for the research of surface processes and seismic thermal anomalies.

Using MODIS MYD11A2 remote sensing data and based on the proposed new method, the reconstruction experiments were carried out in Hotan region of Xinjiang Uygur Autonomous Region and Wenchuan region of Sichuan Province with the strategy of “remove-construction-contrast”, and the results were compared with other two mixed model methods. In addition, the reliability of the reconstruction accuracy of the proposed method is verified based on the 0cm measured surface temperature data of the weather station. The main conclusions are as follows:

(1)Through the reconstruction experiment of LST in Hotan, Xinjiang, it is concluded that compared with the existing two hybrid model reconstruction methods, the new method can better capture the time series features of LST data, so that the reconstructed image can not only better maintain the texture features of the original image, but also improve the accuracy of data reconstruction. The reconstruction error is the smallest among the three methods, RMSE can be reduced to 0.712K, and the correlation with the original data can reach more than 0.95 after reconstruction.

(2)In order to prove the regional applicability of the new method, a reconstruction experiment was carried out in Wenchuan region of Sichuan Province, and the missing values were reconstructed using the proposed method. Through this reconstruction experiment, we found that the reconstruction method in this paper can achieve better data reconstruction effect even in areas with more cloud and fog coverage, poor weather conditions, and complex land cover types, which proves the reliability and regional universality of the method in this paper.

(3)To further verify the reliability of the new method, the accuracy of the new method was evaluated by using the measured 0cm surface temperature data of 6 meteorological stations in Hotan region of Xinjiang. Based on the temporal variation characteristics of the MODIS return data from 2015 to 2019, the return values of 2020 are reconstructed, and the reconstructed results are compared with the measured data. By comparing the 0cm measured data of the meteorological station and the data before and after reconstruction, it can be concluded that the correlation and average deviation of the returned data and measured data after reconstruction based on SCLSTM method are closer to the correlation and average deviation of the original data and measured data. Therefore, the reconstructed data based on the new method can maintain a good consistency with the original data.

(4)By reconstructing the missing value regions of Hotan region of Xinjiang in 2008 and Wenchuan region of Sichuan in 2020, we found that the texture of the images after the supplementary value is fine and natural, without obvious boundary effect. Therefore, it can be proved that the method in this paper can realize the data reconstruction of a large area with missing values.

In summary, the method proposed in this paper provides a new idea and technique for MODIS surface temperature reconstruction work based on deep learning, and also provides a solid data foundation for the ground process research and seismic thermal anomaly information extraction based on MODIS LST.

Earthquake Early Warning(EEW)is the rapid acquisition of earthquake epicenter, magnitude, and occurrence time after a destructive earthquake has started to issue alerts to the public before the arrival of transverse waves and long-period surface waves. Magnitude estimation plays a significant role in EEW algorithm research, serving as a fundamental component for early warning, post-earthquake disaster assessment, and emergency response. Seismic monitoring methods primarily focus on technologies like High-rate Global Navigation Satellite System (HR-GNSS) and strong-motion instruments. HR-GNSS is capable of capturing high-precision ground deformation signals and offers the advantages of a non-saturation recording range, making it crucial for rapid estimation of earthquake magnitudes during major seismic events. However, due to the low GNSS sampling rate and high instrument noise, observational noise often overshadows the deformation signals obtained during low-magnitude earthquakes. Additionally, the sparse distribution of GNSS stations currently impacts the accuracy and timeliness of magnitude estimation. Strong-motion observation methods, characterized by high sampling rates, low noise, and dense station distribution, are widely applied in magnitude estimation. Prevalent methods for strong-motion magnitude estimation often rely on P-wave arrival time information for timely determination of magnitude, commonly used in earthquake early warning systems. Yet, these methods are susceptible to saturation effects, leading to underestimation of magnitudes for large earthquakes. Moment magnitude estimation methods are closely associated with rupture characteristics of the seismic source and hold clear physical significance. However, determining this magnitude necessitates knowledge of the rupture extent and slip distribution along the fault plane, which are challenging to precisely obtain at the moment of earthquake occurrence. Hence, such methods are generally employed for post-event magnitude calculations.

Addressing these challenges, this paper proposes a novel method for rapidly estimating earthquake magnitudes using Peak Ground Velocity(PGV)derived from strong motion. First, a comprehensive dataset of strong-motion acceleration records is compiled, covering nearly 20 years and including 5 596 records from 23 global seismic events with magnitudes ranging from 6.0 to 9.0. These records encompass epicentral distances from 1km to 1 000km, with source depths within 60km. A uniform processing approach is applied to standardize the records in terms of time domain orientation, measurement units(converted to cm/s²), and file formats. Data from each station is categorized into three directions: East-West(EW), North-South(NS), and Vertical(UD). Subsequently, the data is converted into the Seismic Analysis Code(SAC)file format, which is specialized for digital seismic waveform data exchange. Ensuring accurate PGV measurements from strong-motion data involves meticulous data preprocessing. This includes removing the mean acceleration from the first 5 seconds before the seismic event for simple bias correction, followed by baseline correction using a high-pass filter with a cutoff frequency of 0.02Hz. The preprocessed strong-motion acceleration records are then integrated to obtain velocity, enabling the measurement of PGV. A robust PGV-based magnitude estimation model, suitable for rapid earthquake magnitude estimation, is constructed using the least-squares regression method.

Furthermore, the constructed PGV-based magnitude estimation model undergoes comprehensive experimental analysis. Initially, the residuals between observed PGV values from 5596 strong-motion records and PGV values predicted by the regression model are computed to evaluate the precision of the constructed PGV-based magnitude estimation model. The model is validated using four earthquake events not included in its construction: the 2021 Damasi M_W6.3 earthquake, the 2012 Nicoya M_W7.6 earthquake, the 2008 Wenchuan M_W7.9 earthquake, and the 2014 Iquique M_W8.2 earthquake. This validation process assesses the reliability of the constructed magnitude estimation model. Finally, the paper conducts a study on rapid magnitude estimation to evaluate the timeliness and accuracy of the PGV-based magnitude estimation model within this context.

The experimental results indicate that the predicted values of strong-motion PGV are largely consistent with the observed values for 23 seismic events, with a root mean square error of residuals measuring 0.296. For the four seismic events that were not included in the modeling process, the estimated magnitudes based on strong-motion PGV correspond closely to the moment magnitudes reported by the United States Geological Survey(USGS). The absolute deviations for these events are 0.15, 0.14, 0.05, and 0.13 magnitude units, with an average absolute deviation of 0.12 magnitude units. In the investigation of rapid magnitude estimation, the following outcomes were observed: For the Damasi M_W6.3 earthquake, an initial magnitude of 5.03 was calculated at 13 seconds, approaching the theoretical magnitude at 63 seconds, and reaching a convergent magnitude of 6.09 at 76 seconds. Regarding the Nicoya M_W7.6 earthquake, a preliminary magnitude of 4.57 was computed within 6 seconds, approximating the theoretical magnitude at 30 seconds, and converging to 7.46 at 50 seconds. In the case of the Wenchuan M_W7.9 earthquake, a preliminary magnitude of 4.06 was determined within 19 seconds. At 50 seconds, the calculated magnitude approached the theoretical value, and it converged to 7.81 at 84 seconds. For the Iquique M_W8.2 earthquake, an initial magnitude of 6.45 was estimated within 2 seconds, nearing the theoretical magnitude at 55 seconds, and achieving a convergent magnitude of 8.04 at 70 seconds. The convergence time for rapid magnitude estimation for all four events was consistently under 90 seconds.

This experimental findings underscore the applicability of the constructed PGV-based magnitude estimation model for rapid earthquake magnitude estimation. The model's ability to counter saturation effects and prevent magnitude underestimation reinforces its robustness and offers substantial technical support for earthquake early warning systems and post-earthquake emergency response strategies.

As one of the most serious geological disasters, earthquake is of sudden and destructive characteristic. Therefore, it is of great significance to earthquake monitoring and early warning. The phenomenon of surface thermal infrared radiation enhancement is a common precursor of moderate and strong earthquakes and has been used as an important reference information for early warning and short term prediction. A variety of explanations have been given to understand internal mechanism of the above phenomenon, in which the stress-induced heating hypothesis is widely accepted and has been confirmed in the laboratory rock mechanical loading experiments, that is, under ideal conditions in the laboratory, the rock heats up when it is pressed and cools down when it is stretched. Under field conditions in practice, however, weak seismic precursors of thermal anomalies are often interfered by various environmental factors(solar radiation, atmospheric movement and human activities, etc.), and it has not been investigated whether the corresponding relationship between the above crustal compression-extension motions and thermal radiation anomalies can be observed under field conditions. The earth's gravity field, as one of the basic physical fields of the earth, contains the density distribution of crustal structure, which can be served to study the migration of the earth's material, the deformation of the crust and the change of the stress field. In this paper, we use GRACE gravity and MODIS thermal infrared remote sensing data to verify the stress-induced heat hypothesis in the field with Wenchuan earthquake as the time node. Firstly, the crustal mass density obtained by GRACE satellite was compared with thermal infrared radiation. Then, the gravity anomalies extraction method based on maximum shear strain and in-situ temperature method were used to obtain the gravity anomalies and thermal anomalies respectively. Furthermore, the correlation between the two anomalies before the earthquake was detected from the time scale and space scale respectively, and the consistency analysis between the above anomalies and the spatial distribution of the tectonic fault zone was carried out. For this purpose, two important indicators i.e., anomaly intensity and anomaly distribution, were established in time domain and space domain, respectively. The following conclusions could be drawn: 1)The stress-induced heating hypothesis can be verified by remote sensing in field conditions. The warming zone of the crust(positive thermal offset index)corresponds to the compression zone, and the cooling zone(negative thermal offset index)corresponds to the stretching zone. The consistency of positive and negative variation between the crustal mass density and thermal offset index is 88.9%, which provides field observation evidence for the stress-induced heating hypothesis. 2)The spatio-temporal variation of gravity anomalies and thermal anomalies before earthquake has strong correlation. In the time domain, there is a strong correlation between the gravity anomalies and the thermal anomalies, which shows that the intensity of the two anomalies suddenly increases synchronously and reaches the maximum simultaneously three months before the earthquake. In the spatial domain, gravity anomalies mostly occur at the junction of positive and negative values of thermal offset index, which indicates that the spatial distribution of gravity anomalies and thermal anomalies also has a certain correlation. In addition, the two anomalies appear to be distributed along the fault zone for many times, which shows that they are closely related to tectonic activities.

With the recent development of geodetic observation theory, the increasing satellite platforms and the progress of related technology, InSAR is emerging as a new data source and useful tool for remotely-based geodetic observations. More importantly, InSAR observations play an increasingly irreplaceable role in the field of coseismic deformation observations, earthquake emergency responses, earthquake hazard evaluation and seismogenic structure research. Particularly, InSAR is the most commonly used tool in coseismic deformation measurements on the Qinghai-Tibetan plateau or other global seismic zones, where GPS data are sparse or inaccessible in some cases. Specifically, InSAR measurements help us to respond in time after disastrous earthquakes and provide valuable information associated with how the surface of the crust deforms due to large earthquakes. In the area of scientific research, InSAR provides products of surface deformation observations and serves as model constraints kinematically or dynamically in identifying the buried faults, studying the characteristics of seismogenic faults, obtaining three-dimensional displacements, and investigating the relationship between earthquakes and tectonic structures. InSAR observations and its deformation products have the technical advantages of large spatial scale, high precision and in-time, compared to other geodetic measurements. Consequently, InSAR has the ability to provide scientific and technological support for earthquake emergency observations, and meeting the practical needs of earthquake disaster reduction on the Qinghai-Tibetan plateau.

In this review, we mostly limit our focus to the application of InSAR technology in earthquake cycle deformation monitoring in different structural settings on the Qinghai-Tibetan plateau. We also summarize the InSAR-based studies on fault kinematics and seismogenic structures related to some noted earthquakes on the Qinghai-Tibetan plateau. We highlight how the applications of InSAR data can greatly promote earthquake science and can be used as routine observations in some important areas. Then proceed to discuss the cutting-edge development trend and some new challenges of InSAR technology, which are frequently discussed and investigated, but not well resolved, in recent applications. The endeavors in increasing the precision of small-magnitude deformation measurements and expanding the InSAR data volumes can make the scientific objectives of earthquake disaster reduction on the Qinghai-Tibetan plateau and its surrounding areas feasible and reliable. To better understand how InSAR observations have changed the way we study earthquakes, we summarize the development, commercialization, insights, and existing challenges associated with InSAR coseismic deformation measurements and application in recent two decades.

The occurrence of earthquakes is closely related to the crustal tectonic movement and the migration of earth mass, which consequently cause the changes of the earth‘s gravitational field. Global time-varying gravity field data obtained by GRACE gravity satellite can be used to detect pre-seismic gravity anomalies. For example, gravity signals caused by several large earthquakes, such as the 2005 M_W8.6 Indonesia earthquake, the 2010 M_W8.8 Chile earthquake and the 2011 M_W9.0 Japan earthquake, have been successfully extracted using GRACE data. However, previous studies on GRACE satellite-based seismic gravity changes focused more on the dynamics of the co-seismic gravity field than on the pre-seismic gravity anomalies which are of great significance for the early warning of earthquakes. Moreover, the commonly adopted difference disposal of the gravity field with the gravity field of adjacent months or the average gravity field of many years when obtaining gravity anomalies cannot effectively remove the inherent north-south stripe noise in GRACE data. On the contrary, it is more likely to cause the annihilation of the medium-high order information in GRACE gravity field model, which results in the loss of some gravity information related to tectonic activities. To explore the pre-seismic gravity anomalies in a more refined way, this study proposes a method of characterizing gravity variation based on the maximum shear strain of gravity, inspired by the concept of crustal strain. In other words, the gravity strain tensor is obtained by further calculating the second-order gradient of the increment of disturbance potential after the removal of hydrological disturbance, and then the maximum shear strain of gravity is ultimately generated to characterize the pre-earthquake tectonic activities. Then, to better understand the seismogenic process of the fault zone by further extracting the pre-earthquake anomalous changes, the data of the maximum shear strain time series are analyzed in this study by means of the offset index K to describe the gravity anomaly. Because the maximum shear strain is calculated by the second-order gradient of GRACE gravity field, this method can suppress the stripe noise better than the difference disposal, thus effectively improving the sensitivity of gravity anomaly detection. The exploratory experiments are carried out in the Tibetan plateau and its surrounding area, which locates among the Pacific Ocean, the Indian Ocean and Eurasia, with the highest altitude, most complex topography and frequent strong earthquakes. Ultimately, the Wenchuan earthquake and Nepal earthquake were used as an example to complete the extraction of pre-earthquake gravity anomaly information by the above method, and the pre-earthquake tectonic activity of the fault zones was analyzed. The results show that a large area of gravity anomalies consistent with the spatial distribution of the fault zone appeared on the Longmenshan fault zone during the half a year before the earthquake, and the maximum anomalous value appeared within 50km from the epicenter, while no anomalies appeared during the non-earthquake period. In addition, compared with the traditional methods, the proposed method has a better ability to extract anomaly information of gravity field, which provides a new idea for understanding the dynamic mechanism of large earthquakes using GRACE data.

The reliability of anomaly extracting methods is crucial for pre-seismic thermal anomalies research. However, there is a lack of relevant researches. We compared two commonly used anomaly extracting methods, Z-score(ZS)and Robust satellite technology(RST)method, taking the 2014 Yutian earthquake as a typical example and the 2008 Wenchuan earthquake as a validation. The four aspects of extracted results are compared qualitatively and quantitatively, including the extraction effect, sensitivity to slight change, suppression of background information and indication of seismic information in the actual earthquake case. Moreover, the extracted results of validation case are used to validate the reliability of typical case results. Many intermittent anomalies in surface temperature and outgoing longwave radiation appeared before Yutian earthquake. The frequency of anomalies increases with the proximity of earthquake. The spatial distribution of surface temperature and outgoing longwave radiation anomalies gradually concentrated around the fault zone at the same time. The largest surface temperature and outgoing longwave radiation anomalies occurred one month before Yutian earthquake. The difference between the extraction results of ZS and RST method is mainly manifested in the frequency and amplitude of anomaly changes. The frequency and amplitude of anomaly changes obtained by RST method are higher than those obtained by ZS method. To further explore the reason for these differences, we further evaluate the two methods quantitatively by combining the data of two non-seismic years before and after Yutian earthquake respectively. The sensitivity of anomaly extraction method represents its ability to identify the slight changes of thermal parameters caused by the seismogenic process. The two methods are sensitive to slight changes, but the RST method is better than ZS method. The background information represents normal variation in surface temperature and outgoing longwave radiation caused by non-seismic factors. Suppression of background information determines the accuracy of extraction results. The comparison results show that both methods have certain suppression effect to background information, but the ZS method is better. The spatial distribution of pre-seismic thermal anomalies is an important index for predicting earthquake information(e.g. time of occurrence and location of epicenter). The results of quantitative comparison through normalized distance index show that for surface temperature data, ZS method is slightly better than RST method in indicating the location of epicenter. However, RST method is better for outgoing longwave radiation data. The maximum value of normalized distance index of ZS method occurred closer to the origin time of earthquake. We used the same quantitative evaluation method for the validation earthquake case. The verification results show that in addition to the sensitivity to anomaly changes, the comparison results of the two earthquake examples are similar in terms of the ability to suppress background information and indicate earthquake information. The difference is that ZS method has a better ability to suppress background information and RST method is better in indicating earthquake epicenter in the verification earthquake example. The main reason for the difference in extraction effect between the two methods is that the RST method averages the ground feature classification, and the difference between the observed value and the average value of the classification makes the RST method have a certain amplification effect on the weak signal. The difference between the typical earthquake case and the verification earthquake case is mainly due to the different complexity of the object types in the regions. Based on the above research results, we believe that ZS method and RST method have certain ability to extract pre-seismic anomalies. However, comparatively speaking, the RST method also has a good effect on the extraction of anomalies caused by other factors, and there is uncertainty in the ground feature classification. We believe that ZS method is a more appropriate and simple anomaly extraction method in the general seismic anomaly change extraction.

The May 21, 2021 Yangbi M_S6.4 earthquake occurred at the western boundary of the Chuandian tectonic block in southeast Tibetan plateau. The structural background is complex, with multiple active faults distributed around the epicenter area. Focal mechanism and seismic waveform inversion reveal that this earthquake is right-lateral strike-slip type with a NW-trending rupture plane. This accords with the strike and motion directions of the Weixi-Qiaohou and Red River faults along the western boundary of the Chuandian block.
We made a careful field investigation along the Weixi-Qiaohou Fault and around the epicenter area, and did not find any obvious earthquake surface rupture. But we observed a NW-trending ground fissure zone near the epicenter area to the west of the Yangbi County. This zone is divided into two sections, the Yangkechang-Paoshuitian section in the northwest and the Xiquewo-Shahe section in the southwest. These sections have a length of 2.5~3km and 3~3.5km, respectively, and are separated by a ~6km gap. They are characterized by NW-trending ground fissures with a width of several meters to tens meters. The formation of these fissures is inferred to be related to the tectonic movement under the ground, and the fissures have the following features: 1)they are not affected by the topography and cut the slope and range upward; 2)they are continuous and concentrated in a zone with a strike of NW 310°~320°, which is consistent with the belt of aftershocks and differs from the gravity fissures that usually have no regular strikes; 3)they usually have a plane dipping towards upslope(southwest), opposite to the valley; 4)they present shear property, not tensional. This zone thus is interpreted to be the surficial expression of the seismogenic fault of the Yangbi M_S6.4 earthquake.
Moreover, satellite image and field observation suggest that a~30km long linear structure with a NW strike traverses the epicenter area, which may suggest an undiscovered fault. Relocation of small earthquakes shows that the aftershocks are concentrated in a NW-trending belt that is consistent with the linear structure. Furthermore, the fissure zone lies in the northeast side of the aftershock belt, which suggests that the earthquake fault dips SW. Such a dip direction coincides with that of the observed fissure plane, and also agrees with the results from the focal mechanism and InSAR inversion. Both the focal mechanism and the waveform inversion result suggest that the Yangbi earthquake is a right-lateral strike-slip type, which is consistent with the type of the observed ground fissures. No displacement is observed on the fissures, with is also consistent with the InSAR inversion results that suggest the rupture did not break the surface. In addition, there is no coseismic deformation observed along the Weixi-Qiaohou Fault, which may indicate this fault did not move during this earthquake.
Based on our field investigation, in combination with the focal mechanism, aftershock distribution, and InSAR and GNSS inversion results, the seismogenic fault for this Yangbi M_S6.4 earthquake is believed to be a NW-trending(310°~320°)fault with a length of~30km, named as the Yangkechang-Shahe Fault. According to the location, size, and motion of the fault, it is suggested that the Yangkechang-Shahe Fault is a secondary fault of the Weixi-Qiaohou fault system. This fault has a slightly SW-dipping plane, and is dominated by right-lateral strike-slip motion, which may be a younger fault developed during the westward expansion of the western boundary of the Chuandian block.

Due to the ongoing collision between Indian and Eurasian plates, the internal blocks of the Tibet plateau are experiencing eastward extrusion. Resulting from the blocking of the Sichuan Basin along the eastern boundary of the Bayanhar block, the plateau begins to rotate clockwise around the eastern syntaxis, and continues to move toward the IndoChina Peninsula. Such process forms the Hengduan Mountains with thousands of gullies in the Sichuan-Yunnan region, and generates major earthquakes across the entire Red River Fault, where infrastructures and residents are seriously threatened by the frequent earthquakes. InSAR observations feature a high spatial resolution and short intervals, ranging from several days to over a month, depending on the satellite revisit period.
On May 21, 2021, an earthquake struck the Yangbi city. This event provides a rare opportunity to look at the local tectonic and seismic risk in the north of the Red River Fault. We processed the Sentinel-1 SAR data with D-InSAR technology and generated the surface deformation caused by the Yangbi M_S6.4 earthquake occurring on May 21, 2021. Due to the abundant vegetation and moisture in Yunnan, significant atmospheric noise needs to be corrected for the derived InSAR displacement field. The results show a maximum deformation of~0.07m in line-of-sight for ascending track and~0.08m for descending track. The quality of interferogram on the ascending track is low, and only one of the quadrans can be distinguished, the rest of the interferogram is regarded as phase noise. However, the descending interferogram contains two deformation regions, with its long axis roughly along the NW-SE direction. The northeast part of interferogram moves towards the satellite, while the southwest part moves away from the satellite. The InSAR interferograms pattern shows a right-lateral strike-slip movement. Then, we combined coseismic displacement data obtained from the Global Navigation Satellite System(GNSS)and InSAR(both the ascending and descending)to invert the coseismic slip model of the Yangbi earthquake. The inversion test shows that our data cannot give strong constraints for the dip orientations, and the two slip models with opposite dip orientation can explain the observations within the noise level. No matter what the dip orientation is, the slip models show that the coseismic slip concentrated at depth of 2~10km, with a maximum slip of~0.8m, which corresponds to a moment magnitude of M_S6.4, and is consistent with body-wave-based focal mechanism. But the relocated aftershocks in 3 hours immediately after the mainshock reveal a SW-dipping fault plane 10km away to the west of Weixi-Qiaohou-Weishan Fault, we therefore conclude that the Yangbi earthquake ruptured a SW-dipping dextral fault, which is previously unknown. To analyze the effects of the Yangbi earthquake on the seismic risk of the regional dextral faults, we estimated the Coulomb stress change caused by our preferred slip model. The Coulomb stress at 7.5km depth is negative, indicating stress unloading, while the Coulomb stress at 15km depth is positive, indicating slightly loading, but still less than the empirical triggering threshold. The results indicate that Yangbi earthquake partially relieved the strain accumulated on the nearby faults, thus restraining the seismic risk of these faults.

InSAR coseismic deformation fields caused by the Maduo M_W7.3 earthquake occurring on May 22, 2021 were generated using the C-band Sentinel-1A/B SAR images with D-InSAR technology. The spatial characteristics, magnitude of coseismic deformation and segmentation of the seismogenic fault were analyzed. The surface rupture trace was depicted clearly by InSAR observations. In addition, the coseismic slip distribution inversion was carried out constrained by both ascending and descending InSAR deformation fields and relocated aftershocks to understand the characteristics of deep fault slip and geometry of the seismogenic fault. The regional stress disturbance was analyzed based on coseismic Coulomb stress change. The results show that the Maduo M_W7.3 earthquake occurred on a secondary fault within the Bayan Har block which is almost parallel to the main fault trace of the Kunlun Fault. According to field investigation, geological data and InSAR surface rupture traces, the seismogenic fault is confirmed to be the Kunlunshankou-Jiangcuo Fault. The rupture length of seismogenic fault is estimated to be~210km. The NWW direction is followed by the overall displacement field, which indicates a left-lateral strike-slip movement of seismogenic fault. The maximum displacement is about 0.9m in LOS direction observed by both ascending and descending InSAR data. The inversion result denotes that the strike of the seismogenic fault is 276°and the dip angle is 80°. The maximum slip is about 6m and the average rake is 4°. The predicted moment magnitude is M_W7.45, which is overall consistent with the result of GCMT. An obvious slip-concentrated area is located at the depth of 0~10km. The coseismic Coulomb stress change with the East Kunlun Fault as the receiver fault shows that the Maduo earthquake produced obvious stress increase near the eastern segment of the East Kunlun Fault. Thus the seismic risk increases based on the high interseismic strain rate along this segment, which should receive more attention. In addition, the coseismic Coulomb stress change with the Maduo-Gande Fault as the receiving fault indicates that the Maduo earthquake produced an obvious stress drop near the western part of the Maduo-Gande Fault, which indicates that the Maduo earthquake released the Coulomb stress of the Maduo-Gande Fault, and its seismic risk may be greatly reduced. However, there is a stress loading effect in the intersection area of the Maduo-Gande Fault and the Kunlunshankou-Jiangcuo Fault. Considering that aftershocks of Maduo earthquake will release excess energy, the greater earthquake risk may be reduced.

In the global scale, ten destructive earthquakes with magnitude larger than 7 happen on average each year. Yet the number of small earthquakes with limited or even no damage but recordable by seismographs(magnitude between 2.5 and 4.5)is over one million per year. In between, there are hundreds to thousands of earthquakes with moderate to strong magnitude(magnitude between 5.5 and 6.5)with notable destructiveness. The massive moderate to strong earthquakes are often less noticed or even overlooked, with only very few exceptions which caused human casualties and/or structure damages due to the very shallow focal depths. For medium earthquakes, the traditional seismology means can obtain the source mechanism solution of earthquake, but because of the inherent fuzziness of the source mechanism, it cannot distinguish the fault plane from the auxiliary nodal planes, because earthquakes of this magnitude usually do not produce surface rupture, and the result error is large, so it is not suitable for the study of medium and small earthquakes. It is of fundamental significance to further study the source fault of the moderate earthquakes, and more independent methods other than traditional seismology, such as satellite geodesy are needed. As one of the most applied satellite geodesy technique, interferometry of SAR(InSAR)satellite images are commonly used to obtain coseismic deformation related to earthquakes. InSAR has very high spatial sampling, though the temporal sampling is very low, which is several days to over a month depending on the satellite revisit span. The precision of coseismic deformation by InSAR can reach 2~3cm, which is good enough to obtain the surface deformation caused by a moderate earthquake. It is noted that InSAR coseismic measurements can detect 1-dimensional(1D)deformation along Line-of-Sight(LOS)direction. With multiple observing modes including descending and ascending, the InSAR deformation data is very useful for identifying surface ruptures, and for source fault plane discrimination. As a new geodetic observation technology, InSAR uses the elastic dislocation model to obtain source parameters, and the inversion results of fault parameters and slip distribution are more reliable. On September 24th, 2019, an M_W6.0 earthquake hit New Mirpur, Pakistan. The nearest known fault to the epicenter is the Main Frontal Thrust on its south side. We used the Sentinel-1A SAR imagery(TOPS-model)to reconstruct the InSAR coseismic deformation fields generated by the 2019 M_W6.0 Pakistan earthquake along the ascending and descending tracks. The ascending and descending deformation fields indicate that coseismic deformation is asymmetric by a trend of NW-SE in the south secondary fault of the Himalayan frontal thrust fault, with a maximum LOS displacement of~0.1m. The structures of ascending and descending deformation are highly consistent with each other, but the LOS displacement of southern side is obviously larger than the northern side. The continuous change of interference fringes between uplift and subsidence areas shows that there is no coherent phenomenon caused by excessively large deformation gradient or surface rupture, which indicates that the seismic fault rupture did not reach to the ground surface. Two initial fault models constrained by InSAR deformation, with a southwest-dipping and northeast-dipping fault, were utilized in the inversion. We finally determined the northeast-dipping fault as the seismogenic fault by joint inversion of ascending and descending observations, combined with tectonic setting. Our fault model suggests that an obvious slip concentrated area is located in the depth of 2~4km, with a peak slip of~0.64m and a mean rake angle of~125°. The north-dipping thrust motion with a small amount of strike-slip component dominated the faulting. The earthquake occurred in the low-dipping subduction zone between the Indian and Eurasian plates. The dip angle of the fault plane is relatively low. When the fault is ruptured, the upper wall thrust southwards and the north wall subducted northwards. Due to the compressional nappe structure, the front end of the upper wall was uplifted and the back end was stretched to become the subsidence area. Seismogenic fault is the south secondary fault of the Himalayan frontal thrust fault inferred from our coseismic fault model and rupture kinematic features. Active faults on the land have caused many large destructive earthquakes, resulting in surface faults and promoting the development of tectonic landforms. The detailed observation of coseismic surface rupture not only provides basic information for understanding the earthquake itself and estimating the earthquake recurrence period, but also helps to interpret the tectonic and geomorphic features in other areas. Since the M_W6.0 earthquake in Pakistan in 2019, no studies have been reported yet on this earthquake using InSAR technology, so the study of this earthquake provides a rare opportunity to assess the seismic risk of active thrust faults and to study the seismicity of northern Pakistan.

The continuous collision between Tian Shan and Tarim Basin causes not only the uplift of mountains, but also the earthquakes across the entire Tian Shan, particularly in the transient zone from mountains to the adjacent basins, where the critical infrastructures and residents are seriously under threat from these earthquake hazards. On 19^th January, 2020, an earthquake occurred in the Kalpintage fold thrust belt in the southwest Tian Shan foreland. We call this event the 2020 M_W6.0 Kalpintage earthquake, which is the first moderate earthquake captured by modern geodetic measurement techniques. This event therefore provides a rare opportunity to look into the local tectonics and seismic risk in southwest Tian Shan. In this study, we obtained the coseismic deformation of 2020 M_W6.0 Kalpintage earthquake from Sentinel-1A SAR and strong motion data, and then inverted its kinematic slip model. We derived the InSAR interferograms from both ascending and descending tracks. Both of them present similar deformation patterns, two deformation peaks over the Kalpintage anticline. That means: 1)The surface deformation is dominated by vertical displacement, and 2)the coseismic rupture plane is highly suspected to be the shallowly dipping decollement at the base of the sediment cover. We got the 3-D displacements of 6 strong motion stations by double integrating the strong motion acceleration signals. The result shows tiny displacement on the strong motion stations, except for the Xikeer station, which locates at the front of the Kalpintage anticline, where the InSAR interferograms are seriously incoherent. Two slip models can equally fit to the ascending and descending InSAR interferograms: One is a strike slip model with strike of N-S, the other is a thrust model with strike of E-W. This ambiguity in the slip models for the M_W6.0 Kalpintage earthquake is caused by 1)the extremely small dip angles of the causative fault, 2)the inherent shortcomings of the InSAR measurements i.e. the 1-D measurements along the line of sight, the polar orbiting direction of the SAR satellite, and 3)the serious atmospheric delay due to contrasting topography in southwest Tian Shan. We did not distinguish the two ambiguous models with InSAR data due to the weak constraints of InSAR for this event. However, the two quite different slip models show the same spatial dimension and position beneath the Kalpintage anticline, also the same seismic slip vector moving toward the Tarim Basin. We then presumed the two slip models refer to the same fault plane, the weak decollement at the base of the sediment cover, and its rupture released the compressive strain in this fold and thrust belt in the southwest Tian Shan front. The confusing problem is neither the strike slip model nor the thrust model can explain the displacement derived from strong motion. The simple error estimates show small uncertainty in the strong-motion-derived displacement, but we cannot really know the real errors without the comparison to the collocated continuous GNSS observation. Because of the discrepancy between the strong motion displacement and InSAR-derived slip model, we speculate the inelastic deformation occurred in front of the Kalpintage anticline where thick weak sediments exist. We think this earthquake ruptured the decollements in the lower sediments bounded by the adjacent anticlines, which are uplifted in this event. The M_W6.0 Kalpintage earthquake balanced the stress accommodated during the convergence of the Tian Shan and Tarim Basin. We managed to explain all of the ruptures in the southwest Tian Shan by combining the regional tectonic, geophysical data and the available earthquake catalogues with good quality and then estimated the earthquake hazards. The earthquakes, including 1902 M_W7.7 karshigar, 1996 M_W6.3 Jiashi, 1997—2003 Jiashi sequence and 2020 M_W6.0 Kalpintage earthquake, can be explained in one frame, the underthrusting of the Tarim Basin toward the southwest Tian Shan. Our calculation suggests that a M_W7.0+ event could be generated around Kalpintage anticline belt if without barriers on the decollements.

The Aketao M_S6.7 earthquake occurred on November 25, 2016, which was located at the intersection of Gongur extensional system and Pamir frontal thrust. This region is characterized by complex fault structure, high altitude, complex terrain conditions, sparsely populated and few observed data, so the conventional geodetic survey technology is difficult to obtain comprehensive surface deformation information, while InSAR can take advantage of its all-weather, all-day, large-area and high-density continuous monitoring of ground motion. Therefore, this study takes M_S6.7 earthquake as the research object to carry out the co-seismic deformation field extraction and fault static slip distribution inversion. Firstly, the co-seismic deformation field was obtained by using ascending and descending data of Sentinel-1A. The results indicate that the interferogram spatial decorrelation is more serious in the north side of fault, which is affected by the steep terrain. The fringes in the south side of fault were distributed as elliptical semi-petal shapes, and the fringes are smooth and clear. The northern and southern part of the fault was asymmetric: The interferogram fringes of the southern part were dense while fewer fringes were formed in the northern part, and the fringes were semi butterfly-shaped on the surface. The horizontal displacements dominated the co-seismic deformation in this event, with magnitude of 12cm in ascending and -21cm in descending. The deformation occurred mainly on the south wall of fault. Based on the right view imaging of Radar, the co-seismic deformation is consistent with the movement features of dextral strike-slip fault and the focal mechanism provided by USGS and GCMT. The cross section of aftershocks after precisely positioning showed that the dip angle of fault is larger above the depth of 15km, which is generally manifested as the shovel-like structure with the dominant tendency of southward dip. By conducting a comprehensive analysis of deformation feature and aftershocks profile, we proposed that the southwest-dipping Muji Fault is the seismogenic fault. Secondly, a large area of continuous deformation images obtained by InSAR technology contains millions of data points and there is a high correlation between them. In order to ensure the calculation efficiency and inversion feasibility in the inversion process, the quadtree sampling method was used to reduce the number of data points and the datasets were finally obtained that can be received by the inversion system on the basis of retaining the original details of the deformation field. The two tracks InSAR datasets which were down-sampled by quadtree method were used to constrain the inversion to retrieve the fault geometry parameters and slip distribution. The single-segment and two-segment static slip distribution on the fault plane based on uniform elastic half space model were constructed during inversion process. The F-test of fitting residuals based on single-segment and double-segment fault model show that the population variance of the two models was significantly different at the confidence level of 95%, and the variance of the double-fault model was smaller. Through the comprehensive analysis of predicted deformation field, residuals and F-test, it is considered that the simulated results of double fault model are better than that of the single, and the observation data can be better interpreted. The result shows that the simulated co-seismic deformation field and its corresponding observed values were consistent in morphology and magnitude, and the correlation between observed and modeled is up to 0.99. In addition, as can be seen from the spatial distribution and frequency histogram of residuals, the overall residual was not large, mainly concentrated in the range of -0.2~0.2cm with the characteristics of normal distribution. However, there were still some larger residuals on the near fault in ascending track, which may be related to the simplified model. There were two patches with significant slip distribution on each segment and the rupture basically reached the surface. The slip was mainly distributed along the downdip range of 0~20km and was about 50km along the fault strike. The rupture reached the surface and the peak slip of 0.7m was at the depth of 9km. The western segment is dominated by the right-lateral strike-slip and the eastern segment is dominated by the right-lateral strike-slip with slightly normal faulting. The seismic moment derived from inversion was 8.81×10¹⁸N·m, which is equivalent to M_W6.57. The average slip angle obtained by inversion is -175° in the west section and -160° in the east section. The synthetic analysis holds that the source characteristics of the M_S6.7 earthquake was characterized by dextral strike-slip with a slightly normal component, which was composed of two sub-seismic events. The western section was basically pure right-lateral strike-slip with a dip angle of 75°, while the eastern was characterized by dextral strike-slip with a small amount of normal component with a dip angle of 55°. The Aketao earthquake occurred on the northern Pamir salient and its tectonic deformation was mainly characterized by crustal shortening, strike-slip and internal extension of the frontal edge observed by GPS. Generally speaking, the Pamir salient was blocked by nearly east-west South Tian Shan in the process of strong northward pushing under the action of NE direction pushing of Indian plate, and “hard and hard collision” occurred between them. The eastern part of Pamir salient extruded eastward along the nearly NS trending Gongur extensional system, and at the same time rotated clockwise, which caused the nearly EW extension since the Late Quaternary. The Aketao earthquake is a tectonic event occurring at Gongur Shan extensional system, which shows that the pushing of the Indian plate in the NE direction is continuously strengthened, and also implies that the internal crustal deformation of the Pamir Plateau is still dominated by extension in EW direction, which is basically consistent with the present observation of GPS.

There are many factors related to the variations of TEC, and the changes of TEC caused by earthquake only occupy a small portion. Therefore, it is vital how to exclude the ionospheric interference of non-seismic factors accurately in the process of seismic ionospheric anomaly extraction. This study constructed a TEC non-seismic dynamic background field considering the influence of solar and geomagnetic activities. Firstly, the TEC components of half-year cycle and annual cycle are extracted by wavelet decomposition. Then, it establishes a regression model between TEC in which periodic factors are removed and solar activity index, geomagnetic activity index with SVR method(support vector regression)in non-seismic period. Finally, based on the constructed model, the solar activity index and geomagnetic activity index is used to reconstruct aperiodic components of TEC in earthquake's period. From the reconstructed aperiodic components of TEC plus the half-year periodic components and annual periodic components of TEC in the same period, the non-seismic dynamic background field is obtained. Comparing the residuals relative to original TEC values in non-seismic dynamic background field and traditional sliding window background, there are apparent monthly periodic change and semi-annual periodic change in the residuals of sliding window background, which can have obvious impacts on the subsequent seismic ionospheric anomaly detection. In order to test the validity of seismic TEC anomaly detection based on the background field construction method, this paper investigated the long time series TEC anomalies near Wenchuan city(30°N, 100°E)from March 1 to September 26 in 2008. It is found that under the condition of non-seismic disturbance such as solar activity and geomagnetic activity, TEC abnormal disturbance is rarely detected by non-seismic dynamic background field method, when compared with the traditional sliding time-window method. And before the earthquake, more TEC anomalies were detected based on the proposed method, also, they were more intense than those extracted by sliding window method. Therefore, the TEC background field construction method based on SVR(support vector regression)has superiorities in both system errors elimination, which are caused by solar, geomagnetism, the non-seismic ionospheric disturbance events and periodic fluctuations of TEC, and in reducing the false alarm rate of seismic TEC anomaly. Moreover, it can also improve the seismic TEC anomaly detection ability. In addition, this paper analyzed the time-spatial distribution of TEC anomaly before three earthquakes on May 12, August 21 and August 30, 2008. They were mainly negative abnormal perturbations and often distributed on the equatorial side of epicenter.

It has been reported that there is thermal anomaly within a certain time and space preceding an earthquake, and previous research has indicated potential associations between the thermal anomaly and earthquake faults, but it is still controversial whether physical processes associated with seismic faults can produce observable heat.Based on rock experiments, some scholars believe that the convective and stress-induced heat associated with fault stress changes may be the cause of those anomalies. Then, did the thermal anomaly before the Wenchuan earthquake induced by the fault stress change?It remains to be tested by numerical simulations on the distribution and intensity of thermal anomalies. For example, is the area of thermal anomaly caused by the fault stress changes before the earthquake the same as the observation?Is the intensity the same?To clarify the above questions, a two-dimensional thermo-hydro-mechanical(THM)finite element model was conducted in this study to simulate the spatial and temporal variations of thermal anomalies caused by the underground fluid convection and rock stress change due to the tectonic stress release on fault before earthquake. Results showed that the simulated thermal anomalies could be consistent with the observed in magnitude and spatio-temporal distribution. Before the Wenchuan earthquake, deformation-related thermal anomalies occurred mainly in the fault zone and its adjacent hanging wall, which are usually abnormal temperature rise, and occasionally abnormal cooling, occurring in the fault zone after the peak temperature rise. In the fault zone, the thermal anomaly is usually greater than the order of 1K of the equivalent air temperature and is controlled by the combined effect of fluid convection and stress change. The temperature increases first and then decreases before the earthquake. In the hanging wall, it's weaker than that of the fault zone, mainly depending on the convection of the fluid. The temperature gradually increases before the earthquake and is dramatically affected by the permeability. Usually, only when the permeability is larger than 10^-13m², can the air temperature rise higher than 1K occur. The results of this study support the view that fluid convection and stress change caused by fault slip before the earthquake can produce observable air temperature anomalies.

Located at the bend of the northeastern margin of Qinghai-Tibet Plateau, the Haiyuan fault zone is a boundary fault of the stable Alashan block, the stable Ordos block and the active Tibet block, and is the most significant fault zone for the tectonic deformation and strong earthquake activity. In 1920, a M8.5 earthquake occurred in the eastern segment of the fault, causing a surface rupture zone of about 240km. After that, the segment has been in a state of calmness in seismic activity, and no destructive earthquakes of magnitude 6 or above have occurred. Determining the current activity of the Haiyuan fault zone is very important and necessary for the analysis and assessment of its future seismic hazard.
To study activity of the Haiyuan fault zone, the degree of fault coupling and the future seismic hazard, domestic and foreign scholars have carried out a lot of research using geology methods and GPS geodetic techniques, but these methods have certain limitations. The geology method is a traditional classical method of fault activity research, but dislocation measurement can only be performed on a local good fault outcrop. There are a limited number of field measurement points and the observation results are not equally limited depending on the sampling location and sampling method. The distribution of GPS stations is sparse, especially in the near-fault area, there is almost no GPS data. Therefore, the spatial resolution of the deformation field features obtained by GPS is low, and there are certain limitations in the kinematic parameter inversion using this method.
In this study, we obtain the average InSAR line-of-sight deformation field from the Maomaoshan section to the mid-1920s earthquake rupture segment of the Haiyuan earthquake in the period from 2003 to 2010 based on the PSInSAR technique. The results show that there are obvious differences between the slip rates of the two walls of the fault in the north and the south, which are consistent with the motion characteristics of left-lateral strike-slip in the Haiyuan fault zone. Through the analysis of the high-density cross-fault deformation rate profile of the Laohushan segment, it is determined that the creep length is about 19km. Based on the two-dimensional arctangent model, the fault depth and deep slip rate of different locations in the Haiyuan fault zone are obtained. The results show that the slip rate and the locking depth of the LHS segment change significantly from west to east, and the slip rate decreases from west to east, decreasing from 7.6mm/a in the west to 4.5mm/a in the easternmost. The western part of the LHS segment and the middle part are in a locked state. The western part has a locking depth of 4.2~4.4km, and the middle part has a deeper locking depth of 6.9km, while the eastern part is less than 1km, that is, the shallow surface is creeping, and the creep rate is 4.5~4.8mm/a. On the whole, the 1920 earthquake's rupture segment of the Haiyuan fault zone is in a locked state, and both the slip rate and the locking depth are gradually increased from west to east. The slip rate is increased from 3.2mm/a in the western segment to 5.4mm/a in the eastern segment, and the locking depth is increased from 4.8km in the western segment to 7.5km in the eastern segment. The results of this study refine the understanding of the slip rate and the locking depth of the different segments of the Haiyuan fault zone, and provide reference information for the investigation of the strain accumulation state and regional seismic hazard assessment of different sections of the fault zone.

The development of high-rate GNSS seismology and seismic observation methods has provided technical support for acquiring the near-field real-time displacement time series during earthquake. But in practice, the limited number of GNSS continuous stations hardly meets the requirement of near-field quasi-real-time coseismic displacement observation, while the macroseismographs could be an important complement. Compared with high-rate GNSS, macroseismograph has better sensitivity, higher resolution(100~200Hz)and larger dynamic range, and the most importantly, lower cost. However, baseline drift exists in strong-motion data, which limits its widespread use. This paper aims to prove the feasibility and reliability of strong motion data in acquiring seismic displacement sequences, as a supplement to high-rate GNSS.
In this study, we have analyzed the strong-motion data of Wenchuan M_S8.0 earthquake in Longmenshan fault zone, based on the automatic scheme for empirical baseline correction proposed by Wang et al., which fits the uncorrected displacement by polynomial to obtain the fitting parameters, and then the baseline correction is completed in the velocity sequence. Through correction processing and quadratic integration, the static coseismic displacement field and displacement time series are obtained. Comparison of the displacement time series from the strong motions with the result of high-rate GPS shows a good coincidence. We have worked out the coseismic displacement field in the large area of Wenchuan earthquake using GPS data and strong motion data. The coseismic displacement fields calculated from GPS and strong motions are consistent with each other in terms of magnitude, direction and distribution patterns. High-precision coseismic deformation can provide better data constraint for fault slip inversion. To verify the influence of strong-motion data on slip distribution in Wenchuan earthquake, we used strong motion, GPS and InSAR data to estimate the stress drop, moment magnitude and coseismic slip model, and our results agreed with those of the previous studies. In addition, the inversion results of different data are different and complementary to some extent. The use of strong-motion data supplements the slip of the fault in the 180km segment and the 270~300km segment, thus making the inversion results of fault slip more comprehensive.
From this result, we can draw the following conclusions:1)Based on the robust baseline correction method, the use of strong motion data, as an important complement to high-rate GNSS, can obtain reliable surface displacement after the earthquake. 2)The strong motion data provide an effective method to study the coseismic displacement sequence, the surface rupture process and quick seismogenic parameters acquisition. 3)The combination of multiple data can significantly improve the data coverage and give play to the advantages of different data. Therefore, it is suggested to combine multiple data(GPS, strong motion, InSAR, etc.)for joint inversion to improve the stability of fault slip model.

On November 18, 2017, a M_S6.9 earthquake struck Mainling County, Tibet, with a depth of 10km. The earthquake occurred at the eastern Himalaya syntaxis. The Namche Barwan moved northward relative to the Himalayan terrane and was subducted deeply beneath the Lhasa terrane, forming the eastern syntaxis after the collision of the Indian plate and Asian plates. Firstly, this paper uses the far and near field broadband seismic waveform for joint inversion (CAPJoint method)of the earthquake focal mechanism. Two groups of nodal planes are obtained after 1000 times Bootstrap test. The strike, dip and rake of the best solution are calculated to be 302°, 76° and 84° (the nodal plane Ⅰ)and 138°, 27° and 104° (the nodal plane Ⅱ), respectively. This event was captured by interferometric synthetic aperture radar (InSAR)measurements from the Sentinel-1A radar satellite, which provide the opportunity to determine the fault plane, as well as the co-seismic slip distribution, and assess the seismic hazards. The overall trend of the deformation field revealed by InSAR is consistent with the GPS displacement field released by the Gan Wei-Jun's team. Geodesy (InSAR and GPS)observation of the earthquake deformation field shows the northeastern side of the epicenter uplifting and the southwestern side sinking. According to geodetic measurements and the thrust characteristics of fault deformation field, we speculate that the nodal plane Ⅰ is the true rupture plane. Secondly, based on the focal mechanism, we use InSAR data as the constraint to invert for the fine slip distribution on the fault plane. Our best model suggests that the seismogenic fault is a NW-SE striking thrust fault with a high angle. Combined with the slip distribution and aftershocks, we suggest that the earthquake is a high-angle thrust event, which is caused by the NE-dipping thrust beneath the Namche Barwa syntaxis subducted deeply beneath the Lhasa terrane.

In this paper, we processed and analyzed the Sentinel-1A data by "two-pass" method and acquired the surface deformation fields of Menyuan earthquake. The results show the deformation occurred mainly in the south wall of fault, where uplift deformation is dominant. The uplift deformation is significantly larger than the subsidence and the maximum uplift of ascending and descending in the LOS is 6cm, 8cm respectively. Meanwhile, based on the Okada model, we use the ascending and descending passes data as constraints to invert jointly the fault distribution and source parameters through constructing fault model of different dip directions. The optimum fault parameters are:The dip is 43°, the strike is 128°with the mean rake of 85°. The maximum slip is about 0.27m. The inverted seismic moment M₀ is 1.13×10¹⁸N·m, and the moment magnitude M_W is 5.9. The SW-dipping Minyue-Damaying Fault is possibly the seismogenic fault, based on the comprehensive analysis of the focal mechanisms, aftershocks relocation results and the regional tectonic background. The focus property is dominated by thrust movement with a small amount of dextral strike-slip component. The earthquake is the result of local stress adjustment nearby the Lenglongling Fault under the background of northeastward push and growth of Tibet Plateau.

The May 12, 2008 M_S7.9 Wenchuan earthquake is ranked as one of the most devastating natural disasters ever occurred in modern Chinese history. The Longmenshan Fault(LMSF) zone is the seismogenic source structure, which consists of three sub-parallel faults, i.e., the Guanxian-Jiangyou Fault(GJF) in the frontal, the Yingxiu-Beichuan Fault(YBF) in the central fault and the Wenchuan-Maowen Fault(WMF) in the back of the LMSF. In this study, geological survey and seismic profiles are used to constrain the faults geometry and medium parameters. Three visco-elastic finite element models of the LMSF with different main faults are established. From the phase of interseismic stress accumulation to coseismic stress release and postseismic adjustment, the Wenchuan earthquake is simulated using Continuous-Discrete Element Method(CDEM). Modeling results show that before the 2008 Wenchuan earthquake, the GJF becomes unstable due to the interaction between its unique fault geometry and the tectonic stress loading. In the fault geometry model, the GJF is the most gently dipped fault among the three faults, which in return makes it having the smallest normal stress and the greatest shear stress. The continuous shear stress loading finally meets the fault failure criteria and the Wenchuan earthquake starts to initiate on the GJF at the depth of 15~20km. The earthquake rupture then propagated to the YBF. At the same time, due to the GJF and YBF rupture, the interseismic stress accumulation has been greatly reduced, causing the WMF failed to rupture. Although the stress accumulation in the WMF has been reduced significantly after the earthquake, yet it has not been released completely, which means that the WMF likely has with high seismic risk after the 2008 Wenchuan earthquake. We also find that the stress perturbation caused by gently dipping segment of the fault can promote the passive rupture in the steeply dipping segment, making the upper limit of dip angles larger than traditional assumption.

This study focuses on four moderate-sized earthquakes in the northern margin of the Qaidam Basin, northeastern Tibet Plateau, China, of which one occurred in 2008, and three in 2009, respectively. We obtain coseismic displacement fields of these four events using Envisat descending ASAR data and D-InSAR technology. The results show that the 2008 earthquake has only one deformation center and the 2009 earthquakes have three deformation centers in their fields. The maximum displacement of 2008 and 2009 earthquakes are 0.097m and 0.41m in the LOS(line of sight), respectively. We invert ground displacements of these earthquakes based on elastic dislocation models to estimate slip distribution on fault planes. For the 2008 event, using a one-segment fault model, the inversion reveals peak slip of about 0.47m occurring at a depth of 19km. For the 2009 earthquakes, the ground displacement pattern observed by InSAR can be fitted by a three-segment fault model with smallest RMS of residuals. The three sectional fault model is considered the most reliable.

According to the structure of the Himalayan orogenic belt, a low-angle antilistric thrust-slip fault model is used to simulate the ramp on the rupture portion of the Main Himalayan Fault. Based on descending Alos -2 and Sentinal -1 data, we invert for the coseismic slip models of the Gorkha earthquake and its largest aftershock, Kodari earthquake. In contrast to the inversion using Alos -2 or Sentinal -1 separately, the joint inversion of both data sets has stronger constraint for the deep slip and can obtain more details in Gorkha earthquake. The rupture depth obtained by joint inversion can be as deep as 24km underground, cutting across the locking line to the transition of locked and the creeping zone. The largest slip is as large as 4.5m appearing 17km underground and the dip angle is between 3°and 10°. Gorkha and Kodari earthquakes have the similar focal mechanisms, both of which are mainly thrusting, and yet some right-lateral slip component in Gorkha earthquake. The inversion results reveal that slip models of the Nepal mainshock and its largest aftershock are complementary in space and the Kodari earthquake occurs in the gaps of slip in Gorkha earthquake. The epicenter of the Kodari earthquake is just right in the transitive zone of the positive and negative Coulomb stress change, where the Coulomb stress change can reach 0.4MPa. We thus argue that Kodari earthquake has been triggered by the Gorkha earthquake.

The 2008 Gaize M_W6.4 earthquake,occurring on the tensional active fault zone located between Lhasa terrane and Qiangtang terrane in the interior of Tibet is a typical normal-faulting event.In this paper,we resolve the three-dimensional coseismic displacement fields of the earthquakes using a least-square iterative approximation solution with a priori knowledge,according to the theoretical basis that InSAR measurements are extremely insensitive to N-S component.Results show that the boundary dividing the two sides of the main-shock fault is very clear in the vertical movement,and two remarkable subsidence centers can be observed on the hanging wall,while amplitude of the west one (-48.9cm) is larger than the east (-41.4cm),but the maximum uplift on the footwall is only 5cm.In addition to some northward movement with amplitude less than 5cm around the aftershock fault,the north-south deformation field suggests an overall southward movement.The three-dimensional results indicate that the induced surface movement is predominantly vertical and mostly occurred on the upper side,while there are obvious east-west separation and eastward rotation in the horizontal plane.The full vectors are consistent with simulated deformation field with the RMSE less than 6cm,so the research demonstrates the feasibility of the method to recover precise three-dimensional deformation field.On the whole,the three-dimensional deformation field coincides with the tensile fracture characteristics of Gaize earthquakes,and the tectonic stress background of coeval east-west extension and north-south shortening.

There are thermal infrared anomalies(TIA)before earthquake, and TIA has become one of the important parameters for assessing regional earthquake risk. However, not all of the surface infrared anomalies are related to tectonic activities or earthquakes. How to eliminate the influence of non-structural factors and extract the weak signals from strong disturbances is the key and difficult point for tectonic activities studies based on the thermal infrared remote sensing techniques. Land surface temperature(LST)background field is the basis for thermal infrared anomalies extraction. However, the established background fields in previous researches cannot eliminate the influence of climate changes, so the accuracy of thermal anomaly extraction is limited. Now an improved method is proposed. Combined with the periodic character of LST time series, harmonic analysis is lead into the process of LST background field establishment. Specifically, the yearly trend of LST is fitted based on Fourier Approximation method. As a new background field, the yearly trend is dynamic, includes the local and the yearly information. Then, based on the rule of "kσ", the earthquake anomalies, calculated by RST with the yearly trend of LST, can be extracted. At last, the effectiveness of the algorithm can be tested by the quantitative analysis of anomalies with anomaly area statistics, anomaly intensity statistics and distance index statistics. The Wenchuan earthquake was discussed again based on the proposed algorithm with MODIS land temperature products in 2008. The results show that, there were obvious pre-earthquake thermal anomalies along the Longmen Mountains faults with a longer time; but there were no anomalies when the earthquake happened; and the post-earthquake thermal anomalies occurred with much smaller amplitudes and scopes. Compared with the results derived from the traditional RST which is based on the spatial average of LST values, the TIA extracted by the new RST, which is based on the yearly trend of LST, is more fit with the active faults, and the process of the anomalies occurring and removing can be described in more detail. Therefore, as the background field to extract earthquake anomalies, the yearly trend of LST is more reliable.

We achieved the coseismic displacements of the Napa M_W6.1 earthquake located in California US occurring on 24 August 2014 by using InSAR data from the newly launched ESA's Sentinel-1A satellite. The 30m×30m ASTER GDEM was used to remove the terrain effect, and phase unwrapping method of branch-cut algorithm was adopted. In order to obtain a better coseismic displacement field, we also tested 90m×90m SRTM data to remove the terrain effect and Minimum Cost Flow algorithm to unwrap the phase. Results showed that the earthquake caused a significant ground displacement with maximum uplift and subsidence of 0.1m and -0.09m in the satellite light of sight(LOS). Based on the Sentinel-1A dataset and sensitivity based iterative fitting(SBIF) method of restrictive least-squares algorithm, we obtained coseismic fault slip distribution and part of the earthquake source parameters. Inversion results show that the strike angle is 341.3°, the dip angle is 80°, rupture is given right-lateral fault, average rake angle is -176.38°, and the maximum slip is ~0.8m at a depth of 4.43km. The accumulative seismic moment is up to 1.6×10¹⁸N·m, equivalent to a magnitude of M_W6.14.

Earthquake prediction is one of the key areas of earthquake research. Thermal infrared abnormity, which is the abnormally increased land surface temperature, is universal before earthquake and has complex nonlinear relation with the three elements of earthquake. Combining the advantage of neural network, this paper provides a method for earthquake prediction by taking thermal anomaly as information source and constructing a neural network to carry out the test. Based on the MODIS data which has synthesis of eight days with 1km resolution, taking a 10°×10° rectangle, whose center is the epicenter, as research area, and a two-month time before earthquake as the time range, we used RST algorithm to extract thermal anomaly information before earthquake. Considering the time-space relationship between thermal anomaly information and the fault zone, thinking carefully about the information of the neural network input neurons, we constructed BP neural network and used 100 earthquake cases with magnitudes larger than 5, and 70 random samples without earthquake in the research region for training and simulating. According to the statistical analysis, the prediction accuracy is 80%, missing prediction rate is 20%, and false prediction rate is 13.3%. Prediction accuracy of magnitude with error within magnitudes of 2 is 69%, prediction accuracy of earthquake origin time with error within 30 days is 87.5%, and prediction accuracy of epicenter location with error within 3°is 81.2%. The result shows that BP neural network-based earthquake prediction is feasible by using thermal infrared abnormal precursor extracted by RST method. However, in this experiment, the determination of the start time of thermal abnormity, the origin point and range of research area are based on the known epicenter location and time. In fact, the result depicts a non-linear relationship between earthquake and thermal abnormity, and the accuracy of prediction reflects the correlation degree. Therefore, the prediction accuracy of future earthquake may be not as large as our result. For future earthquake prediction, accurate selection of research area and neuron number of hidden layer in neural network has great influence on prediction result.

The variance component estimation method (VCEM) in generalized surveying adjustment theory, which realizes optimal weights allocation for different data sources, is applied to jointly invert two independent datasets, InSAR and GPS, for 3-D deformation field acquisition in this paper. Illustrated by the case of the Wenchuan earthquake, 3-D deformation field in high coherent area near the fault is achieved by using this method, which shows clearly a whole picture for the locations of right-lateral and thrust components movements generated by the earthquake. The 3-D deformation results are quantitatively consistent with GPS observations with RMS errors less than 5cm in 3-D directions, which demonstrates the feasibility to acquire precise 3-D deformation field by employing VCEM to fuse independent deformation datasets.

Strong earthquake-induced landslides in mountainous region often cause serious damages to buildings, transportation route, lifeline engineering etc. It is one of the major reasons causing significant casualties and economic losses of property. For such serious and wide range disasters, doing classification for earthquake-induced landslide hazard zones is one of the effective methods for reducing losses. This paper, based on former studies, takes Lushan earthquake on April 20, 2013 as a sample and selects Lushan County, Baoxing County and the surrounding area, which were influenced seriously by landslide, as a study area. This paper takes comprehensive indexes method to classify earthquake-induced landslide hazard zones for this area. There are 5 impact factors, including lithology, slope, seismic intensity, distances from faults and distances from drainages, are selected and weight is determined for each factor by AHP (the Analytic Hierarchy Process). The study area then is classified into 4 levels of hazards zones by comprehensive indexes method to indicate possibilities of triggering landslide in region under the suffering from given seismic intensities. The paper makes a comparison between the existing landslide sites map and the earthquake-induced landslide hazard zoning map. The results show a relatively high match between the two maps (about 77% landslide sites are in the higher hazard zones and highest hazard zones). This research will provide a reference for emergency response of earthquake-induced landslide disaster, prediction of earthquake-induced landslides in mountainous area and prevention of landslide disaster.

In the past few years, the improved InSAR technology based on time series analyses to many SAR images has been used for measurement of interseismic deformation along active fault. In the paper, we first made a summary and introduction to the basic principle and technical characteristics of existing Time Series InSAR methods(such as Stacking, PSInSAR, SBAS). Then we presented a case study on the central segment of Haiyuan Fault in west China. We attempt to use the PS-InSAR(Permanent Scatter InSAR)technique to estimate the motion rate fields of this fault. We processed and analyzed 17 scenes of ENVISAT/ASAR images in descending orbits from 2003-2010 using the PS-InSAR method. The results reveal the whole movement pattern around the Haiyuan Fault and a remarkable velocity gradient of about 5mm/a across the central segment of the fault. The motion scenes are consistent with left-lateral strike-slip. On this basis, we make a discussion on some issues about observation of fault activity using Time Series InSAR methods, such as the changes of LOS deformation rates with fault strike and region width observed across a fault, fault reciprocity and motion style indicated by Time Series InSAR rate map and the relationship between the InSAR LOS deformation and the ones from other methods. All these studies will benefit the promotion of InSAR application in detection of tectonic movement.

Vertical coseisimic deformation near seismogenic fault is one of the most important parameters for understanding the fault behavior, especially for thrust or normal fault, since near field vertical deformation provides meaningful information for understanding the rupture characteristics of the seismogenic fault and focal mechanism. Taking Wenchuan thrust earthquake for an example, we interpolate GPS horizontal observed deformation using Biharmonic spline interpolation and derive them into east-westward or north-southward deformation field. We first use reliable GPS observed value to correct InSAR reference point and unify both GPS and InSAR coordinate frame. We then make a profile using InSAR data and compare it to that from GPS data and we find GPS and InSAR observation reference point has a 9.93cm difference in the hanging wall side, and around -11.49cm in the footwall. After correction, we obtain a continuous vertical deformation field of the Wenchuan earthquake by combined calculation of GPS and InSAR LOS deformation field. The results show that the vertical deformation of both hanging wall and foot wall of the fault decreases rapidly, with deformation greater than 30cm within 50km across the fault zone. The uneven distribution of the vertical deformation has some peak values at near fault, mainly distributed at the southern section(the town of Yingxiu), the middle(Beichuan)and the northern end(Qingchuan)of the seismogenic fault. These three segments have their own characteristics. The southern section of the fault has an obvious asymmetric feature, which exhibits dramatic uplift reaching 550cm on the hanging wall, with the maximum uplift area located in Yingxiu town to Lianshanping. The middle section shows a strong anti-symmetric feature, with one side uplifting and the other subsiding. The largest uplifting of the southern segment reaches around 255cm, located at the east of Chaping, and the largest subsiding is in Yongqing, reaching around -215cm. The vertical deformation of the northern section is relatively small and distributed symmetrically mainly in the north of Qingchuan, with the maximum uplift to be 120cm, locating in the northernmost of the seismogenic fault.