This study proposes a workflow that enables the accurate identification of earthquake-induced damage zones by using coherence image pairs of the Sentinel-1 satellite before and after an earthquake event. The workflow uses interferometric synthetic aperture radar (InSAR) processing to account for coherence variations between coseismic and preseismic image pairs. The coherence difference between two image pairs is useful information to detect specific disasters in a regional-scale area after an earthquake event. To remove background effects such as the atmospheric effect and ordinal surface changes, this study employs the two-step threshold method to develop the coseismic coherence difference (CCD) map for our analyses. Thirty-four Sentinel-1 images between January 2015 and February 2016 were collected to process 30 preseismic image pairs and two coseismic image pairs for assessing multiple types of disasters in Tainan City of southwestern Taiwan, where severe damages were observed after the Meinong earthquake event. The coseismic unwrapping phases were further calculated to estimate the surface displacement in east-west and vertical directions. Results in the CCD map agree well with the observations from post-earthquake field surveys. The workflow can accurately identify earthquake-induced land subsidence and surface displacements, even for areas with insufficient geological data or for areas that had been excluded from the liquefaction potential map. In addition, the CCD details the distribution of building damages and structure failures, which might be useful information for emergency actions applied to regional-scale problems. The conversion of 2D surface displacement reveals the complex behavior of geological activities during the earthquake. In the foothill area of Tainan City, the opposite surface displacements in local areas might be influenced by the axis activities of the Kuanmiao syncline.

We provide new data and insights into a 6 February 2018 $Mw$ 6.4 earthquake that shook the city of Hualien in eastern Taiwan at the leading edge of a modern arc–continent collision. Fatalities and damages were concentrated near the Milun fault and extended south to the northern Longitudinal Valley fault. Although the Hualien area has one of the highest rates of seismicity in Taiwan, the geologic structures responsible for active deformation were not well understood before this event. We analyzed Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System (GPS) data and produced a 3D displacement model with InSAR and azimuth offset of radar images to document surface deformation induced by this earthquake. The 3D displacement model was inverted to estimate slip on the Milun fault. We find that models assuming a single fault are inconsistent with observations of coseismic deformation and regional strain patterns, providing evidence for linked slip on a little‐studied offshore thrust belt. Based on data presented here and elsewhere, we propose a model for transpressive deformation in a zone of oblique convergence and left‐lateral wrench tectonics to explain this and a prior 1951 M 7.3 earthquake.

We use high‐resolution Pléiades optical satellite imagery to study the distribution and magnitude of fault slip along the Milun fault surface rupture, which broke during the 2018 Hualien earthquake (⁠$Mw$ 6.4) in eastern Taiwan. Correlation of pre‐ and postearthquake stereo Pléiades images reveals detailed 3D surface displacements along the 8‐km‐long Milun fault, with maximum $∼1m$ left‐lateral offsets across the fault. Along the northern section of the Milun fault, our correlation results indicate a localized deformation zone, with offset values slightly larger than the maximum offsets reported in the field (⁠$∼77cm$⁠). To the south, the left‐lateral offsets become increasingly distributed, producing arctangent shapes in displacement profiles crossing the fault. In places, the deformation zone reaches widths of $200+m$ and can be explained by a shallow east‐dipping fault rupture extending from 2 to 3 km depth to 70–120 m below the surface. A very shallow coseismic rupture on the Milun fault is consistent with a shallow locking depth interpreted from previous geodetic analyses from the interseismic period. Despite a few highly discontinuous and irregular surface ruptures reported along the southern section of the fault, our results suggest the main fault slip (up to 1 m) stopped at very shallow depths below the surface, in which $∼60%$ of the deformation may be accommodated as off‐fault deformation (OFD). In this upper $∼100m$ of the crust, OFD may be promoted by a significant change in material strength, as the fault crosses from bedrock and/or consolidated sediments into weaker, water‐rich, poorly consolidated alluvial sediments.

Land subsidence is a significant problem around the world that can increase the risk of flooding, damage to infrastructure, and economic loss. Hence, the continual monitoring of subsidence is important for early detection, mechanism understanding, countermeasure implementation, and deformation prediction. In this study, we used multiple-sensor observations from the Continuous Global Positioning System (CGPS), the small baseline subset (SBAS) algorithm, interferometric synthetic-aperture radar (InSAR), precise leveling, multi-layer compaction monitoring wells (MLCWs), and groundwater observation wells (GWs) to show the spatial and temporal details of land subsidence in the Choushui River alluvial fan (CRAF), Taiwan, from 1993 to 2019. The results showed that significant land subsidence has occurred along the coastal areas in the CRAF, and most of the inland subsidence areas have also experienced higher subsidence rates (>30 mm/yr). The analysis of subsidence along the Taiwan High Speed Rail (THSR) revealed a newly formed subsidence center between Tuku and Yuanchang Townships in Yunlin, with high subsidence rates ranging from 30 to 70 mm/yr. We propose a map showing, for the first time, the distribution of deep compactions occurring below 300 m depth in the CRAF.

An unusual devastating tsunami occurred on September 28, 2018 after a strike‐slip faulting earthquake in Sulawesi, Indonesia. The induced tsunami struck Palu city with ∼4‐m flow depth. We performed two analyses to investigate the source of the tsunami. We first conducted the teleseismic source inversion and obtained the overall slip distribution of the strike‐slip fault. Our tsunami simulation from the coseismic deformation of the seismically estimated strike‐slip faulting produced a tsunami comparable to the leading part of the observation at Pantoloan. In order to reconstruct the detailed slip distribution on the fault plane, we then jointly utilized the tsunami waveform and Synthetic Aperture Radar (SAR) data. Because of the lack of SAR data in the bay, the tsunami data is necessary to constrain the offshore slip distribution, which directly induces the tsunami. The inverted source model shows a strike‐slip fault which consists of three segments extending from the epicenter to the south of 1.4°S with two bends and two asperities around Palu city. The joint inversion model accurately reconstructs the observed surface displacements and the leading part of the tsunami waveform. Our result exhibits the significant contribution of the strike‐slip faulting to the tsunami, but it also suggests additional tsunami sources, such as landslides, for the high inundations near Palu bay. The result also indicates that regional devastating tsunamis can be generated by an onshore strike‐slip fault with localized large dip slip.

This letter presents a 3-D fusion method combining with the pixel offset results of synthetic aperture radar (SAR) and optical images for measuring 3-D coseismic deformation, which suffered the limitations of huge displacement gradient, low coherence, and large temporal interval. This method takes the advantages of the pixel offset results of the two different types of satellites. We use the hanging wall deformation of the 1999 Chi-Chi earthquake as an example and generate two sets of 3-D coseismic displacements from the fusion method and radar images only. We compare the two sets of results to GPS and field survey data, and the 3-D fusion result shows more consistent 3-D displacements than one derived from radar images with decreased root mean square (rms) values of 20%-50%. The results of this letter provide a detailed information of displacement distribution in the hanging wall of the Chelungpu fault (CLPF) during the Chi-Chi earthquake. Along the fault, the vertical displacement increases from south to north gradually and the vertical pattern follows the topography. The area where uplift starts to be higher than the average of vertical displacements is consistent with the turning point of CLPF. The 3-D fusion method appears not only the potentials to describe the uplift behavior of active fault, but also the abilities to constrain the subsurface fault geometry.