Taiwan Earthquake Research Articles

Temporal Variations of Earthquake Magnitude‐Frequency Relation in the Source Area of M ≥ 6.0 Earthquakes: A Systematic Survey in Taiwan

AbstractRecent studies in the earthquake magnitude‐frequency relation (b‐value) found that the b‐value can decrease with time before large earthquakes in the source area. Such a decrease even coincided with a burst of foreshocks immediately before the earthquakes implying a preslip migrating toward the nucleation zone. We systematically survey the b‐value variations in space and time in the source area of 17 earthquakes with magnitudes greater than ML 6.0 in Taiwan. We relocated the earthquakes released by the Central Weather Administration of Taiwan since 2012 as timing can provide a sufficiently low completeness magnitude (MC) of 1.5. We carefully determine the spatiotemporal search criteria on seismicity in the source area of all targeted earthquakes. We surveyed the temporal b‐value systematically using moving time windows with a given number of earthquake events with the magnitudes greater than MC. We found the b‐value decreased clearly for 2 days before the 2018 ML 6.3 Hualien earthquake, coinciding with a burst of ML 5.8 earthquake and its aftershocks nearby as foreshocks. The foreshocks migrated updip toward the hypocenter of the 2018 ML 6.3 Hualien earthquake and revealed a second decrease in the b‐value 10 hours before it occurred. The b‐value precursor primarily comes from a rapid reduction of small earthquakes in the foreshocks and agrees with recent key findings of preslip. However, there is no strong correlation between the b‐value precursor and coseismic slip. Apart from this, the b‐values did not change significantly in most cases of earthquakes in Taiwan before and after they occurred.

Reconnaissance of the 2022 Guanshan and Chihshang earthquakes in eastern Taiwan

Two significant earthquakes struck eastern Taiwan on consecutive days in mid-September of 2022. The first, the Guanshan earthquake, occurred on the night of September 17 (local time) with a local magnitude (ML) of 6.4, and the second, the Chihshang earthquake, occurred on the afternoon of September 18 with a mainshock of ML of 6.8. The strong motion of these two events resulted in a series of ground surface ruptures, 2 collapsed buildings, two collapsed bridges, and more than 100 partially damaged structures along the Chihshang and Yuli faults around the Longitudinal Valley in eastern Taiwan. The observed response spectra at the damage sites of the Chihshang earthquake were significantly larger than the design response spectra of the 1997 Taiwan building code. Near-fault velocity pulses with a maximum value of 132 cm/s were observed along the faults, destructively impacting the damaged structures. The details and causes of the structural damage are presented in this article according to the findings of the on-site reconnaissance and ground motion analysis. Finally, the behavior of selected structures that have a structural health monitoring system at the time of these two destructive earthquakes is also evaluated.

Boulder transport and wave height of a seventeenth-century South China Sea tsunami on Penghu Islands, Taiwan

Abstract. The South China Sea faces widespread tsunami risks from diverse sources, including trench megathrusts, intraplate earthquakes, and landslides. However, historical and geological records to constrain worse-case simulations are scarce. The cliff-top basalt boulders on the Penghu Islands in the Taiwan Strait provide wave estimates from incipient motion formulas and stratigraphic links to the probable sources. Calibrating for ancient local sea levels and a 100-year surge indicates that storm waves in the shallow interisland bathymetry only enable boulder sliding–rolling below the 2.5 m high cliff. A minimum tsunami wave height of ∼ 3.2 m is necessary for cliff-top overflow to exceed boulder height and terminal rolling before deposition. Coeval gravels in two other outcrops also record the time and extent of tsunami deposition with beach-derived bioclasts, stranded pumices, a sharp base, matrix support, poor sorting, and elevations surpassing the 100-year surge. These gravels mark local minimum wave run-ups, reaching 2.4–4.0 m above sea level. The radiocarbon age of the studied boulder, between 1575 and 1706, suggests a probable tie to the disastrous 1661 earthquake in southwest Taiwan and the megathrust source in the northern Manila Trench.

The Assessments of Seismic Hazards for the Potential M<sub>L</sub> 7.0 Changhua Earthquake in Taiwan and the Strategy of School Seismic Disaster Risk Mitigations and Management

The Assessments of Seismic Hazards for the Potential M<sub>L</sub> 7.0 Changhua Earthquake in Taiwan and the Strategy of School Seismic Disaster Risk Mitigations and Management

Sensitivity limits for strain detection of hypothetical remote fluid-induced earthquakes (Mw ≥ 4): a case study in Taiwan

Capturing and quantifying the timing of remotely triggered earthquakes and understanding the physical processes responsible for this delay represent major challenges in earthquake forecasting. In this study, we propose a physical framework for the integration of borehole strainmeter observations for the investigation of remote triggering of moderate to large earthquakes (Mw ≥ 4) in Taiwan. Based on the time-delay computation between regional events and global earthquakes, we establish a selection of earthquakes showing fault zone properties (hydraulic diffusivity and nucleation length) that may be compatible with a magnitude-dependent fluid-induced nucleation process. Using theoretical fault zones parameters, we calculate the evolution of fluid pressure transiting along the nucleation region under the assumption of a one-dimensional, homogeneous poroelastic medium. Pore pressure levels reached before earthquake rupture are ranging from about 0.02 kPa to 3 kPa in the case of teleseismic wave-induced elastic pressure ranging from 0.15 kPa to 27.3 kPa. To compute the time-dependent evolution of deformation generated by a remote diffusing pressure front, we model the nucleation region using the analogue volcano source represented by a horizontal circular crack, and calculate synthetic dilatation at the strainmeter location from displacements using a finite-difference approach. In general, predictions are about two to four orders of magnitude smaller than observations (∼ 10–5 to 10–3 nϵ). Therefore, this suggests that detection of pore pressure-related deformation would have required change of volume in the nucleation region that is at least one order of magnitude larger than for the hypothetical cases considered here. The study represents the first attempt to analyze strain time-series for detecting pre-earthquake strain anomalies related to fluid-induced earthquakes and illustrates the challenge for detecting and characterizing intermediate-to far-field earthquake precursors caused by fluid flow in active regions.

Correlations between Ground Motion Parameters Measures and Structural Damages of the Mw6.4, 2016 Meinong Taiwan Earthquake Using Hybrid Simulation Method

Correlations between Ground Motion Parameters Measures and Structural Damages of the Mw6.4, 2016 Meinong Taiwan Earthquake Using Hybrid Simulation Method

Mechanisms of vegetation restoration at landslides caused by a catastrophic earthquake in Central Taiwan

The vegetation restoration of a large-scale landslide, triggered by the catastrophic earthquake on 21 September 1999, in Jiujiu Peaks, Central Taiwan with an impacted area of 821 ha recovered 80% by 2020 was studied using self-organizing map (SOM) coupled with multi-temporal SPOT satellite images and a terrain-based distribution index for a 20-year period. Although disturbed by several typhoons during two decades of natural vegetation succession, the landslide restoration rate has reached 87.5% with the invasion or regrowth of vegetation gradually. A predicted logarithmic model with statistically significant difference was derived to estimate the restoration trend of the landslide in the studied area. Most of the poorly vegetated areas are located along the ridgelines, as verified by field surveys. Landslide restoration was carried out in three stages, (1) vulnerable landslides and fast-growing invasive vegetation (1999/9 - 2005/9); (2) stabilized landslides and slow-growing vegetation toward the vegetated strips (2005/9 - 2009/11); and (3) more stabilized landslides and vegetation toward secondary forest (2009/11–2020/2). Topographic location, water supply, typhoon disturbance, invasive or residual vegetation patterns and succession time are the main factors of landslide restoration. The evaluated results indicate that nature itself is a complex ecological balance system with a strong capacity for vegetation recovery at landslides, and can be used by government agencies to add in the recovery of landslide areas.

Temporal distribution characteristics of earthquakes in Taiwan, China

The characteristics of seismic temporal distribution represent an important basis for earthquake prediction and seismic hazard analysis. In this paper, based on the seismic catalogs in Taiwan, and using Poisson (exponential distribution), Gamma, Lognormal, Weibull, and Brownian passage time distributions as target models, we adopt the maximum likelihood method for estimating model parameters. The optimal model for describing the temporal distribution of earthquakes in Taiwan is determined according to the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), K-S test, Chi-square test, and coefficient of determination R2 results. The results show that for moderate-strong earthquakes events (MW < 7.0), the Gamma distribution model can well describe the temporal distribution characteristics of earthquakes, while large earthquakes (MW ≥ 7.0) can be described entirely by exponential distribution. In addition, the temporal correlation between earthquakes is also examined through diffusion entropy analysis. The results show that seismic activity features temporal correlation, and earthquakes with relatively small magnitude (MW < 7) are affected by larger events (MW ≥ 7.0), thus suggesting long-term memory in time. In this study, the probability of the occurrence of a major earthquake in Taiwan is also calculated. The results show that the probability of an MW ≥ 7.0 earthquake in Taiwan in the next 10 years reaches 91.3%. The results may be used to inform the selection of seismic time distribution models and the calculation of seismic activity parameters in earthquake prediction and seismic hazard calculation, and hold scientific significance for understanding the mechanism of earthquake genesis.

Short-Term Deep Postseismic Slips Following Large Earthquakes in Southern Taiwan

Abstract Deep postseismic slips that reflect the rheology and the deformation of the seismogenic fault after large earthquakes are usually investigated less than shallow slips because of the difficulty of obtaining direct observations. In this study, we used the seismicity of repeating aftershock sequences (RASs) to improve our understanding of the deep postseismic slips after three large earthquakes in southern Taiwan. To more precisely characterize the evolution of the RASs, we applied a template-matching technique to continuous waveform data for 90 days before and after the mainshocks. We identified 28 RASs that mainly occurred in regions near the mainshock hypocenters with relatively high VP/VS ratios. The deep fault slips estimated from the RASs show that the postseismic slip rates decreased logarithmically with increasing duration time, suggesting that the faults were creeping according to the velocity-strengthening friction law. We inferred that the high hydraulic pressure environment contributed to the fault creep, but the dynamic stress perturbation may have been the main factor affecting the fault creep. The results of this study improve our understanding of the behavior of deep faults and may aid in future seismic hazard assessments in Taiwan.

Rapid seismic damage state assessment of RC frames using machine learning methods

A rapid seismic damage state assessment of individual building is essential for a region-scale risk and vulnerability assessment that requires significant manpower, time, and computational efforts. In this study, three machine learning (ML) algorithms that exhibited high predictive accuracy in previous studies, namely random forest (RF), extremely gradient boosting (XGB), and active machine learning (AL) were used to develop models for rapidly assessing the seismic damage states of reinforced concrete (RC) frames after an earthquake. Compared to RF and XGB, the active machine learning develops an efficient model with a small number of instances by interactively selecting the valuable instances for desired outputs. Using these aforementioned algorithms, three predictive models were developed, tested, and validated using a comprehensive dataset which included a total of 9900 data points. The dataset was developed according to a non-linear time history analysis involving a combination of 199 RC frames and 50 ground motions. The results indicated that active machine learning predicted the damage states of RC frames with an accuracy of 84% in the testing dataset, followed by the XGB algorithm with an accuracy of 80%. These predictive models were also validated using actual damaged buildings in the Taiwan earthquake. Seismic design intensity (SDI) and spectrum intensity (SI) were the most important input features in the damage states of RC frames, with a relative importance factor exceeding 50% for the two features. Constructed periods have a non-negligible influence on the damage states of RC frames when these differ for regional buildings. Finally, an interactive and user-friendly graphical user interface (GUI) platform was created to provide a rapid seismic damage state assessment of RC frames. This study represents a pioneering step toward the application of AL in damage state assessment of existing RC frames.

ADPD: Anomaly Detection for Population Distribution in Geo-Space Using Mobile Networks Data

Real-time population mobility pattern at a specific time is an essential indication for sudden events. With the high penetration ratio of mobile phones, the mobile network could serve as a sensor network to monitor the population distribution, and user positioning without extra cost because the distribution of mobile phones is approximately the same as the population distribution. The abnormal spatial-temporal transition of the population is one of the critical indicators for sudden events. In this article, using the log data obtained from the mobile networks, we propose an AI-based framework, anomaly detection for population distribution (ADPD), to detect abnormal population distribution in geo-space. Different from the previous works, to detect anomaly of a specific grid area, the ADPD uses only the population information in the grid, which makes the ADPD more practical in the actual situation. We investigate the performance of the ADPD by running experiments based on the log data of the mobile network obtained during an actual sudden event, the 2018 Hualien Earthquake in Taiwan. Our study shows that the ADPD can identify the abnormal population transition grids nearby the grids with sudden events.

Earthquake-induced persistent and instantaneous groundwater variations caused by volumetric strain of soil in Taiwan from 1999 to 2020

Estimating the magnitude of earthquake-induced groundwater level (GWL) based on poroelastic theory is a challenge for researchers. To address this challenge, the present study explores this topic in the context of volumetric strain induced by ground shaking. Specifically, GWL records on the Chi-Chi earthquake in Taiwan, along with other selected events from 2004 to 2020, are analyzed to identify the persistent and instantaneous changes of GWL under distinct geological conditions. The magnitude of the persistent GWL change is highly correlated with peak ground acceleration, and thickness and density of sandy layers. This finding is explained by the magnitude of volumetric strains caused by soil particle rearrangement associated with ground motion intensities and site-specific conditions. Meanwhile, the instantaneous GWL change caused by seismic wave propagation exhibits a highly negative correlation with the vertical ground motion velocity time history because the compression wave induces instantaneous contraction or dilation of the soil. Moreover, the peak instantaneous GWL change correlates well with the peak ground velocity (PGV) in the vertical direction because the compressional (volumetric) strain is theoretically proportional to the PGV of vertical motion.

PERFORMANCE EVALUATION OF 34 FLOORS BUILDING STRUCTURE IN SURABAYA BASED ON SNI 1726:2012 AND SNI 1726:2019

Indonesia has undergone several earthquake regulations updates, starting from Peraturan Muatan Indonesia 1970 to SNI 1726:2019. This update requires earthquake loads with a larger return period. This has an impact on the existing buildings that were planned to use the old regulations. It is feared that the building does not meet the requirements required by the new regulations, so a review of the performance of the building is needed. This research will use a case study of a Cornell apartment building with 34 floors in the city of Surabaya, which is planned based on SNI 1726:2012 with concrete regulations SNI 2847:2013 and will be evaluated with SNI 1726:2019. The analysis uses Performance Based Design with the Nonlinear Time History Analysis method which was carried out in the 2016 ETABS program. The background to the use of the Performance Based Design method is its use which is quite easy to apply and can also be used to measure the efficiency of the structure being reviewed. The use of Nonlinear Time History Analysis is based on the fact that the use of this method has been regulated in SNI 1726:2019 and the use of this method is considered closest to the actual conditions in the field. Nonlinear Time History analysis in this study uses time history data from the Chichi earthquake in Taiwan in 1999. The evaluation of building performance is based on the performance level refer to FEMA 356. The results of the case study on the comparison of the two regulations show that there is an increase in the basic earthquake force by 1.02%. Meanwhile, in relation to drift ratio analysis, an increase of 1% on the X axis and 5.5% on the Y axis is obtained.

Seismo-Ionospheric Effects Prior to Two Earthquakes in Taiwan Detected by the China Seismo-Electromagnetic Satellite

In this paper, we focused on the characteristics of the seismo-ionospheric effects related to two successive earthquakes, namely, the earthquakes in 2022 in Taitung Sea, Taiwan, China, with magnitudes (M) of 6.7 and 6.3, at 23.45° N, 121.55° E and 23.39° N, 121.52° E and with the same focal depth of 20 km, which were detected by the China Seismo-Electromagnetic Satellite (CSES). By applying the sliding interquartile range method to electron density (Ne) data acquired by the Langmuir probe (LAP) onboard the CSES and the grid total electron content (TEC) data obtained from the Center for Orbit Determination in Europe (CODE), positive anomalies were found under quiet geomagnetic conditions on 2–3 March and 8–9 March 2022—that is, 19–20 and 13–14 d before the earthquakes, respectively, and the global ionospheric mapping (GIM) TEC data suggested that anomalies may also have been triggered in the magnetic conjugate area 13–14 d prior to the earthquakes occurrences. In addition, the CSES Ne data showed enhancements 3 and 5 d before the earthquakes occurred. Furthermore, 138 earthquakes with M ≥ 5.0 that occurred in Taiwan and the surrounding region during the period February 2019 to March 2022 were statistically analyzed using the CSES Ne data. The results show that most of the Ne anomalies were positive. Moreover, the greater the earthquake magnitude, the greater the frequency of the anomalies; however, the amplitude of the anomalies did not increase with the earthquake magnitude. The anomalies were concentrated during the period of 10 d before to 5 d after the earthquakes. No increase in the amplitude of anomalies was observed as the time of the earthquakes approached. Finally, based on evidence relating to earthquake precursor anomalies, we conclude that it is possible that earthquakes in Taiwan and the surrounding region affect the ionosphere through the geochemical, acoustic, and electromagnetic channels, as described by the lithosphere–atmosphere–ionosphere coupling (LAIC) model, and that the two studied earthquakes in Taiwan may have induced ionospheric effects through the geochemical channel.

Deep Learning of Detecting Ionospheric Precursors Associated With M ≥ 6.0 Earthquakes in Taiwan

AbstractA short‐term (30 days before an earthquake) prediction of an earthquake is a big challenge in seismology. As a first step, we apply deep learning to the ionospheric total electron content (TEC) data between 2003 and 2014 to detect the seismo‐ionospheric precursors of M ≥ 6.0 earthquakes in Taiwan. The bidirectional Long Short‐Term Memory (Bi‐LSTM) network is employed to use observed input data (features) to obtain the sequential TEC variations. The five input features are sequential vectors of TEC, the geomagnetic index Dst, the solar activity index F10.7, sunspot number (SSN), and solar emission index Lyman‐α. The daily values of F10.7, SSN, and Lyman‐α are converted into hourly values, depending on the solar elevation angle. The calculated hourly TEC variations can be more precisely predicted with this data conversion. We calculate the normalized difference of errors between two 15‐day adjacent stages as the “relative error”. Three trained models with the best discrimination between the relative errors of earthquake and no‐earthquake cases are chosen as classifiers. These three classifiers are then used to have a majority vote to declare whether the 30‐day period is related to the preparation of an earthquake or not. The results show that all 22 positive cases (earthquakes) are successfully predicted, giving a true positive rate of 100%. Among the 19 negative cases (normal cases), 10 of them are true negative.” Overall, a high accuracy of 78.05% is obtained.

Analysis on the impact of Taiwan far-field earthquakes on the disaster avoidance behavior of people in high-rise buildings in large cities in southeast China

Taiwan Province is an earthquake-prone area, and strong earthquakes in Taiwan could affect coastal cities in the mainland. The high-rise buildings in coastal cities often are seriously affected, which can cause social panic. Therefore, it is necessary to study the seismic impact of moderate and strong earthquakes in Taiwan on the mainland coast to accurately analyze the effect on buildings in this area, especially the responses of people in high-rise buildings after the earthquake, and to provide a relatively accurate reference for the evaluation of the timely restoration of social order. This paper uses the 43.29 million mobile phone location records collected after the Ms6.1 earthquake in Hualien, Taiwan on April 18, 2021, for the bandwidth selection in kernel density estimation in different regions and conducts a quantitative density analysis of 331 buildings using the communication check-in data after the earthquake on different temporal and spatial scales. Through this work, an exponential model of people’s responses in high-rise buildings to far-field strong earthquakes in Taiwan is obtained, and the flow pattern of people in regard to disaster avoidance in high-rise buildings after far-field non-destructive earthquakes is summarized. This article can be a reference for the local government to judge the impact of Taiwan’s far-field earthquakes and to make decisions with respect to disaster relief.

Probabilistic Liquefaction Analysis Using Standard Penetration Test

Abstract The Youd etal liquefaction resistance curves developed in 2001 to characterize the cyclic resistance of soil based on SPT test are the most used in the context of the Seed and Idriss simplified procedure as a deterministic model. These curves were developed from a modified database of Seed etal. in 1985 with the assumption that the actual peak shear stress (τd) induced at depth h is always less than that predicted by the simplified procedure (τr) of Seed and Idriss (rd= τd/τr<1). By using a suite of equivalent linear site response analyses to adjust the dynamic and the simplified shear stress at depth h, Filali and Sbartai showed in 2017 that the dynamic peak shear stress for some earthquakes is greater than the simplified peak shear stress (rd>1). As in this case, the assumption of the simplified procedure is not verified, Filali and Sbartai have proposed a corrector factor (RC) in the range where rd >1 to adjust the deformable and rigid body. In this paper, we will present a probabilistic study for the evaluation of the liquefaction potential using a database based on SPT measurement compiled after the Chi-Chi Taiwan earthquake, in which the cyclic stress ratio is evaluated using the proposed corrector factor. The objective of this study is to present a probabilistic shape of the cyclic resistance ratio (CRR) curves based on the original simplified method of Seed and Idriss and the corrected version and a new formulation for computing the probability of liquefaction.

Gouge fabrics reset by thermal pressurization record stress on faults after earthquakes

Abstract Stress on seismogenic faults provides critical information about how much elastic energy is stored in the crust and released by earthquakes, which is crucial in understanding earthquake energetics and recurrence. However, determining post-earthquake stress states on faults remains challenging because current borehole methods are rarely applicable to damaged fault zone rocks. We applied neutron texture analysis to gouge samples of the 1999 Chi-Chi earthquake in Taiwan to infer the stress state after the earthquake. Results indicate that the clay fabric within the principal slip zone is orthogonal to the fault plane, whereas outside the principal slip zone the fabric is predominantly parallel to the bedding-parallel fault plane. We suggest that the clay fabric in the slip zone was first neutralized by the coseismic fluidization caused by thermal pressurization and later re-oriented to the new direction of post-earthquake principal stress. Such stress orientation is consistent with the orientations inferred from core-scale fault slip data and dislocation models constrained from global navigation satellite system displacements. If thermal pressurization is a ubiquitous process during earthquakes, gouge fabrics can be used to help probe the post-earthquake stress state of faults.

Validation of the Probabilistic Seismic Hazard Assessment by the Taiwan Earthquake Model through Comparison with Strong Ground Motion Observations

Abstract To validate the probabilistic hazard assessment proposed by the Taiwan Earthquake Model (TEM), we compared it with the strong ground motion observations. We accessed the Taiwan Strong Motion Instrumentation Program (TSMIP) database and reported the maximum ground shaking of each strong-motion station. Comparing the TSMIP observations and the TEM hazard model reveals similar spatial patterns. However, some records indicate significantly higher shaking levels than the model does due to the occurrence of some large events, for example, the 1999 Mw 7.6 Chi-Chi earthquake. Such discrepancies cannot be explained by model parameter uncertainties but by unexpected events in the given short observation period. We have confirmed that, although each seismogenic structure in Taiwan is unlikely to rupture within a short period, the summarized earthquake potentials from all of the structures are significant. In addition, we discuss the impacts of some model parameters, including epistemic uncertainties of source parameters, truncation of standard deviation for ground-motion prediction equations, the Gutenberg–Richter law for area source, and the time-dependent seismicity rate model. The outcomes of this study provide not only crucial information for urban planning on a city scale and building code legislation on a national scale but also suggestions for the next generation of probabilistic seismic hazard assessment for Taiwan as well as other regions.

Modeling of earthquake-induced landslide distributions based on the active fault parameters

Earthquake-induced landslides can cause enormous damage and numerous casualties in mountainous areas worldwide; consequently, accurate assessment of the potential distribution of earthquake-induced landslides is an important issue. For a national disaster prevention agency, it is desirable to be prepared to rapidly evaluate disasters and risks from information that can be scarce or easily available. The present study examined landslides triggered by reverse and strike-slip fault earthquakes, focusing on recent cases in Japan with relatively complete landslide inventories and detailed active-fault information. The landslide distributions and parameters of active faults were compared, and it was found that the skewness and kurtosis of the landslide distribution for each earthquake event was close to zero, indicating that the distributions followed the normal distribution. The mean distance of the landslide distribution from the active fault is negatively correlated with the inclination of the active fault, while the standard deviation is negatively correlated with the fault-top depth of the active fault and positively correlated with the magnitude of the earthquake.Based on our findings, we conducted a regression analysis of the relationship between the mean distance from the active fault and the inclination of the active fault. The mean distance of the landslide from the active fault increased when the active fault had a lower inclination, and was regarded as zero when the inclination was greater than 60°. In addition, a relationship between the standard deviation, depth of fault top, and earthquake magnitude was established using multiple regression analysis. We thus confirmed the accuracy of the methodology using the actual landslide distributions of recent earthquakes in Japan. The length of the active fault can be used as input for the methodology, to estimate the maximum magnitude of the respective earthquake. Furthermore, the 95% confidence interval appears to cover almost all the large landslides, which enables us to limit the extent of areas that should be considered as the most exposed to co-seismic landslide hazards. The applicability of the proposed methodology was successfully tested using the case of the 1999 Chi-Chi earthquake in Taiwan with a seismic mechanism similar to the Japanese earthquake. Consequently, the proposed methodology can be applied to estimate the potential distribution of landslides caused by reverse and strike-slip fault earthquakes, based on the parameters of the active faults.