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Monitoring and Modelling of Geological Disasters Based on InSAR Observations II

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (20 January 2024) | Viewed by 23371

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Special Issue Editors

Dr. Chisheng Wang

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Guest Editor

School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China
Interests: Disaster and infrastructure monitoring; InSAR; point cloud processing; photogrammetry
Special Issues, Collections and Topics in MDPI journals

Dr. Bochen Zhang

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MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China
Interests: InSAR; UAV-InSAR; ground-based radar interferometry; geohazards; infrastructures
Special Issues, Collections and Topics in MDPI journals

Dr. Chuanhua Zhu

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Guest Editor

Ministry of Natural Resources (MNR) Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics, School of Architecture & Urban Planning, Shenzhen University, Shenzhen 518060, China
Interests: InSAR; Geological disaster; Disaster monitoring
Special Issues, Collections and Topics in MDPI journals

Dr. Biao Lu

E-Mail Website
Guest Editor

Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milan, MI, Italy
Interests: seismics; satellite gravimetry; crust modelling; geohazard monitoring

Special Issue Information

Dear Colleagues,

With our first Special Issue, open from 2021 to 2022, we published 16 state-of-the-art research articles covering such topics as PS, DS, deformation parameter inversion, motoring deformation (e.g., earthquakes, volcanoes, and oil extraction ), and driving mechanism interpretation, among others (https://www.mdpi.com/journal/remotesensing/special_issues/InSAR_Geological_Disasters). These excellent reports significantly contribute to further developments in the monitoring and modeling of geological disasters using InSAR techniques. Meanwhile, an increasing number of scholars are expressing their willingness to submit and publish their research output in our journal. Therefore, we are launching a second edition of this Special Issue.

Interferometric synthetic aperture radar (InSAR) has demonstrated its potential in monitoring geological disasters, e.g., related to subsidence, landslides, earthquakes, and volcanoes. Such monitoring results provide significant information for further physical modeling, driving mechanism interpretation, developments in early warning technology, and the management and formulation of policies by authorities and stakeholders. Recently, more advanced InSAR methods have been developed for geological disaster monitoring and modeling. For instance, integration of multi-sensor SAR data improves the temporal resolution. Advanced distributed scatterer interferometry algorithms increase the possibility of measuring low-coherent areas. Introducing machine/deep learning improves the quality of phase unwrapping and decreases errors in InSAR processing. Deep neural networks even make it possible to directly invert geophysical parameters of disasters from SAR interferograms. Uncertainty analysis of InSAR results further increases the readability of monitoring results.

This Special Issue aims at publishing studies covering different applications by InSAR technique, especially monitoring and modeling of geological disasters. Topics may cover any aspect from ground displacement monitoring to inversion of geophysical parameters. Multi-source data integration (e.g., InSAR, GNSS, and ground sensors), advanced InSAR approaches, geological disaster modeling, and other relevant issues are all welcome. Monitoring results based on InSAR technique promote the development of remote sensing science and expand the scope of remote sensing technique applications.

Articles may address, but are not limited to, the following topics:

Multisource monitoring data integration
Geo-hazard detection
Disaster catalog compilation
Parameter inversion
Innovative InSAR applications
Advanced InSAR algorithms

Dr. Chisheng Wang
Dr. Bochen Zhang
Dr. Chuanhua Zhu
Dr. Biao Lu
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

InSAR
geological disaster
disaster monitoring
disaster modeling and interpretation

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Monitoring and Modelling of Geological Disasters Based on InSAR Observations: 3rd Edition in Remote Sensing

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21 pages, 30297 KiB

Open AccessArticle

A Bayesian Source Model for the 2022 Mw6.6 Luding Earthquake, Sichuan Province, China, Constrained by GPS and InSAR Observations

by Guangyu Xu, Xiwei Xu, Yaning Yi, Yangmao Wen, Longxiang Sun, Qixin Wang and Xiaoqiong Lei

Remote Sens. 2024, 16(1), 103; https://doi.org/10.3390/rs16010103 - 26 Dec 2023

Cited by 1 | Viewed by 1282

Abstract

Until the Mw 6.6 Luding earthquake ruptured the Moxi section of the Xianshuihe fault (XSHF) on 5 September 2022, the region had not experienced an Mw >6 earthquake since instrumental records began. We used Global Positioning System (GPS) and Sentinel-1 interferometric synthetic aperture radar (InSAR) observations to image the coseismic deformation and constrain the location and geometry of the seismogenic fault using a Bayesian method We then present a distributed slip model of the 2022 Mw6.6 Luding earthquake, a left-lateral strike-slip earthquake that occurred on the Moxi section of the Xianshuihe fault in the southwest Sichuan basin, China. Two tracks (T26 and T135) of the InSAR data captured a part of the coseismic surface deformation with the line-of-sight displacements range from ∼−0.16 m to ~0.14 m in the ascending track and from ~−0.12 m to ~0.10 m in the descending track. The inverted best-fitting fault model shows a pure sinistral strike-slip motion on a west-dipping fault plane with a strike of 164.3°. We adopt a variational Bayesian approach and account for the uncertainties in the fault geometry to retrieve the distributed slip model. The inverted result shows that the maximum slip of ~1.82 m occurred at a depth of 5.3 km, with the major slip concentrated within depths ranging from 0.9–11 km. The InSAR-determined moment is 1.3 × 10¹⁹ Nm, with a shear modulus of 30 GPa, equivalent to Mw 6.7. The published coseismic slip models of the 2022 Luding earthquake show apparent differences despite the use of similar geodetic or seismic observations. These variations underscore the uncertainty associated with routinely performed source inversions and their interpretations for the underlying fault model. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations II)

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19 pages, 5458 KiB

Open AccessArticle

A Simulation Framework of Unmanned Aerial Vehicles Route Planning Design and Validation for Landslide Monitoring

by Dongmei Xie, Ruifeng Hu, Chisheng Wang, Chuanhua Zhu, Hui Xu and Qipei Li

Remote Sens. 2023, 15(24), 5758; https://doi.org/10.3390/rs15245758 - 16 Dec 2023

Cited by 5 | Viewed by 1848

Abstract

Unmanned aerial vehicles (UAVs) have emerged as a highly efficient means of monitoring landslide-prone regions, given the growing concern for urban safety and the increasing occurrence of landslides. Designing optimal UAV flight routes is crucial for effective landslide monitoring. However, in real-world scenarios, the testing and validating of flight path planning algorithms incur high cost and safety concerns, making overall flight operations challenging. Therefore, this paper proposes the use of the Unreal Engine simulation framework to design UAV flight path planning specifically for landslide monitoring. It aims to validate the authenticity of the simulated flight paths and the correctness of the algorithms. Under the proposed simulation framework, we then test a novel flight path planning algorithm. The simulation results demonstrate that the model reconstruction obtained using the novel flight path algorithm exhibits more detailed textures, with a 3D model simulation accuracy ranging from 10 to 14 cm. Among them, the RMSE value of the novel flight route algorithm falls within the range of 10 to 11 cm, exhibiting a 2 to 3 cm improvement in accuracy compared to the traditional flight path algorithm. Additionally, it effectively reduces the flight duration by 9.3% under the same flight path compared to conventional methods. The results confirm that the simulation framework developed in this paper meets the requirements for landslide damage monitoring and validates the feasibility and correctness of the UAV flight path planning algorithm. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations II)

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17 pages, 42609 KiB

Open AccessArticle

Coseismic Deformation, Fault Slip Distribution, and Coulomb Stress Perturbation of the 2023 Türkiye-Syria Earthquake Doublet Based on SAR Offset Tracking

by Wan Wang, Yunhua Liu, Xiaoran Fan, Chao Ma and Xinjian Shan

Remote Sens. 2023, 15(23), 5443; https://doi.org/10.3390/rs15235443 - 21 Nov 2023

Cited by 5 | Viewed by 2064

Abstract

The Türkiye-Syria earthquake doublet of 6 February 2023 (Mw 7.8 at 01:17 UTC and Mw 7.6 at 10:24 UTC) resulted in extensive damage and tens of thousands of casualties. We present the surface displacements of the two earthquakes from synthetic aperture radar (SAR) offset tracking measurements. We extracted the geometric parameters of the rupture faults from the surface displacements and early aftershock distribution, based on which we inverted the coseismic slip distributions. We then calculated Coulomb stress to investigate the triggering relationship between the earthquakes and stress transfer to neighbouring faults and regions. The coseismic ruptures of the earthquake doublet were predominantly left-lateral strike-slip motions distributed between 0 and 15 km depth. The maximum fault slip reached > 8 m (Mw 7.8) and almost 10 m (Mw 7.6). The coseismic deformation and fault slip motion are consistent with the overall westward extrusion of the Anatolian Plate relative to the Eurasian and Arabian plates. The Mw 7.8 earthquake increased Coulomb failure stress at the hypocenter of the Mw 7.6 earthquake, implying that the Mw 7.8 event had a strong positive causative effect. Moreover, coseismic stress perturbations revealed a positive Coulomb stress effect on the middle Puturge Fault, northern Dead Sea Fault Zone (DSFZ), Yesemek Fault, Antakya Fault, and Turkoglu Fault, indicating an increasing seismic hazard in these regions. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations II)

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20 pages, 14259 KiB

Open AccessArticle

Study of the Interseismic Deformation and Locking Depth along the Xidatan–Dongdatan Segment of the East Kunlun Fault Zone, Northeast Qinghai–Tibet Plateau, Based on Sentinel-1 Interferometry

by Shuai Kang, Lingyun Ji, Liangyu Zhu, Chuanjin Liu, Wenting Zhang, Ning Li, Jing Xu and Fengyun Jiang

Remote Sens. 2023, 15(19), 4666; https://doi.org/10.3390/rs15194666 - 23 Sep 2023

Cited by 2 | Viewed by 1370

Abstract

The East Kunlun fault zone (EKFZ), located northeast of the Qinghai–Tibet Plateau, has experienced several strong earthquakes of magnitude seven or above since 1900. It is one of the most active fault systems and is characterized by left-lateral strike-slip. However, the Xidatan–Dongdatan segment (XDS) of the East Kunlun fault zone (EKFZ) has had no earthquakes for many years, and the Kunlun Mountains M_S 8.1 earthquake has a stress loading effect on this segment, so it is widely regarded as a high-risk earthquake gap. To this end, we collected the Sentinel-1 data of the XDS of the EKFZ from July 2014 to July 2019 and obtained the high-precision interseismic deformation field by the Interferometric Synthetic Aperture Radar (InSAR) technique to obtain the slip rate and locking depth of the XDS of the EKFZ, and the seismic potential of the segment was analyzed. The results are as follows: (1) The LOS deformation field of the XDS of the EKFZ was obtained using Sentinel-1 data of ascending and descending orbits, which indicated that the XDS of the EKFZ is dominated by horizontal motion. Combined with the interference results, it is shown that the strike-slip rate dominates the deformation information of the XDS of the EKFZ. The deep strike-slip rate of the fault is about 6 mm/yr, the deep dip-slip rate is about 2 mm/yr, and the slip-deficit rate on the fault surface is about 6 mm/yr; (2) Combined with the spiral dislocation theory model, the slip rate of the XDS to Xiugou Basin of the EKFZ has a gradually increasing trend, with an average slip rate of 9.6 ± 2.3 mm/yr and a locking depth of 29 ± 5 m; (3) The stress accumulation is about 483 ± 92 years in the XDS of the EKFZ, indicating that the cumulative elastic strain energy of the XDS can produce an M_W 7.29 ± 0.1 earthquake in the future. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations II)

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22 pages, 15984 KiB

Open AccessArticle

Coupling the Relationship between Land Subsidence and Groundwater Level, Ground Fissures in Xi’an City Using Multi-Orbit and Multi-Temporal InSAR

by Xing Zhang, Zhengfeng Cheng, Bei Xu, Rong Gui, Jun Hu, Changjiang Yang, Qiuhong Yang and Tao Xiong

Remote Sens. 2023, 15(14), 3567; https://doi.org/10.3390/rs15143567 - 16 Jul 2023

Cited by 4 | Viewed by 1663

Abstract

The Xi’an region of China has been suffering from groundwater depletion, ground fissure hazards, and surface subsidence for a long time. Due to the complex tectonics and frequent human and natural activities, land deformation in the region is aggravated, posing a threat to infrastructure and human life. This study adopted the multi-orbit and multi-temporal InSAR technology to measure multi-dimensional displacements and time-series displacements in Xi’an City. Through the multi-dimensional deformation verification, it was found that the control of groundwater flow direction by ground fissures is the cause of horizontal deformation. On the contrary, the flow direction of groundwater from west to east was inferred using multi-dimensional deformation. Further analysis was performed by calculating the deformation gradient of the cumulative deformation to obtain differential land subsidence and angular distortions, and it was quantitatively determined that the threshold for the generation of ground fissures caused by differential subsidence is 1/500. Then, through the mutual verification of the time series data and the groundwater level, a positive correlation was obtained. However, due to the inconsistent geological conditions and soil layers at the monitoring positions of Well 2 and Well 3, the lag time was 64 days and 4 days, respectively. Finally, the relationship between the surface deformation and the groundwater in the sustained uplift areas was explored. The Well 1 groundwater-level data with a monitoring period of 22 years and the corresponding monitoring points’ time series data were modeled; it was concluded that, in the future, the groundwater level will continue to rise and surface deformation will mainly increase, without a slowing trend. Therefore, research on the impact of surface uplift on infrastructure should be strengthened. By quantifying the relationship between land subsidence, ground fissures, and the groundwater level in Xi’an, the results of this study provide a reference for groundwater monitoring and management. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations II)

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18 pages, 34940 KiB

Open AccessArticle

Deformation Evaluation of the South-to-North Water Diversion Project (SNWDP) Central Route over Handan in Hebei, China, Based on Sentinel-1A, Radarsat-2, and TerraSAR-X Datasets

by Siting Xiong, Zhichao Deng, Bochen Zhang, Chisheng Wang, Xiaoqiong Qin and Qingquan Li

Remote Sens. 2023, 15(14), 3516; https://doi.org/10.3390/rs15143516 - 12 Jul 2023

Cited by 2 | Viewed by 1599

Abstract

The South-to-North Water Diversion Project (SNWDP) is a megaproject which has been constructed to alleviate imbalanced water resource distribution between northern and southern China. It encompasses three routes distributed in the east, central, and west of China, respectively. The central route (CR) of the SNWDP starts from the Danjiangkou Reservoir and ends in Beijing and Tianjin, running through Hubei, Henan, and Hebei Provinces; it has been in service since December 2014. For this type of megaproject, efficient and effective safety monitoring during its operation is highly challenging to the management department. Multitemporal interferometric synthetic aperture radar (MT-InSAR) has been widely applied in monitoring land deformation, especially in a wide area. However, its ability to show the deformation of one specific facility along the SNWD has not been deeply investigated. This study investigates the capability of MT-InSAR in monitoring the deformation of the canal and ancillary facilities along the SNWD-CR over Handan, Hebei Province, in China, using Sentinel-1, Radarsat-2, and TerraSAR-X datasets. Deformation rates from March 2015 to March 2016 are obtained by applying permanent scatterers (PS)-InSAR to these three SAR datasets. After combining the deformation rates derived by the three datasets, deformation along the SNWDP-CR is evaluated using a method encompassing median absolute deviation (MAD) calculation and heatmap. The evaluation result reveals that one part of the western embankment of the open canal is subsiding at up to 10 mm/year, which may be associated with overirrigation. Besides this location, the most dangerous areas assessed by the proposed method are related to ancillary facilities, mainly aqueducts and crossing-canal bridges. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations II)

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20 pages, 5312 KiB

Open AccessArticle

Evaluation of Post-Tunneling Aging Buildings Using the InSAR Nonuniform Settlement Index

by Yuzhou Liu, Wenxi Cao, Zhongqi Shi, Qingrui Yue, Tiandong Chen, Lu Tian, Rumian Zhong and Yuke Liu

Remote Sens. 2023, 15(14), 3467; https://doi.org/10.3390/rs15143467 - 9 Jul 2023

Cited by 3 | Viewed by 3202

Abstract

Tunneling work, including the construction of municipal tunnels and metro lines, may disturb the structural health of aging buildings in densely built urban areas. Deformation monitoring and risk assessments of aging buildings are crucial to mitigate incidents and prevent losses of people’s lives and properties. Time-series InSAR reveals spatio-temporal information about observed targets by extracting persistent scatterers of the structures, which can achieve the wide-range monitoring of buildings and infrastructure. However, solely relying on InSAR-derived general parameters (deformation rates and time series of specific points) cannot objectively assess the safety conditions of buildings. To address this issue, this study proposes an InSAR Nonuniform Settlement Index. First, the point targets of buildings are extracted through time-series InSAR processing. Then, using the points as inputs, the Nonuniform Settlement Index calculates the 3D settlement plane and the inclination angle of the plane corresponding to each building. In this way, the proposed Nonuniform Settlement Index acts as a subsequent analysis method of time-series InSAR to characterize the safety statuses of buildings. In our study, 147 scenes of COSMO-SkyMed images from 2013 to 2022 were used to inverse the nine-year deformation evolution of the tested area. After time-series InSAR processing and index analysis based on the above SAR datasets, cross-validation was implemented with static-level and manual investigation data. The approach was to use one aging, collapsed building affected by tunneling work, as well as the eight adjacent aging buildings. The results showed high consistency with the in situ data, which proves the efficiency of the proposed approach. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations II)

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21 pages, 10808 KiB

Open AccessArticle

Spatial Distribution Analysis of Landslide Deformations and Land-Use Changes in the Three Gorges Reservoir Area by Using Interferometric and Polarimetric SAR

by Jun Hu, Yana Yu, Rong Gui, Wanji Zheng and Aoqing Guo

Remote Sens. 2023, 15(9), 2302; https://doi.org/10.3390/rs15092302 - 27 Apr 2023

Cited by 3 | Viewed by 2189

Abstract

Landslides are geological events that frequently cause major disasters. Research on landslides is essential, but current studies mostly use historical landslide data and do not reflect dynamic, real-time research results. In this study, landslide deformations and land-use changes were used to analyze the landslide distribution in Fengjie County and Wushan County in the Three Gorges Reservoir Area (TGRA) by using interferometric and polarimetric SAR. In this study, the mean annual rate of landslide deformations was obtained using the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) for the ALOS-2 (2014–2019) data. Land-use changes were based on the 2007 and 2017 land-use results from dual-polarization ALOS-1 and ALOS-2 data, respectively. To address the problem of classification accuracy reduction caused by geometric distortion in mountainous areas, we first used texture maps and pseudocolor maps synthesized with dual-polarization intensity maps to perform classification with random forest (RF), and then we used coherence and slope maps to run the K-Means algorithm (KMA). We named this the secondary classification method. It is an improvement on the single classification method, exhibiting a 94% classification accuracy, especially in rugged areas. Combined with land-use changes, GIS spatial analysis was used to analyze the spatial distribution of landslides, and it was found that the landslide rate was significantly correlated with the type after change, with a correlation coefficient of 0.7. In addition, land-use types associated with human activities, such as cultivated vegetation, were more likely to cause landslide deformation, which can be used to guide local land-use planning. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations II)

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18 pages, 10661 KiB

Open AccessArticle

Joint Estimation of Ground Displacement and Atmospheric Model Parameters in Ground-Based Radar

by Yan Zhu, Bing Xu, Zhiwei Li, Jie Li, Jingxin Hou and Wenxiang Mao

Remote Sens. 2023, 15(7), 1765; https://doi.org/10.3390/rs15071765 - 25 Mar 2023

Cited by 2 | Viewed by 1337

Abstract

Atmospheric delay is the primary error in ground-based synthetic aperture radar (GBSAR). The existing compensation methods include the external meteorological data correction method, the polynomial fitting method, and the persistent scatterers SAR interferometry (PSInSAR) calibration method. Combining the polynomial fitting and the persistent scatterers targets is the most popular method of GBSAR atmospheric delay compensation. However, the displacement component of the coherent target is always ignored in the atmospheric delay compensation, which is unpractical. A joint estimation method of ground displacement and atmospheric model parameters is developed in this paper. The displacement component is determined by the spatial and temporal features of the objects. The atmospheric delay component is regarded as a systematic error represented by a quadratic polynomial related to distance. The result is resolved by the least-square method. Compared to the existing method, the root-mean-square error (RMSE) of the proposed method had a significant improvement in the validation experiment. In the real in situ experiment, the time series obtained by the GBSAR had a similar trend to that acquired by the Global Positioning System (GPS) receiver. It is indicated that the proposed method can lead to a better deformation estimation by taking the deformation component into account in the atmospheric compensation. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations II)

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22 pages, 21321 KiB

Open AccessArticle

Ground Deformation Monitoring over Xinjiang Coal Fire Area by an Adaptive ERA5-Corrected Stacking-InSAR Method

by Yuxuan Zhang, Yunjia Wang, Wenqi Huo, Feng Zhao, Zhongbo Hu, Teng Wang, Rui Song, Jinglong Liu, Leixin Zhang, José Fernández, Joaquin Escayo, Fei Cao and Jun Yan

Remote Sens. 2023, 15(5), 1444; https://doi.org/10.3390/rs15051444 - 4 Mar 2023

Cited by 3 | Viewed by 1989

Abstract

Underground coal fire is a global geological disaster that causes the loss of resources as well as environmental pollution. Xinjiang, China, is one of the regions suffering from serious underground coal fires. The accurate monitoring of underground coal fires is critical for management and extinguishment, and many remote sensing-based approaches have been developed for monitoring over large areas. Among them, the multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques have been recently employed for underground coal fires-related ground deformation monitoring. However, MT-InSAR involves a relatively high computational cost, especially when the monitoring area is large. We propose to use a more cost-efficient Stacking-InSAR technique to monitor ground deformation over underground coal fire areas in this study. Considering the effects of atmosphere on Stacking-InSAR, an ERA5 data-based estimation model is employed to mitigate the atmospheric phase of interferograms before stacking. Thus, an adaptive ERA5-Corrected Stacking-InSAR method is proposed in this study, and it is tested over the Fukang coal fire area in Xinjiang, China. Based on original and corrected interferograms, four groups of ground deformation results were obtained, and the possible coal fire areas were identified. In this paper, the ERA5 atmospheric delay products based on the estimation model along the LOS direction (D-LOS) effectively mitigate the atmospheric phase. The accuracy of ground deformation monitoring over a coal fire area has been improved by the proposed method choosing interferograms adaptively for stacking. The proposed Adaptive ERA5-Corrected Stacking-InSAR method can be used for efficient ground deformation monitoring over large coal fire areas. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations II)

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18 pages, 6858 KiB

Open AccessArticle

Coseismic Rupture Behaviors of the January and March 2022 M_W > 5.5 Hala Lake Earthquakes, NE Tibet, Constrained by InSAR Observations

by Jiuyuan Yang, Caijun Xu and Yangmao Wen

Remote Sens. 2023, 15(4), 1124; https://doi.org/10.3390/rs15041124 - 18 Feb 2023

Viewed by 1640

Abstract

On 23 January and 25 March 2022, two M_W > 5.5 Hala Lake earthquakes characterized by right-lateral strike-slip faulting occurred around the Elashan Fault in Northeastern Tibet, marking the two largest events since the 1927 M_W 6.2 Hala Lake earthquake. Since no surface rupture related to the two earthquakes has been reported, the seismogenic faults and coseismic rupture behaviors of the two events are still unknown. The occurrence of the two events provides a rare opportunity to gain insight into the seismogenic structure and rupture behavior of the less studied region, further helping us accurately evaluate the regional seismic hazard. Here, we first exploit Interferometric synthetic aperture radar (InSAR) data to obtain the coseismic deformation associated with the two earthquakes and then invert for the fault geometry and detailed coseismic slip of the two events. Coseismic modeling reveals that the January and March 2022 earthquakes ruptured two buried west-dipping moderate-angle and high-angle right-lateral strike-slip faults, respectively. Most of the slip of the January event occurred at depths from 1.7–7.6 km, while the majority of the slip associated with the March event occurred at depths from 2.5–10 km, which may have been restricted by the intersections between the January and March Hala Lake seismogenic faults. By a comprehensive analysis of the coseismic inversions, stress changes, and early postseismic signal, we suggest that the significant fault dip difference (~30°), highlighting a fault segmentation, stops the rupture propagation from one fault segment to another and that fluid migration may encourage the restart of the rupture of the later event, which requires further investigation. Moreover, Coulomb stress modeling shows stress loading on the eastern segment of the Daxueshan–Shule Fault and the northern segment of the Elashan fault, which we should pay more attention to. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations II)

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19 pages, 8641 KiB

Open AccessArticle

A Modification to Phase Estimation for Distributed Scatterers in InSAR Data Stacks

by Changjun Zhao, Yunyun Dong, Wenhao Wu, Bangsen Tian, Jianmin Zhou, Ping Zhang, Shuo Gao, Yuechi Yu and Lei Huang

Remote Sens. 2023, 15(3), 613; https://doi.org/10.3390/rs15030613 - 20 Jan 2023

Cited by 4 | Viewed by 1887

Abstract

To improve the spatial density and quality of measurement points in multitemporal interferometric synthetic aperture radar, distributed scatterers (DSs) should be processed. An essential procedure in DS interferometry is phase estimation, which reconstructs a consistent phase series from all available interferograms. Influenced by the well-known suboptimality of coherence estimation, the performance of the state-of-the-art phase estimation algorithms is severely degraded. Previous research has addressed this problem by introducing the coherence bias correction technique. However, the precision of phase estimation is still insufficient because of the limited correction capabilities. In this paper, a modified phase estimation approach is proposed. Particularly, by incorporating the information on both interferometric coherence and the number of looks, a significant bias correction to each element of the coherence magnitude matrix is achieved. The bias-corrected coherence matrix is combined with advanced statistically homogeneous pixel selection and time series phase optimization algorithms to obtain the optimal phase series. Both the simulated and Sentinel-1 real data sets are used to demonstrate the superiority of this proposed approach over the traditional phase estimation algorithms. Specifically, the coherence bias can be corrected with considerable accuracy by the proposed scheme. The mean bias of coherence magnitude is reduced by more than 29%, and the standard deviation is reduced by more than 18% over the existing bias correction method. The proposed approach achieves higher accuracy than the current methods over the reconstructed phase series, including smoother interferometric phases and fewer outliers. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations II)

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