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Interferograms for intraplate earthquakes with large deformation. Each color cycle represents 12 cm of LOS displacement. Stars and circles denote the location of the epicenter from USGS and the centroid from GCMT, respectively. Black L-shaped arrows indicate the azimuth (long) and range (short) directions. Beach balls denote the focal mechanism of the GCMT solution. (a) 2014 M w 6.2 Japan (No. 3). (b), (c) 2015 M w 6.5 East Timor (No. 9). (d), (e) 2015 M w 7.2 Tajikistan (No. 11). (f), (g) 2016 M w 7.0 Japan (No. 14). (h) 2016 M w 6.0 Australia (No. 18). (i), (j) 2016 M w 6.6 Italy (No. 25). (k), (l) 2016 M w 7.8 New Zealand (No. 26).
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Many studies have used Advanced Land Observing Satellite 2 (ALOS-2) synthetic aperture radar (SAR) interferograms to make remarkable advances toward understanding and assessing seismic hazards. Next-generation satellites will make abundant L-band SAR data available in the near future, enabling even more progress in earthquake research and disaster...
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... Intraplate Earthquakes With Large Deformation: The in-201 terferograms showed that seven large intraplate earthquakes gen-202 erated dense fringes and discontinuities along the main causative 203 fault (see Fig. 3), suggesting that a large fault slip occurred at a 204 very shallow part and reached the ground surface. Most of the 205 fringe patterns are so complex that a simple fault geometry can-206 not explain them, and the dense and detailed displacement data 207 provided by InSAR aid considerably in detangling the complex-208 ity (e.g., [17]- ...
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... of the interferograms contain decorrelated areas along 210 the causative fault because of the extremely large gradient of the 211 LOS displacement required to retain coherence [e.g., Fig. 3(f), 212 (g), (k), and (l)]. In such cases, instead of interferometry, a 213 pixel-offset method that exploits the amplitude of SAR images 214 is appropriate for retrieving large displacements, despite this 215 method's lower spatial resolution and precision (e.g., [9], [20], 216 ...
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... Intraplate Earthquakes With Moderate Deformation: 223 Fig. 4 shows interferograms with moderate deformation for 11 224 seismic events. Although the amplitude of these deformations 225 was much smaller than those in Fig. 3, considering the spatial 226 scale and shape of the fringes, the interferograms appear to rep-227 resent coseismic deformations rather than noises. In Fig. 4(e), 228 (f), (q), and (r), the actual surface displacement under the sea 229 may be larger than that detected on land, although the former 230 cannot be observed by InSAR. With ...
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... Nev ertheless, w e w ere still able to observe a clear coseismic deformation signal in the Sentinel-1 interferograms. Compared to C-band InSAR, the ALOS-2 interferograms showed e xcellent coherence, ev en in heavily v e getated areas (Funning & Garcia 2019 ;Morishita 2019 ). Thus, for this study, we collected ascending track 124 and descending track 22 ALOS-2 data, in addition to the two ascending Sentinel-1 images, to map the coseismic surface displacement of the Alor earthquake. ...
... The location (longitude and latitude) of the uniform slip model derived in this study represents the midpoint of the upper boundary of the seismogenic fault. (Funning & Garcia 2019 ;Morishita 2019 ). A detailed description of InSAR coseismic deformation can be found in Supplementary Text S2. ...
On 4 November 2015, an Mw 6.5 earthquake struck the east region of Alor Island, eastern Indonesia. Here, we use Sentinel-1 and ALOS-2 data to explore the coseismic surface displacement of this earthquake. Based on the ALOS-2 coseismic interferograms, the first fault model and coseismic slip distribution of the 2015 Alor earthquake are presented in this study. The preferred slip model links to a blind south-southeast striking, south-southwest dipping strike-slip fault with amount of normal slip component and a peak slip of 2.09 m at 2.34 km of depth. Considering the fact that the ascending and descending InSAR prediction of the distributed slip model does not fit the InSAR observations at the northwest and southeast tips with the simple planar fault model. We tried to construct a strike-variable fault model to further improve data fit. The results of the calculated Coulomb stress change imply that the regions with positive CFS changes mainly located at the northwest and southeast extremities of the rupture of the Alor earthquake, and in the lobes north and south of the rupture The most striking discovery from the InSAR observations of the Alor earthquake is that most of the displacements occurred on a fault whose existence was unknown before the earthquake.
... With the process of Synthetic Aperture Radar (SAR) satellite missions, Interferometric SAR (InSAR) has become an established tool for measuring the Earth's surface deformation caused by earthquakes, considerably boosting our capacity to detect active tectonic processes (Massonnet et al., 1993;Peltzer and Rosen, 1995;Salvi et al., 2012). InSAR, in addition to seismology, provides independent measurements of fault position, depth, and orientation (Zebker et al., 1997;Pedersen et al., 2003;Lohman and Simons, 2005;Agram and Simons, 2015;Funning and Garcia, 2019;Morishita, 2019). The InSAR gives geographical coverage, but the data is in the line-of-sight (LOS) direction, necessitating extra multi-geometrical analysis to determine the real ground motion components. ...
... GNSS surveys and InSAR images can be used in conjunction to estimate 3D surface deformation over a target region. With both synthetic and actual data, both strategies have been evaluated and validated (Massonnet et al., 1993;Peltzer and Rosen, 1995;Pedersen et al., 2003;Chen and Gan, 2010;Lagios et al., 2012;Salvi et al., 2012;Shan et al., 2014;Funning and Garcia, 2019;Morishita, 2019). Lekkas et al. (2020) 2021), focused on the Mw 6.9 Samos Island earthquake on October 30, 2020, and proposed that the earthquake originated on two segments of a north-dipping listric fault with a strong dip-slip component and a small lateral component. ...
Izmir, which is one of the biggest cities of Turkey and has the extensive tectonic features of the Western Anatolia region, has been struck in recent years due to its high seismic activity. In particular, the south of Izmir is one of the regions that has high seismic activity in the city, which is constrained by major fault zones. The earthquake of magnitude of a Mw 6.9 occurred 8 km north of Samos Island at a depth of 16 km on 30.10.2020, at 11:51:24 UTC (14:51:24 Local Time (LT)). It occurred on a 40-kilometer-long north-dipping normal fault zone in the Mediterranean between Greece’s Samos Island and Turkey’s Kuşadası Bay. Following the mainschock, a tsunami with a height of more than 1 meter occurred at Sığacık Bay, south of Izmir, and on the north side of Samos Island. This article focuses on the investigation of the Samos earthquake by utilizing both GNSS data and InSAR images, and the obtained results are given in this paper. GNSS data were processed by using CSRS-PPP Software as static and kinematic modes. After processing the GNSS data, the maximum displacements were observed at CESME and IZMIR CORS-TR points located in the north of the fault. Horizontal movements of 12 cm and 6 cm towards the north were obtained at CESME and IZMIR points, respectively. However, the amount of horizontal movements was less at DIDIM and AYDIN CORS-TR locations, which are located to the south of the fault. In addition to GNSS data, ESA Sentinel-1 SAR data was used in the InSAR procedure, and the displacements were clarified using the unwrapped interferogram. The interferogram revealed a 10 cm uplift in the west of the Island of Samos and a 10 cm subsidence in the Izmir region, on the north side of the fault, based on the InSAR data. The most striking feature of this study is that the earthquake that occurred near the island of Samos was reported by Gansas’ study that the 3 GNSS points (SAMO, SAMU, and 093A) on the island of Samos are moving in a south direction and the largest displacement is about 36 centimetres south. However, in our study, the north direction is more prominent as the direction of movement at IZMIR and CESME points. The movement at the DIDIM point supports his work. In other words, the Samos Fault affected the points located in the north and south differently.
... round deformation is the most direct apparent phenomenon of earthquake occurrence, and it is essential data for inversion of earthquake damage, epicenter mechanism, fault structure, etc. [1,2]. In recent years, Differential Interferometric Synthetic Aperture Radar (DInSAR) has been widely used in the study of earthquakes [3]. ...
Manual analysis of LiCSAR deformation data in tectonic zones and timely detection of pre-earthquake anomalous activity is very time-consuming. In order to solve this problem, a LiCSAR-based anomaly detector of seismic deformation in InSAR (LADSDIn) is constructed in this paper. LADSDIn can automatically detect and extract anomalous activity and seismic deformation in tectonic zones. LADSDIn is modeled by learning the spatiotemporal characteristics of MTInSAR time series deformation data to detect abnormal deformation. The detector considers transients that deviate from the “predicted” deformation are considered “anomalous”. For earthquake-prone regions, “anomalies” with outlier characteristics in spatial and temporal properties are usually the deformations caused by seismic activities. We successfully applied LADSDIn to January 8, 2022, Menyuan Mw 6.7 earthquake in China, and LADSDIn successfully detected the extent of ground deformation induced by this seismic activity. The results show that the deformation range of the ascending track is -350 ∼ 87 mm, and the deformation range of the descending track is -127 ∼ 132 mm. And the detector successfully detected the “anomalous deformation” signs before the earthquake (November 2021). In addition, LADSDIn supports parallel processing in chunks to reduce computation time. The characteristics of LADSDIn facilitate cluster deployment and use for automatic detection and extraction of seismic deformation in global tectonic zones. This work provides theoretical support for the automation and refinement study of global seismic activity.
... However, compared with strong earthquakes (6:0 < M w < 6:9), shallow moderate earthquakes (5:0 < M w < 5:9) have smaller deformation signals in the interferogram. The InSAR coseismic displacement fields are usually contaminated by atmospheric noise (Elliott et al., 2016;Pepe and Calò, 2017;Funning and Garcia, 2019;Morishita, 2019). Generally, the error level in the InSAR signal has a significant impact on the accuracy of the fault model and slip distribution obtained in the displacement inversion. ...
On 24 September 2019, an Mw 5.8 earthquake occurred on the Mangla-Samwal anticline near Mirpur city, Pakistan. Because the seismogenic fault is hidden and the near-field seismic data are scarce, the magnitude and slip distribution of this earthquake are not determined. Furthermore, due to small deformation and significant atmospheric noise in the coseismic interferograms, it is difficult to accurately determine source parameters and slip distribution using the original single ascending and descending Interferometric Synthetic Aperture Radar observations. In this article, we used Sentinel-1A satellite Synthetic Aperture Radar data to generate 60 ascending and 56 descending coseismic interferograms and performed atmospheric error correction including Kriging interpolation correction and displacement stacking to obtain more accurate coseismic displacement fields for the 2019 Mw 5.8 Mirpur earthquake. Considering the local geological structures, focal mechanism solutions, and the optimal fault parameters obtained from the coseismic displacement inversion, we determine that the strike and dip of the fault of the 2019 Mirpur earthquake are 296.3° and 4.0°, respectively. Based on this fault model, the fault plane was extended to 12.0 km long and 11.0 km wide and divided into subfaults of 1.0×1.0 km2. We inverted the coseismic displacement fields to obtain slip distribution on the fault plane. Slip is mainly distributed at a depth of 4.7 ∼ 5.0 km, with a maximum of 0.95 m at a depth of 4.88 km. The slip distribution shows that this earthquake was a thrust event with right-lateral strike-slip components, which is consistent with the focal mechanism solution from the U.S. Geological Survey. The estimated geodetic moment is about 7.14×1017 N·m, equivalent to Mw 5.8.
... However, InSAR-only approaches cannot measure large deformations (specifically in areas with large deformation gradients) because of decorrelation in interferograms. There have also been few opportunities for the further application of this approach because it requires left-looking acquisitions, which are only available in a very limited number of situations (Morishita 2019). ...
... The largest displacement observed by the GNSS CORS Page 7 of 19 Morishita and Kobayashi Earth, Planets and Space (2022) 74:16 network for this event was approximately 7 cm at ~ 13 km north of the epicenter. As Fig. 2 shows, both regions are covered with dense vegetation; therefore, C-band SAR data tend to be decorrelated, while the L-band provides sufficient coherence (Jiang et al. 2017;Funning and Garcia 2018;Amey et al. 2019;Morishita 2019;He et al. 2019b). For both earthquake events, abundant pre-and post-earthquake ALOS-2 data are available including left-looking and right-looking types. ...
... Although ~ 10 cm post-seismic deformation in Kumamoto has been reported in previous studies (Fujiwara et al. 2016; Himematsu and Furuya 2020; Hashimoto 2020; Morishita 2021a), the deformed area was mostly limited where large coseismic deformation occurred and, therefore, the impact of the post-seismic deformation is relatively small. All three methods (i.e., InSAR, SBI, and pixel offset) were applied to each data pair and processed using GSISAR software (Tobita 2003;Morishita et al. 2018;Morishita 2019Morishita , 2021b. The 10 m mesh digital elevation model (DEM) prepared by the Geospatial Information Authority of Japan (GSI) was used to remove topographic phases in the InSAR. ...
Three-dimensional (3D) surface deformation data with high accuracy and resolution can help reveal the complex mechanisms and sources of subsurface deformation, both tectonic and anthropogenic. Detailed 3D deformation data are also beneficial for maintaining the position coordinates of existing ground features, which is critical for developing and advancing global positioning technologies and their applications. In seismically active regions, large earthquakes have repeatedly caused significant ground deformation and widespread damage to human society. However, the delay in updating position coordinates following deformation can hamper disaster recovery. Synthetic aperture radar (SAR) data allow high-accuracy and high-resolution 3D deformation measurements. Three analysis methods are currently available to measure 1D or 2D deformation: SAR interferometry (InSAR), split-bandwidth interferometry (SBI), and the pixel offset method. In this paper, we propose an approach to derive 3D deformation by integrating deformation data from the three methods. The theoretical uncertainty of the derived 3D deformations was also estimated using observed deformation data for each of these methods and the weighted least square (WLS) approach. Furthermore, we describe two case studies (the 2016 Kumamoto earthquake sequence and the 2016 Central Tottori earthquake in Japan) using L-band Advanced Land Observing Satellite 2 (ALOS-2) data. The case studies demonstrate that the proposed approach successfully retrieved 3D coseismic deformation with the standard error of ~ 1, ~ 4, and ~ 1 cm in the east–west, north–south, and vertical components, respectively, with sufficient InSAR data. SBI and the pixel offset method filled the gaps of the InSAR data in large deformation areas in the order of 10 cm accuracy. The derived standard errors for each pixel are also useful for subsequent applications, such as updating position coordinates and deformation source modeling. The proposed approach is also applicable to other SAR datasets. In particular, next-generation L-band SAR satellites, such as ALOS-4 and NASA-ISRO SAR (NISAR), which have a wider swath width, more frequent observation capabilities than the former L-band satellites, and exclusive main look directions (i.e., right and left) will greatly enhance the applicability of 3D deformation derivation and support the quick recovery from disasters with significant deformation.
... In this section, we describe an example of the implementation for correcting ionospheric azimuth offset. In this study, we used GSISAR software [22]- [25] for interferometric processing including the split-spectrum method, and GAMMA-SAR software [26] to generate pixel-offset imagery. The processing flowchart is presented in Fig. 1, and the detail of the processing is described below. ...
... One option for improving the accuracy in an extensive decorrelation area would be through the application of GNSS CORS data in the area to the correction, which is left as a further investigation. The other drawback is the potential degradation of the estimation accuracy if using lower resolution modes [i.e., SM2, SM3, and wide area observation mode (WD)] of ALOS-2/PALSAR-2 image, since the measurement accuracy of ionospheric phase delay based on the split-spectrum method is inversely proportional to bandwidth [20], [25]. The bandwidth of SM1 is 84 MHz, those of SM2 and SM3 are 42 and 28 MHz, respectively, and that of WD is 14 or 28 MHz. ...
... And note that the sign of right-hand side of (25) is different from the original equation in [12] because the differential ionospheric phase delay in [12] is defined to have the opposite sign to that in [16]. Combining (24) and (25) to eliminate φ MAI , we obtain ...
The pixel-offset method has been utilized as a powerful tool to measure large ground movements. However, L-band spaceborne synthetic aperture radar (SAR) data are often affected by the ionosphere, which produces serious noises in the azimuth component of the pixel offset field, called as azimuth streaks. Here, we propose a new method to mitigate azimuth streaks based on physical modeling. Azimuth streaks cannot be removed by simply combining the known relationship between ionospheric azimuth offset and the ionospheric phase delay with the phase delay obtained by the split-spectrum method. Thus, taking into account that image matching (coregistration) affects the measurement of azimuth offsets, we formulate a theoretical correction formula of azimuth streaks by subtracting the coregistration-induced effects approximated by a polynomial function from ionospheric azimuth offsets modeled using the split-spectrum method. Applying the method to two pairs of Advanced Land Observing Satellite-2 (ALOS-2)/Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) stripmap images which are severely affected by the ionosphere, we demonstrate effective mitigation of azimuth streaks. In the application to the case that no significant ground movement is detected by Global Navigation Satellite System (GNSS), while the standard deviation of azimuth pixel offset before the correction is 87.2 cm, the value after the correction is 29.2 cm, which is comparable to the theoretical measurement accuracy of the azimuth pixel offset. In the application to the 2016 Kumamoto earthquake, we substantially reduce the azimuth streaks and successfully extract the ground movements from the azimuth offset fields within an accuracy of about 20 cm. The result suggests the proposed method enables more accurate and operational estimation of the 3-D ground displacement.
... Phase unwrapping is an integral part of multiple algorithms with applications such as fingerprint re-construction [1], synthetic aperture radar (SAR) interferograms [2], deformation estimation [3], susceptibility field mapping [4], optical meteorology [5], 3D shape reconstruction [6], digital holography [7], Doppler OCT [8], imaging [9], and 3D scanning [10]. Accurate phase unwrapping is also a fundamental requirement for high-accuracy metric sensing using self-mixing interferometry (SMI) or optical feedback interferometry [11]. ...
Phase unwrapping is an integral part of multiple algorithms with diverse applications. Detailed phase unwrapping is also necessary for achieving high-accuracy metric sensing using laser feedback-based self-mixing interferometry (SMI). Among SMI specific phase unwrapping approaches, a technique called Improved Phase Unwrapping Method (IPUM) provides the highest accuracy. However, due to its complex, sequential, and compute-intensive nature, this method requires a high-performance computing architecture, capable of scalable parallel processing so that such a high-accuracy algorithm can be used for high-bandwidth sensing applications. In this work, the existing sequential IPUM C program is parallelized by using hybrid OpenMP/MPI (Open Multi-Processing/Message Passing Interface) parallel programming models and tested on Barcelona Supercomputing Center Nord-III Supercomputer. The computational performance of the proposed parallel-hybrid IPUM algorithm is compared with existing IPUM sequential code by executing multi-core and uni-core processor architecture, respectively. While comparing the performance of sequential IPUM with the parallel-hybrid IPUM algorithm on 16 nodes of Nord-III supercomputer, the results show that the parallel-hybrid algorithm gets 345.9x times performance improvement as compared to IPUM’s standard, sequential implementation on a single node system. The results show that the parallel-hybrid version of IPUM gives a scalable performance for different target velocities and a different number of processing cores.
... The L-band InSAR is one of the best tools for the detection of details concerning the crustal deformation caused by earthquakes. The improvement in performance of the ALOS-2 satellite and other short-term intensive observations has revealed the occurrence of several phenomena, especially during the 2016 Kumamoto earthquake sequence (Fujiwara et al. 2016;2017a;Morishita 2019). This study reviews these past cases of DL detection; in addition, new analyses have been performed. ...
... Figure 13 depicts DLs around Suizenji Park along with a high-pass filtered up-down displacement map (Fujiwara et al. 2016) obtained using three-dimensional (3D) InSAR Morishita 2019). Figure 14 depicts the surface strain (extension and contraction) and dilatation values calculated using a 3D deformation map for co-seismic displacement (Additional file 1: Fig. S2). ...
Abstract Interferograms pertaining to large earthquakes typically reveal the occurrence of elastic deformations caused by the earthquake along with several complex surface displacements. In this study, we identified displacement lineaments from interferograms; some of which occur on the shallow section of seismogenic faults. However, such displacements are typically located away from the hypocenter, and they are considered as triggered shallow slips. We found that the triggered shallow slips had a varied nature, as follows. (1) No evidence has yet been obtained regarding the generation of large seismic motion via triggered shallow slips; thus, their occurrence is seldom considered a cause of major earthquakes. However, we found that a movement of triggered shallow slip associated with an M 6-class earthquake occurred on an active fault that has previously caused an M 7-class earthquake. (2) At certain locations, several parallel displacement lineaments have been discovered. During the Kumamoto earthquake sequence in 2016, the strain created by the main shock and the motion of triggered shallow slips coincided at a specific location, resulting in the creation of parallel triggered shallow slips by the main shock. Conversely, at another location, the movements of the main shock and triggered shallow slips did not match, since the main shock was simply a trigger, whereas the latter parallel triggered shallow slips are likely a means for releasing previously accumulated strain. (3) The fault scaling law—which states that the length and displacement of a fault are proportional—does not hold true for triggered shallow slips. However, the parallel triggered shallow slips show a relationship between horizontal spacing and its displacement. This may be attributed to immobility in deep locations. These results lead to the following conclusions. Large earthquakes tend to trigger shallow slips on the pre-existing faults. Subsequently, these triggered shallow slips release accumulated strain by causing fault motions, which in turn result in displacement lineaments. The occurrence of such passive faulting creates weak, mobile fault planes that repeatedly move at the same location. These triggered shallow slips cause the diversity among active faults as a result.
Remote sensing geodetic observations (Interferometric Synthetic Aperture Radar [InSAR] and optical correlation [“pixel tracking”]) serve an increasingly diverse and important role in earthquake monitoring and response. This study introduces the Geodetic Centroid (gCent) catalog—an earthquake catalog derived solely from space-based geodetic observations—and analysis of 74 earthquakes (Mw 4.3–7.4) imaged from 1 August 2019 to 01 February 2022. For gCent, we use InSAR and optical correlation observations derived from the Sentinel-1 satellites and various publicly available optical satellites to systematically image all global earthquakes Mw 5.5 or larger and shallower than 25 km, Mw 7.0 or larger at any depth, and other high-impact earthquakes or seismic events of special interest. We invert surface displacements from successfully imaged earthquakes for the location, orientation, and dimensions of a single slipping fault patch that describes the centroid characteristics of the earthquake. These centroid models, in turn, are compiled into a catalog and used in U.S. Geological Survey/Advanced National Seismic System (ANSS) operational earthquake response products such as ShakeMaps and finite-fault models. We provide a comparison of the gCent catalog to the ANSS Comprehensive Catalog and Global Centroid Moment Tensor (Global CMT) catalog to compare reported locations, depths, and magnitudes. We find that global earthquake catalogs not only generally provide reasonably comparable locations (within 10 km on average), but also they systematically overestimate depth that may have implications for earthquake shaking predictions based solely on earthquake origin information. Geodetic magnitudes are comparable to seismically inferred magnitudes, indicating that gCent models are unlikely to be systematically biased by the presence of postseismic deformation. We additionally highlight limitations of the gCent catalog induced by both the limitations of remote sensing imaging of earthquakes and our imposition of a simplified earthquake source description that does not include spatially distributed slip.
Synthetic aperture radar (SAR) interferometry can measure ground surface deformation with high accuracy and spatial resolution, in the form of phase change in an interferogram. The phase is observed modulo 2 π (i.e., wrapped), and unwrapping is necessary to obtain the absolute amount of deformation. Although several advanced automatic unwrapping algorithms and approaches have been proposed, unwrapping errors can occur, especially in complicated phases. Manual adjustment of the integration path in the unwrapping may improve the unwrapping result. However, sometimes, it tends to be challenging even for an expert. In this report, I describe an effective unwrapping approach for complicated phases to obtain a reliable unwrapping result using multiple interferograms. A common integration path guide is created from geocoded interferograms and their phase noise coherence estimates, which reduces/eliminates the effort involved in manual adjustment and greatly reduces unwrapping errors. The remaining unwrapping errors were detected from residuals between the unwrapped phases of multiple interferograms and corrected based on isolated components. A case study was taken up in the northwest of the outer rim of the Aso caldera. Here, plenty of displacement lineaments were generated by the 2016 Kumamoto earthquake, resulting in severely complicated interferometric phases to correctly unwrap by any existing approaches. Therefore, the proposed approach effectively and efficiently retrieves reliable unwrapped phases and subsequent significant interpretations of the displacement lineaments. This effective unwrapping approach may reveal complicated deformations and unrecognized mechanisms in future earthquakes or other deformation-causing geophysical phenomena.
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