Search

In this paper, a scalable end-to-end tree boosting system called XGBoost has been applied for predicting the magnitude of an earthquake from the early part of earthquake waveform data. This model uses the features extracted from the early P wave phase of the records as an input. The model's effectiveness has been verified by using data on earthquakes occurring in the Eurasian plate of Japan Islands from 1996 to 2021. Feature engineering has given 29 new features identified from the early P wave phase of the record, which show a high correlation with the magnitude of an earthquake. The comparison of predicted and actual magnitude shows that a trained XGboost model, which uses a single input record for magnitude prediction, gives an average prediction error of 0.004 ± 0.57 for earthquakes in the test dataset. In contrast, the average prediction error of –1.1 ± 0.80 and –0.65 ± 0.69 has been obtained for the magnitude estimated from conventional τc and Pd methods using the same test dataset. It is further seen that the average predicted magnitude of a single earthquake of magnitude 4.5 and 6.1 (MJMA) obtained by using multiple nearfield records using XGBoost model is 4.58 ± 0.33 and 6.32 ± 0.29, which is close to the actual magnitude of the earthquake. The results presented in this paper clearly show that the structured data can be effectively used by complex machine learning or deep learning models to predict earthquake magnitude from single or multiple records. [ABSTRACT FROM AUTHOR]

Earthquake swarms are most commonly composed of small‐magnitude earthquakes. However, a recent study by Yoshida, Uchida, et al. (2023, https://doi.org/10.1029/2023GL106023) analyzed a swarm beneath the Noto Peninsula in Japan that, after more than two years of moderate‐magnitude seismicity, triggered the moment magnitude (Mw) 6.2 Suzu mainshock in May 2023. Based on high‐precision earthquake locations and a slip inversion of the mainshock, these authors found that the Mw 6.2 Suzu earthquake occurred on the updip extension of a fault that was active during the swarm, likely driven by increased fluid pressure. After publication of that paper, a much larger and more destructive Mw 7.5 event occurred nearby on 1 January 2024. These events underscore the potential for swarms to be precursors to large, damaging earthquakes. Forecasting the eventual evolution of swarms is currently very challenging but could be aided in the future by new observations and models. Plain Language Summary: Although earthquake swarms often only contain small earthquakes, occasionally they can trigger large, damaging earthquakes. Yoshida, Uchida, et al. (2023, https://doi.org/10.1029/2023GL106023) examined the triggering of a magnitude 6.2 earthquake in Japan, which caused extensive damage, following two years of smaller earthquakes. This sequence, like many swarms, may have been driven by elevated fluid pressure migrating upwards within the crust. After publication of that paper, a much larger and more destructive Mw 7.5 event occurred nearby. Forecasting the eventual evolution of ongoing swarms is currently very challenging but could be aided in the future by new observations and models. Key Points: Earthquake swarms can be precursors to damaging earthquakes, including the 1 January 2024, Mw 7.5 Noto Peninsula, Japan eventFluid pressure changes often drive swarm activity, and their degree of confinement may influence swarm evolutionDirect observations of fluids in fault zones combined with numerical modeling may aid swarm forecasting in the future [ABSTRACT FROM AUTHOR]

The Fukushima power station in Japan was affected by a major earthquake and tsunami in March 2011, inspecting the primary containment vessel remains difficult due to high radioactivity. Long-reach robot arms are useful in inspecting such hazardous environments, and a coupled tendon-driven mechanism enables realizing a long, light-weight, and thin manipulator. However, high elastic elongation of tendons due to gravity may lead to unstable joint control. In this paper, we introduce dynamics-based control as a feasible strategy for a long-reach tendon-driven robotic arm. Additionally, a planning method to identify the joint angle path ensuring stability is proposed. Considering stability analysis, the potential due to the tendon elasticity and gravity is evaluated and used as an index of joint stability. The rapidly exploring random tree is used as the planning algorithm. The effectiveness of the proposed method was demonstrated through the successful manipulation of a 5-kg payload by a 10-m long robotic arm. [ABSTRACT FROM AUTHOR]

The electron density (Ne), ion density (Ni), and electron temperature (Te) statistics recorded by the DEMETER satellite payload ISL (Instrument Sonde de Langmuir) were used to study the disturbance characteristics of the ionosphere before solid earthquakes of magnitude 6 or higher in Japan during the summer of 2005 – 2009 , to provide more information and methods for the coupling mechanism and short-range earthquake prediction. In this paper, the region of ± 10 ° of the epicenter is divided into 1 ° × 1 ° pixels, and the background field of each parameter is constructed using data without earthquakes and relatively calm space weather. We also define a measure of the perturbation intensity of ionospheric parameters relative to the background field during the occurrence of earthquakes. The analysis results of the four Japanese earthquakes from space and time show an excellent synchronization in the time and area of the anomalies in ionospheric parameters of the four cases. All four instances showed Ne abnormalities, and three showed Ni and Te anomalies, in which N e and Ni increased or decreased abnormally, while Te increased abnormally every time, and the anomalies mainly occurred about 9–12 days before the earthquake. This paper eliminates the influence of solar, geomagnetic, and satellite data defects on the experimental results as much as possible in data screening and method selection. The results partially agree with the conclusions reported in the existing literature, and the obtained anomalies are somewhat related to the ionospheric precursors of earthquakes. [ABSTRACT FROM AUTHOR]

This paper discusses the relationship between the vertical ground motion and ionospheric disturbances before the Kumamoto earthquake on 16 April 2016, in Kyushu, Japan, using the vertical ground motion measured by slant gauges widely distributed in Kyushu, and the NmF2 observed by ionosondes in Japan and another region. We provide evidence that vertical ground motion excites internal gravity waves (IGWs) that disturb changes in the ionospheric plasma density. From the spectral analysis results of the vertical ground motion data, the summation of various period (frequency) components analyzed from the original data of the slant gauge shows a possible correlation with the change of NmF2 before the earthquake. On the other hand, the influence of the geomagnetic disturbance on vertical ground motion seems to exist. However, we cannot confirm that vertical ground motion is influenced by the geomagnetic disturbance (Kp index) and that the earthquake is triggered by the geomagnetic disturbance. There are two conditions for the vertical ground motion to disturb variations in the ionospheric plasma density: (1) The effective vertical ground motion period should be shorter than 5 h. In addition, (2) vertical ground motion should continue to exist so that wave energy can be continuously injected into the atmosphere. A possible mechanism with which to modify the ionosphere is discussed. The results of this study can provide a basis for the future ionospheric precursors of earthquakes by using the vertical ground motion. [ABSTRACT FROM AUTHOR]

In this paper, we explore the use of seismicity data on a single-station basis in site response characterization. We train a supervised deep-learning model, SeismAmp, to recognize and separate seismic site response with reference to seismological bedrock (VS  = 3.45 km s−1) in a broad frequency range (0.2–20 Hz) directly from single-station earthquake recordings (features) in Japan. Ground-truth data are homogeneously created using a classical multistation approach—generalized spectral inversion at a total number of 1725 sites. We demonstrate that site response can be reliably separated from single-station seismograms in an end-to-end approach. When SeismAmp is tested at new sites in both Japan (in-domain) and Europe (cross-domain), it achieves the lowest standard deviation among all tested single-station techniques. We also find that horizontal-to-vertical spectral ratio (HVSR) is not the optimal use of single-station recordings. The individual components of each record carry salient information on site response, especially at high frequencies. However, part of the information is lost in HVSR. SeismAmp could lead to improved site-specific earthquake hazard prediction in cases where recordings are available or can be collected at target sites. It is also a convenient tool to remove repeatable site effects from ground motions, which may benefit other applications, for example, improving the retrieval of seismic source parameters. Finally, SeismAmp is trained on data from Japan, future studies could explore transfer learning for practical applications in other regions. [ABSTRACT FROM AUTHOR]

Peak ground acceleration (PGA) is a key parameter used in earthquake early warning systems to measure the ground motion strength and initiate emergency protocols at major projects. The traditional P -wave peak displacement-dependent PGA prediction model (Pd-PGA model) tends to underestimate the PGA for large earthquakes because it cannot make full use of the fault continuity rupture information hidden in the time-varying process of ground motion. In this paper, a continuous PGA prediction long short-term memory (LSTM) neural network model is proposed. The model takes eight sequential features of stations that are proxies of the energy and other physical parameters as input and provides the recorded PGA at the station as the target output. A total of 5961 records from 119 earthquakes recorded by the Japanese Strong-Motion Earthquake Network (K-NET) in Japan are used to train the neural network and 3433 records from 73 earthquakes are used as the test set to verify the model's generalization ability. The results show that within the same data set, the residuals of the predicted PGA for the proposed model are smaller than those of the Pd-PGA model and that the problem of PGA underestimation is resolved. The prediction accuracy also improves with increasing sequence length, which indicates that the LSTM neural network learns the rules hidden in the time series. To further verify the model's generalization ability, the model performance is analyzed for an M 7.3 earthquake that was not included in the training or test data sets. The results show that the residuals of the predicted PGA for the event are consistent with those for the test data set, indicating that the model has good generalization ability. [ABSTRACT FROM AUTHOR]

The motivation of this study stems from a retaining wall made of waste tires. The wall did not suffer any earthquake or tsunami-induced damage during the 2011 Off the Pacific Coast of Tohoku Earthquake, Japan. This paper deals with a case study on this tire retaining wall. Results from a series of field and laboratory investigations are first described. A numerical simulation is also described in which whole tires were used as protective layers in an embankment. The results show that confining effect of each tire, friction between the tires, ductility, and damping inherent in tires contribute towards the excellent performance of the retaining wall during the earthquake loading. The case study also reveals that it is the isolation mechanism due to the vibration absorption capability of rubber particles in tires, which could protect tire retaining structure during the earthquake. [ABSTRACT FROM AUTHOR]

Shikoku island, southwestern Japan lies in the western Nankai Trough and showcases along-strike segmentation of slow earthquake behavior. Whether the spatial variation of tremor behavior reflects the regional differences in structure/source properties and how much such differences can be recognized by the seismic signals themselves are two questions addressed in this paper. Taking advantage of advanced methods in recognizing and classifying signals using machine learning approaches, we attempt to answer them by conducting signal classification experiments in Shikoku. Based on the tremor catalog from 1 June 2014 to 31 March 2015, the tremors recorded in four different areas were treated as different classes and segmented into 60-s-long signals. The number of tremors in four different areas (A to D, from west to east) reached 15,000, 31,000, 10,000, and 16,000, respectively. To efficiently distinguish between tremors from different areas, we applied a k-nearest neighbor (k-NN) classifier with Fisher's class separability criteria to select the optimal feature subset. The resulting classification performance reached more than 90% at all 12 stations. We further designed a triangle test to select the features that can better represent the differences in source properties between areas. We found that the most efficient features were associated with (1) the number of peaks in the temporal evolution of discrete Fourier transforms and (2) the energy distribution in the autocorrelation function (ACF). To match the difference in behavior revealed by the ACF, the size of the tremor zone, which mainly controls how long the seismic energy lasts in a tremor episode, was determined to be largest in Area B and smallest in Area C. The heterogeneity of the asperities in a tremor zone, which may control how spiky the tremor signals developed over time, was determined to be strong in Areas B and C. Together with previously documented variations in slow earthquake behavior in the same area, we finally propose a conceptual model that provides a better understanding of the regional differences in the tremor source properties in Shikoku, Japan. [ABSTRACT FROM AUTHOR]

In this paper, we explore the Western Pacific subduction impact on the geodynamics of the Asian continent. The data on migration of slow strain and earthquakes from the Nankai, Japan and Kuril-Kamchatka segments of the Western Pacific subduction zone deep into mainland Asia are analyzed. The calculations performed on five profiles, crossing the Kuril Islands, the Japanese Archipelago and Sakhalin Island toward the Asian continent, have revealed the transverse migration of earthquakes from the Japan–Kuril-Kamchatka subduction zone. The velocities of hypocenter migration of M ≥ 4.5 earthquakes from the Kuril-Kamchatka Trench via northern and central Sakhalin vary from 6 to 17 km/year, on average, at different depths. The profiles crossing the islands of Hokkaido and Sakhalin show the M ≥ 4.earthquake migration from the Kuril and Japan trenches at velocities of 8–27 km/year. [ABSTRACT FROM AUTHOR]

A modified k-nearest-neighbors method is introduced that provides an efficient nonlinear estimate of the intensity of a point process (field) based on locations of events. The method is applied to perform a detailed statistical analysis of the spatial structure of the seismic intensity field (in the context of this paper, the term "intensity" refers to the intensity of the seismic field, and should not be mistaken for the intensity of ground motion caused by an earthquake). The proposed method requires neither a preliminarily delineated area nor a normalization procedure for the estimates. In contrast to many interpolation methods, estimates based on the proposed method are statistically justified. The "uncertainty relation" between the spatial smoothing effect and random errors is established for the method in an explicit form. A procedure for choosing the number of nearest neighbors k* that controls the effective radius of smoothing is suggested. The proposed method is applied to analyze the seismic intensity field in two seismogenic regions surrounding the Kuril Islands and Japan during the period from 1904 to 2011. Spots of increased seismic activity in these regions are localized by the new method, and some quantitative statistical characteristics of these spots are determined and discussed. [ABSTRACT FROM AUTHOR]

Rupture size is a fundamental earthquake source parameter that is challenging to infer independently from far‐field seismological observations. Here, we develop a novel observational constraint on source size based on the decay rate of wavefield coherence across a seismic array. For a given earthquake, waveform coherence decays with increasing interstation distance or, more precisely, with increasing projection difference defined as the difference between the takeoff vectors associated to the two stations projected along the rupture direction. We find that coherence generally falls off with projection difference faster for earthquakes of larger magnitudes. The magnitude dependence of the coherence decay rate can be explained by a finite source effect: larger source sizes cause larger differences of phase delays between waves arriving from different parts of the rupture at different stations, hence a stronger spatial variability of the wavefield, resulting in a breakdown of waveform coherence. Assuming a 1‐D Haskell's source model, the rupture size can be estimated from the coherence decay rate. We apply this method to USArray data of earthquakes in three subduction zones, the Sea of Okhotsk, South America and Japan. The source sizes inferred from the coherence decay patterns are consistent with scaling relations intermediate between width‐saturated L‐models and quasi equi‐dimensional rupture models. Our observation captures a unique pattern of array waveform coherence and demonstrates the potential of utilizing waveform coherence to study earthquake source parameters. Plain Language Summary: In this paper, we observe that for a given earthquake, the similarity of the waveform (coherence) recorded by stations in a far‐field array decays with increasing interstation distance. The waveform coherence generally falls off with interstation distance faster for earthquakes of larger magnitudes and therefore, larger rupture sizes. We develop a novel method using array waveform coherence to estimate the earthquake rupture size, and apply this method to USArray data of earthquakes in three geological regions: the Sea of Okhotsk, South America and Japan. The source sizes inferred from the coherence decay patterns are consistent with previous studies using different methods. According to our observation, there is a potential to infer earthquake rupture independently from far‐field observations by waveform coherence. Key Points: Waveform coherence decays as a function of interstation distance faster for large earthquakes (Mw > 7)The waveform coherence pattern is governed by earthquake source sizeRupture sizes inferred from waveform coherence satisfy empirical scaling relations [ABSTRACT FROM AUTHOR]

Since the appearance and evolution of earthquake ionospheric precursors are expected to show a nonlinear and complex behaviour, the use of nonlinear predictor models seems more appropriate. This paper proposes a new approach based on deep learning as a powerful tool for extracting the nonlinear patterns from a time series of ionospheric precursors. A Long Short-Term Memory (LSTM) network as a type of Recurrent Neural Network (RNN) was used to investigate 52 six-month time series, deduced from the three Swarm satellite (Alpha (A), Bravo (B) and Charlie (C)) measurements, including electron density (Ne), electron temperature (Te), magnetic scalar and vector (X, Y, Z) components, Slant and Vertical Total Electron Content (STEC and VTEC), for day and night periods around the time and location of a seismic event. This new approach was tested on a strong Mw = 7.1 earthquake in Japan on 13 February 2021, at 14:07:50 UTC by comparing the results with two implemented methods, i.e., Median and LSTM methods. Furthermore, clear anomalies are seen by a voting classification method 1, 6, 8, 13, 31 and 32 days before the earthquake. A comparison with atmospheric data investigation is further provided, supporting the lithosphere–atmosphere–ionosphere coupling (LAIC) mechanism as a suitable theory to explain the alteration of upper geolayers in the earthquake preparation phase. In other words, using multi-method and multi-precursor analysis applied to 52 time series and also to the orbit-by-orbit investigation, the observed anomalies on the previous day and up to 32 days before the event in normal solar and quiet geomagnetic conditions could be considered as a striking hint of the forthcoming Japan earthquake. [ABSTRACT FROM AUTHOR]

Background. The significance of mutual-help in communities for disaster management is a fundamental important concept. However, the current societal state does not reflect this lesson. S&G (Simulation and Gaming) has the potential to overcome the challenges faced in promoting community-based disaster management. No scientific research is currently present that reviews their achievements in Japan. Aim. This paper analyzes the current achievements of S&G in enhancing community resilience against large-scale earthquakes in Japan. Method. The paper clarifies the theoretical advantages of S&G in enhancing community resilience in coping and adaptive capacity plus proposes a conceptual contribution framework of S&G in improving community resilience. Based on this framework, the paper analyzes some major games that tackle community resilience against earthquakes in Japan. Results. The paper demonstrates the achievements through the S&G spectrum that stresses the disastrous experience with specific resilience views on one side, while decision making for critical reflection from other players with more comprehensive resilience views on the other side. Conclusion. The paper showcases the current S&G achievements in enhancing community resilience against large-scale earthquakes in Japan using the proposed framework, which can be utilized by other disaster-prone countries to develop and evaluate applications of S&G for increasing community resilience against earthquakes. [ABSTRACT FROM AUTHOR]

This paper describes an efficient approach to high-resolution time-reversal source imaging simulation. Dense seismograph network records are backpropagated from stations to the hypocentre through a 3-D subsurface structure model to estimate the initial source wavefield at the earthquake initiation time. By assimilating high-density observational data into the time-reversal wave propagation, a clearer source image can be determined, even for deep and distant earthquakes, than is achievable with conventional source imaging. The effectiveness of data-assimilation-based source imaging by a time-reversal wave propagation simulation with a 3-D heterogeneous structural model was demonstrated using recordings from a nationwide strong-motion seismograph network during the 2007 Off Niigata, Japan, M w 6.6 earthquake, and the 2007 Off Ibaraki, Japan, M w 6.8 earthquake. Such data-assimilated-based simulations are also effective for early forecasting of strong ground motions caused by large earthquakes through fast time-advancing simulations based on the current assimilated wavefield. We will discuss the feasibility of a disaster prevention system for the early forecasting of strong motion disasters due to large earthquakes, based on repeatedly estimating source parameters and forecasting strong motions in future time based on the current assimilated wavefields. [ABSTRACT FROM AUTHOR]

This research aims to explore detailed spatial distribution characteristics, identify key factors weight, and establish an accurate susceptibility regionalization model of coseismic landslides by the Mw 6.6 Iburi, Japan, earthquake sequence of 6 September 2018. Based on the remote sensing interpretation database, 5,977 individual coseismic landslides were delineated, which occupies an area of about 15.26 km2. The relationship between eight key factors and spatial distribution of coseismic landslides were precisely analyzed by the landslide area density (LAD) and landslide point density (LPD) curves. In order to obtain the weight of eight key factors more accurately, this paper compares the similarities and differences of the two curves in the earthquakes with similar magnitude, which was included the Lushan and Jiuzhaigou earthquake in China. According to the weight of eight key factors, the improved weight of evidence method was used to produce the susceptibility regionalization map of coseismic landslides in the Iburi earthquake. The results show that the improved weight of evidence method has better precision and can provide a scientific coseismic landslides susceptibility regionalization map for disaster prevention and mitigation in the Iburi earthquake. [ABSTRACT FROM AUTHOR]

This analysis is an extension of the studies based on the space–time–magnitude domain nearest-neighborhood distances (ƞ) obtained from two successive earthquakes. We included epicentral depth as a parameter, and established a new analytical solution for seismicity clustering in the space–time–depth–magnitude domain. The proposed technique was applied to SW Japan seismic observation data for 2011–2018, and revealed that the temporal, spatial, and epicentral (T, R, E) components of the joint distribution for ƞ were prominently bimodal, indicating the presence of two, statistically distinct, earthquake populations. We used the Lomb–Scargle periodogram (LSP) to generate a power spectrum preceding the Kumamoto earthquake, and detected the periodic component of unequally spaced points for log10ƞ (logarithmic scale of ƞ). The LSP showed a dominant peak corresponding to the time period between foreshocks and aftershocks, due to the highest number of recorded ƞ observations. The technique presented in this paper can be applied globally for any time period and any seismotectonic zone preceding large earthquakes of interest. [ABSTRACT FROM AUTHOR]

The literature often reports space–time relations between the abnormal variations of different kinds of nonseismological (i.e., geophysical, geochemical, and atmospheric) parameters and the occurrence of earthquakes. The integration of such observations with seismological ones could improve the quality of the seismic hazard assessment in the medium‐short term (months to days). Each considered parameter has, in principle, its capabilities to provide useful (and utilizable) information about seismic processes. Therefore, to define a system based on different observations, the first step is to estimate the informative contribution that each considered parameter could provide. In this paper, we will evaluate the potential of Significant Sequence of Thermal Anomalies (SSTAs). In particular, we adopted the broadly used Robust Satellite Techniques (RST) data analysis methodology to identify SSTAs over 11 years (June 2005 to December 2015) of nighttime satellite images acquired by MTSAT satellites over Japan. Aiming at reducing the false‐positive rate, we introduced and tested an innovative configuration of the RST, which is here presented. We executed a correlation analysis between SSTAs and Japanese earthquakes with MJMA ≥ 6 by applying suitable constraints concerning space, time, and magnitude. The analysis highlights (a) the occurrence of just 29 SSTAs in the 11‐year period of observation, (b) 18 SSTAs (i.e., 62%) occur in an apparent space–time relation to earthquakes, and (c) 13 of them occur before the quake. Results of the random test analysis, based on error diagrams, confirm a noncasual correlation between "RST‐based satellite thermal anomalies" and earthquake occurrences. In particular, for MJMA ≥ 6.5 earthquakes, probability gain is up to better than 4.3 as compared with the random guess. Key Points: We present an innovative version of the Robust Satellite Techniques able to reduce the proliferation of false‐positive thermal anomaliesA noncasual relation between satellite thermal anomalies and MJMA ≥ 6 earthquakes affecting Japan in the time span 2005–2015 was foundMultiparametric approach could accelerate the set‐up of a system for time‐dependent assessment of seismic hazard [ABSTRACT FROM AUTHOR]

The Tōhoku Pacific Coast earthquake on 11 March 2011 severely disrupted transport networks, suddenly jeopardising a large part of Japan, and prompting authorities to take fast action. Refugees and inhabitants of the affected areas were forced to adapt their transport needs. This unprecedented situation laid bare the need for a more resilient Japanese transportation infrastructure in order to significantly improve physical and social reconstruction capacity during an emergency situation. This paper analyses the damage and impact of the disaster on transport and its energy infrastructure, reviews the measures adopted, and assesses past and acquired resilience. [ABSTRACT FROM AUTHOR]

A new risk-based tsunami early warning method is developed using Random Forest (RF) with an extensive tsunami monitoring network (S-net) deployed off the Northeastern region of Japan. To consider a wide range of possible tsunami waves that may occur in the future, the RF model is developed using simulated 4000 tsunami wave time series at the S-net sensors. The response variable is the total aggregate loss of buildings caused by the tsunami, and the explanatory variables include earthquake information (magnitude, epicenter latitude, and epicenter longitude) and tsunami wave amplitudes at the S-net sensors. Unlike the conventional tsunami early warning method for predicting the tsunami wave amplitude along the shoreline, the response variable adopted in this study is a tsunami risk metric that reflects the tsunami impact to people and assets in coastal areas. The RF model is suitable for predicting highly nonlinear and scattered tsunami loss due to its characteristics of nonparametric regression and ensemble learning. The result indicates that compared with conventional linear regression-based algorithms, RF predicts the tsunami loss significantly better, reducing the mean square error by 90%. Furthermore, RF does not rely heavily on earthquake information, making it useful for announcing early warning for tsunamis generated by other sources. • A new risk-based tsunami early warning algorithm is developed. • A random forest method is particularly suitable for forecasting highly nonlinear tsunami loss. • The random forest method outperforms a conventional method of multiple linear regression method. • A case study application considers an extensive ocean bottom sensor network in northeastern Japan (S-net). • The dataset and the MATLAB code are included in the paper. [ABSTRACT FROM AUTHOR]

Coseismic and postseismic crustal deformations caused by earthquake episodes are important in understanding the mechanisms of these episodes as well as the fault rheology near an epicentral area. Specifically, interferometric synthetic aperture radar (InSAR) and synthetic aperture radar (SAR) pixel tracking can depict high‐resolution crustal deformation fields associated with earthquakes and volcanic activities without installing on‐site observation instruments. In this study, we investigate the coseismic and postseismic near‐fault crustal deformations associated with the 2016 Kumamoto earthquake sequence in southwest Japan using ALOS‐2/PALSAR‐2 (Phased Array‐type L‐band SAR‐2) data. Coseismic three‐dimensional (3‐D) displacement fields inferred from PALSAR‐2 pixel tracking data showed 1.6 m of horizontal displacements and 2 m of subsidence at maximum, despite the mainshock focal mechanism that was dominated by strike‐slip components with N‐S extension axes. The locations of large displacement variations along surface ruptures due to the mainshock were almost identical to a region where infrastructure was damaged, thus implying the generation of strong ground seismic waves. By using conventional InSAR stacking, we inferred two independent quasi‐east‐west and quasi‐vertical displacement fields as cumulative postseismic deformations following the mainshock over a period of about 2 years. The near‐fault postseismic deformation represented complicated displacement characteristics that could not be explained by a single physical process. Deformation signals around Aso volcano were interpreted by the effects of postseismic physical processes as well as geological heterogeneous structures. Plain Language Summary: Coseismic and postseismic crustal deformation fields provide information for inferring slip distributions occurring along a fault, and these data are helpful for understanding the geological characteristics around an epicentral area. By using satellite synthetic aperture radar (SAR) images, we can derive crustal deformation maps with high spatial resolutions and high measurement accuracy without installing on‐site observation instruments. In this paper, we offer coseismic and postseismic crustal deformation maps associated with the 2016 Kumamoto earthquake sequence on Kyushu Island, SW Japan, which were derived using the Japanese SAR satellite ALOS‐2/PALSAR‐2 data. Measurements of displacements along with details on Earth surface ruptures due to earthquakes also allow us to understand the variations in rupture processes along seismogenic faults. Furthermore, comparisons of the spatial and temporal variations of coseismic and postseismic deformations can provide information on the geophysical mechanisms of long‐term deformations following a mainshock. Key Points: PALSAR‐2 pixel tracking and InSAR revealed near‐fault coseismic and postseismic deformations due to the 2016 Kumamoto earthquake sequenceSignificant coseismic displacement variations along the surface ruptures imply complicated fault rupture processes during the mainshockPostseismic deformations can be interpreted by multiple physical processes and geological heterogeneous structures [ABSTRACT FROM AUTHOR]

The concept of determining the dislocation Love numbers using GNSS (Global Navigation Satellite System) data and calculating the corresponding Green's functions is presented in this paper. As a case study, we derive the dislocation Love number h of vertical displacement by combining 1232 onshore GPS data and 7 GPS-Acoustic data with the 2011 Tohoku-Oki earthquake (M w 9.0). Three fault-slip distributions are used to compare and verify the theory and results. As the GPS stations are only located in Japan Island and along the Japan trench, we use the theoretical vertical displacements of a spherically layered Earth structure to constrain the low-order signal. The L-curve and an a priori preliminary reference skill are applied in the inversion method. Then, the GPS-observed vertical displacement changes are used to invert for the vertical displacement dislocation Love numbers h based on three different fault-slip models. Our results indicate that the estimated dislocation Love numbers |$h$| fluctuate significantly from the earth model (i.e. the preliminary reference earth model), especially for the |$h_{n1}^{32}$| component, and these changes in |$h_{n2}^{12}$| and |$h_{n0}^{33} - h_{n0}^{22}$| are relatively small. The vertical displacements derived from the inversion results agree well with the GPS vertical observations. The inverted dislocation Love numbers are considered to profile the regional structure which differs from the mean 1-D heterogeneous structure of the Earth, and the corresponding Green's functions of four independent dislocation sources describe a more reasonable seismic deformation field. [ABSTRACT FROM AUTHOR]

This paper examines the effects of the 2012 revisions to the damage predictions of an anticipated Nankai Trough megathrust earthquake on subsequent inter-municipality migration in Japan's coastal areas. We find that an increase in predicted tsunami height—rather than anticipated seismic movements—after the 2012 revision is associated with a subsequent reduction in net migration. While the reducing effect of tsunami predictions on in-migration persisted throughout the study period, the effect on out-migration was only temporary. Moreover, working-age people are more likely to respond to tsunami risk and avoid moving to municipalities with a high tsunami risk after the revisions. [ABSTRACT FROM AUTHOR]

The three‐dimensional (3‐D) deformation field associated with the 2016 Central Tottori earthquake is retrieved from advanced land observing satellite 2 interferometric synthetic aperture radar (InSAR) observations with four different viewing geometries, that is, ascending/descending tracks and left‐/right‐looking modes. The strain model and variance component estimation (SM, VCE, SM‐VCE) method is exploited and improved to integrate the InSAR observations with different viewing geometries so that the 3‐D deformation field is not affected by the inconsistent coverage of SAR footprints or the gross errors in InSAR observations. The obtained results are consistent with GNSS observations, indicating that the improved SM‐VCE method, known as SM‐RVCE in this paper, is capable of retrieving an accurate and spatially complete 3‐D deformation field for this earthquake. In addition, the precision of the InSAR observations and the estimated 3‐D deformation are quantitatively assessed by the SM‐RVCE method. Finally, on the basis of the estimated 3‐D coseismic deformation, the source parameters of this event are inverted, revealing an asperity with a maximum strike‐parallel slip of ~1.1 m concentrated at depths between 2 and 10 km. The estimated seismic moment is 2.4 × 1018 Nm, which corresponds to a Mw 6.2 event. Key Points: We retrieve the 3‐D deformation field of the 2016 Central Tottori earthquake from left‐ and right‐looking InSAR observationsWe conduct a precision assessment for InSAR observations based on the variance component estimation (VCE) methodWe employ the robust VCE method to mitigate the effects of gross InSAR errors such as unwrapping errors on the 3‐D deformation [ABSTRACT FROM AUTHOR]

The 2016 Kumamoto earthquake first occurred on April 14, 2016 with magnitude 6.5 in Kumamoto, Japan as a foreshock. Subsequently, after 28 h, an even larger earthquake occurred with magnitude 7.3 as the main shock on April 16, 2016. These earthquakes were caused by two active faults: the Futagawa and Hinagu faults. This paper proposes a landslide susceptibility calculation method that considers the geomaterial strength reduction from peak to residual state and ground motion directivity. Although there is a lack of information regarding the strength parameters of geomaterials in the slopes, a parametric analysis with various strength parameters of friction angle and cohesion was carried out. To simulate the actual landslides triggered by the 2016 Kumamoto earthquake, the best combination of friction angle and cohesion in each lithology was optimized by a proposed weighted prediction rate. Based on the calculated permanent seismic displacement, a landslide susceptibility map was produced to show the degree of susceptibility over a wide area comprising 100 km2. The proposed regional landslide susceptibility map will be valuable for estimating the locations of possible slope failures and the extent of damage, as well as for planning field reconnaissance and preventing secondary disasters immediately after earthquakes. [ABSTRACT FROM AUTHOR]

The objective of this paper is to reveal the reasons why the traditional buildings and cities have been able to survive the impacts of disasters in the long run that resulted in their heritage status. The study explains the new and old viewpoints on the cases of Japan with relation to the design of heritage buildings and historic cities that are sophisticated with traditional patterns, limited materials, and technologies of past, which is a kind of survival design for mitigation of unavoidable disasters. Recently, “disaster mitigation” has been looked upon to ward-off the unavoidable disasters within minimum damage as compared to “disaster prevention.” Aiming at zeroing the damage, even the latest modern technology cannot completely undo the damages caused by the disasters, such as Kobe Earthquake in 1995 and 311 Tsunami in 2011. The present cultural heritages are associated with traditional wisdom, resulting in its survival from many disasters. This paper introduces the traditional Japanese towns and architectural buildings from the viewpoint of their resistance to disasters and sheds light on the “survival designs” that employ limited materials and available technologies. As per the context, the targeted natural disasters are divided into four parts, i.e., earthquake, city fire, flood, and others, including tsunami and windstorm. Aiming at these disasters and the risk they pose, a strong traditional knowledge base has to be gathered leading to the adoption of the disaster-mitigation methods in the modern architectural designs and further passing them on to the future generations. [ABSTRACT FROM AUTHOR]

Sliding of natural and artificial slopes generally occurs during or following strong earthquakes. Such sliding is greatly affected by a combination of geological conditions and earthquake loading. Earthquake-induced landslides often cause more damage to infrastructure and human lives than the earthquake itself. Pseudo-static analysis is widely implemented as one of several design methods used in engineering practice to assess the seismic stability of natural and artificial slopes. However, the most important issue of pseudo-static analysis is to select the most appropriate method for measuring seismic coefficient. In order to investigate this, back analysis was conducted for surficial slides subjected to strong ground motion during the 2004 Mid-Niigata prefecture earthquake in Japan. This paper surveyed the stochastic properties of earthquake-induced surficial slides and clearly showed that the obtained results were applicable to back analysis of shear strength and seismic coefficient. In back analysis, soil properties such as soil strength and density and sliding depth were assumed as random variables owing to their uncertainties. Seismic coefficient is also assumed to be a random variable and varies with distance from the epicenter fault line. The analysis of 4504 recorded surficial slides clearly shows a unique relationship of landslide occurrence ratio with slope angle and distance from the epicenter fault line. This study’s results enhance the calculation of the shear strength of weathered soil covering slopes and the horizontal seismic coefficient through back analysis procedure. By considering possible stochastic properties of variables, some case studies were implemented in the back analysis. [ABSTRACT FROM AUTHOR]

The paper analyzes the data of manual ionograms processing of hourly measurements of the critical frequency foF2 of the F2 ionospheric layer at the Wakkanai ionospheric vertical sounding station (Japan) in a geomagnetically quiet environment before a series of earthquakes with magnitude M > 6.0, for which the station entered the earthquake preparation zone, in order to detect possible Ionospheric Disturbances Preceding Earthquakes (IDPE), and to determine their quantitative characteristics. Detected IDPE, in the opinion of the authors, can be related to the processes of preparation of the corresponding earthquakes, i.e., to be Ionospheric Precursors of Earthquakes (IPE). [ABSTRACT FROM AUTHOR]

In this paper, we deal with evacuation decision making of people in the disaster area. By threshold model, we discuss whether all agents decide to evacuate or not. It is reported that not all people in the affected area evacuated during the Great East Japan Earthquake. But, many evacuation simulations treat that all people evacuate. In the previous work, on the assumption that all people decide to evacuate, we dealt with the needed time to make all people evacuate if psychological conditions exist at the time of disaster. In this paper, we deal with the condition that not all people decide to evacuate and focus on contagion of evacuation decision making on real map. We found that for contagion of evacuation decision making, local neighborhood and connection of sub network is necessary. [ABSTRACT FROM AUTHOR]

• Curie point depth analysis by magnetic data reveals thermal structure of the Japanese islands. • The map of Curie depth was upgraded from the previous hand-writing map to a digital map. • Drillhole data provides local temperature data, while the map of Curie depth provides regional thermal structure. • It may be possible to estimate heat sources by combining Curie depths, drillhole data, and seismic data. This paper shows results of Curie point depth (CPD) analysis of the Japanese Islands using magnetic data. The analysis method is Bouligand et al. (2009) based on fractal theory. This analysis result was combined with the cutoff depth of ordinary earthquakes, low frequency earthquakes and drillhole data. CPD by magnetic data (Dcmag) performed in the case of 50 km window size ranges 6–9 km deep in volcanic areas and is deeper than 9 km in non-volcanic areas. The results are concordant with the previous study by Okubo et al. (1989). Cutoff depths calculated by JMA unified catalog are 10 km or shallower in the volcanic area, deeper than 20 km in the forearc side and concordant with Dcmags. Dcmags across the Kakkonda GP gradually become shallower from 6.8 km west Akita-Komagatake toward to 4.6 km near Iwate volcano. The depth-to-temperature curves from drillhole database around the Kakkonda GP show that thermal gradients between Iwate volcano and the Kakkonda GP range 0.157 - 0.222 K/m. Assuming that these thermal gradients continue from the bottom of hole to the deeper part, the depths reaching 580 °C (Dchole) are determined. Dchole is concordant with Dcmag in the west side of the Kakkonda GP and much shallower than Dcmag in the east side. This suggests that Dcmags may miss to delineate a local high temperature area smaller than 50 km square in the east because of the average effect of CPD analysis. Dchole is shallower than 3 km west Iwate volcano and deepens at about 5 km west the Kakkonda GP. Combining the low frequency earthquakes data from the JMA unified earthquake catalog and the drillhole data of the Kakkonda geothermal field, we find the Curie point depths are consistent with those data. [ABSTRACT FROM AUTHOR]

Recent geodetic measurements have detected recurrent slow slip events (SSEs) in many subduction zones. Numerical simulations suggest that the recurrence intervals and magnitudes of such SSEs decrease in the later stage of the interseismic period. Therefore, activities of SSEs and their temporal variations in recurrence intervals and magnitudes provide important clues for evaluating future large earthquakes. However, our knowledge of recurrent SSEs before the establishment of dense observation networks is limited. Here, we report a possible SSE in 1973 beneath the Kii peninsula along the Nankai subduction zone, southwest Japan, where magnitude 8 class earthquakes such as the 1944 Tonankai and 1946 Nankai earthquakes repeatedly occur. The possible SSE was detected by a horizontal pendulum tiltmeter installed in 1947 at the Kishu observatory. We recovered and converted the original tilt records from 1969 to 1974 drawn on bromide (light sensitive) papers to digital tilt records. In late-November 1973, there was a slow transient signal down to the northeast of about 1.4 μrad, lasting about 1–3 days. Assuming this crustal deformation was due to an SSE, we searched for a possible fault model by adopting the already-known SSE models occurring from 1996 to 2012 as template models. Among the 42 template fault models, five models were able to qualitatively explain the direction of the observed tilt change. The centroids of these fault models were located about 30–60 km to the west of the observatory. In the source region, two magnitude 5 class earthquakes occurred before the initiation of the transient signal, and thus may be related to the occurrence of the possible SSE. In contrast, the magnitude of the calculated tilt change was about 1–2 order smaller than that of the observed tilt change. This discrepancy could be partly explained by a slip amount larger than that in the template models, which suggests that the possible SSE in 1973 was larger than those detected by recent observations. Further investigation of historical data on crustal deformation will reveal more about the temporal change in the recurrence intervals and magnitudes of SSEs during earthquake cycles of large earthquakes. [ABSTRACT FROM AUTHOR]

Many buildings in Japan currently have a base-isolation system with a low stiffness that is designed to shift the natural frequency of the building below the frequencies of the ground motion due to earthquakes. However, the ground motion observed during the 2011 Tohoku earthquake contained strong long-period waves that lasted for a record length of 3 min. To provide a novel and better solution against the long-period waves while maintaining the performance of the standard isolation range, the exploitation of the characteristics of nonlinear damping is proposed in this paper. This is motivated by previous studies of the authors, which have demonstrated that nonlinear damping can achieve desired performance over both low and high frequency regions and the optimal nonlinear damping force can be realized by closed loop controlled semi-active dampers. Simulation results have shown strong vibration isolation performance on a building model with identified parameters and have indicated that nonlinear damping can achieve low acceleration transmissibilities round the structural natural frequency as well as the higher ground motion frequencies that have been frequently observed during most earthquakes in Japan. In addition, physical building model based laboratory experiments are also conducted, The results demonstrate the advantages of the proposed nonlinear damping technologies over both traditional linear damping and more advanced Linear-Quadratic Gaussian (LQG) feedback control which have been used in practice to address building isolation system design and implementation problems. In comparison with the tuned-mass damper and other active control methods, the proposed solution offers a more pragmatic, low-cost, robust and effective alternative that can be readily installed into the base-isolation system of most buildings. [ABSTRACT FROM AUTHOR]

The devastating Japan earthquake (magnitude 9.0) and tsunami (39-metre high) of 2011, also called the Great Tohoku or Sendai earthquake, was a record-breaker natural disaster causing enormous damage and a nuclear meltdown at Fukushima nuclear power plant. This paper attempts to analyse the long and short run effects of this record-breaking natural disaster on the Japanese equity, debt and FX markets as well as Gold as one of the most popular metals and investment options, using daily data. A variance bound test proposed by Fakhry & Richter (2018) underpinned by the C-GARCH-t model of volatility is adopted. The results seem to indicate that the natural disaster influenced the efficiency of the market in the immediate terms more than the long term. In a global financial market where the key is competitiveness, it is essential to analyse the efficiency and therefore stability of the Japanese financial market. Therefore, analysing the impact of the natural disaster on the competitiveness of the Japanese financial market. [ABSTRACT FROM AUTHOR]

Earthquake is a threat to all kinds of structures including underground structures. Before the 1995 Hyogoken-Nanbu Japan earthquake, however, it was considered that underground structures are at minimum seismic risk in comparison to above-ground structures unless they are crossing the active faults. The collapse of Daikai station in the Kobe subway system during the 1995 Hyogoken-Nanbu earthquake exhibited that underground structures are at high risk of earthquake with shallow overburden. Though researches have been done on this issue, it is still necessary to investigate further the mechanical behavior of underground structure during an earthquake and corresponding efficient seismic enhancement. In this paper, in order to find out an optimum ground-improvement pattern for a rectangular-shaped box culvert constructed in soft ground that does not meet the present seismic requirement, numerical tests with nonlinear 2D/3D dynamic FEM are conducted. Different patterns of the ground improvement for the box curvet constructed with cut-and-cover method are investigated to find out an optimum pattern that can reduce the impact of earthquake in the most effective way. In the 2D/3D dynamic finite element analysis, the ground is Toyoura sand, typical clean sand, and its nonlinear mechanical behavior is described by Cyclic Mobility model. Validity of the proposed numerical method is firstly confirmed with 1 g shaking table test and then numerical tests are conducted to find out the optimum pattern for the ground improvement. Finally, an effective pattern of ground improvement for existing box culvert is proposed by the numerical analysis. [ABSTRACT FROM AUTHOR]

On October 21, 2016, an earthquake with Japan Meteorological Agency (JMA) magnitude 6.6 hit the central part of Tottori Prefecture, Japan. This paper demonstrates two notable effects of the surface geology on strong ground motions due to the earthquake. One is a predominant period issue observed over a large area. A seismic intensity of 6 lower on the JMA scale was registered at three sites in the disaster area. However, the peak ground acceleration ranged from 0.3 to 1.4 G at the three sites because of the varying peak periods of observed strong ground motions. The spectral properties of the observations also reflect the damage around the sites. Three-component microtremors were observed in the area; the predominant ground period distributions based on horizontal to vertical spectral ratios were provided by the authors. The peak periods of the strong motion records agree well with predominant periods estimated from microtremor observations at a rather hard site; however, the predominant periods of the microtremors are slightly shorter than those of the main shock at the other two soft sites. We checked the nonlinear effect at the sites by comparing the site responses to small events and the main shock. The peak periods of the main shock were longer than those of the weak motions at the sites. This phenomenon indicates a nonlinear site effect due to large ground motions caused by the main shock. A horizontal component of the accelerogram showed rather pulsating swings that indicate cyclic mobility behavior, especially at a site close to a pond shore; ground subsidence of ~20 cm was observed around the site. The peak periods of weak motions agree well with those of the microtremor observations. This implies an important issue that the predominant periods estimated by microtremors are not sufficient to estimate the effect of surface geology for disaster mitigation. We have to estimate the predominant periods under large ground motions considering the nonlinear site response of soft sediment sites. [ABSTRACT FROM AUTHOR]

Due to the complexity of earthquakes, predicting their magnitude, timing and location is a challenging task because earthquakes do not show a specific pattern, which can lead to inaccurate predictions. But, using Artificial Intelligence-based models, they have been able to provide promising results. However, few mature studies are dealing with large earthquake prediction, especially as a regression problem. For these reasons, this paper investigates an attention-based LSTM network for predicting the time, magnitude, and location of an impending large earthquake. LSTMs are used to learn temporal relationships, and the attention mechanism extracts important patterns and information from input features. The Japan earthquake dataset from 1900 to October 2021 was used because it represents a highly seismically active region known for its large earthquakes. The results are examined using the metrics of MSE, RMSE, MAE, R-squared, and accuracy. The performance results of our proposed model are significantly better compared to other empirical scenarios and a selected baseline method, where we found that the MSE of our model is better by approximately 60%. • An attention-based LSTM network for earthquake prediction. • Clustering seismic regions for location prediction. • Time, magnitude, and location of earthquakes of magnitude >6 are predicted. • Two different seismic regions are studied: Japan and the northern Red Sea. • Discussion and comparison of results. [ABSTRACT FROM AUTHOR]

This paper discusses the emergent interest in risk communication as a strategy for disaster risk reduction. Communication plays an essential role in understanding risk, but studies suggest that people often do not respond in the way that risk experts anticipate. For risk communication to be effective, vulnerable communities need to understand risk within the local context as well as in terms of sustainability. Risk messages offer communities a way to enhance their collective knowledge of existing vulnerabilities, leading them towards alternative solutions for action. A longitudinal study of the Mano community development approach and its recovery from the 1995 Kobe earthquake illustrates how risk communication dynamics contributed to the community’s sustainable risk reduction. The study concludes that risk communication is a collaborative way for a community to work with risk experts, own their risk information, influence existing policies and practices, develop solutions to reduce vulnerability, and ultimately enhance a community’s capacity for managing future risk. [ABSTRACT FROM PUBLISHER]

This paper analyzes the cost and efficiency of waste disposal associated with the Great East Japan Earthquake. The following two analyses were performed: (1) a popular parametric approach, which is an ordinary least squares (OLS) method to estimate the factors that affect the disposal costs; (2) a non-parametric approach, which is a two-stage data envelopment analysis (DEA) to analyze the efficiency of each municipality and clarify the best performance of the disaster waste management. Our results indicate that a higher recycling rate of disaster waste and a larger amount of tsunami sediments decrease the average disposal costs. Our results also indicate that area-wide management increases the average cost. In addition, the efficiency scores were observed to vary widely by municipality, and more temporary incinerators and secondary waste stocks improve the efficiency scores. However, it is likely that the radioactive contamination from the Fukushima Daiichi nuclear power station influenced the results. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of debris estimation which is one of the most important initial challenges in the wake of a disaster like the Great East Japan Earthquake and Tsunami. Reasonable estimates of the debris have to be made available to decision makers as quickly as possible. Current approaches to obtain this information are far from being optimal as they usually rely on manual interpretation of optical imagery. We have developed a novel approach for the estimation of tsunami debris pile heights and volumes for improved emergency response. The method is based on a stereo-synthetic aperture radar (stereo-SAR) approach for very high-resolution polarimetric SAR. An advanced gradient-based optical-flow estimation technique is applied for optimal image coregistration of the low-coherence non-interferometric data resulting from the illumination from opposite directions and in different polarizations. By applying model based decomposition of the coherency matrix, only the odd bounce scattering contributions are used to optimize echo time computation. The method exclusively considers the relative height differences from the top of the piles to their base to achieve a very fine resolution in height estimation. To define the base, a reference point on non-debris-covered ground surface is located adjacent to the debris pile targets by exploiting the polarimetric scattering information. The proposed technique is validated using in situ data of real tsunami debris taken on a temporary debris management site in the tsunami affected area near Sendai city, Japan. The estimated height error is smaller than 0.6 m RMSE. The good quality of derived pile heights allows for a voxel-based estimation of debris volumes with a RMSE of 1099 m 3 . Advantages of the proposed method are fast computation time, and robust height and volume estimation of debris piles without the need for pre-event data or auxiliary information like DEM, topographic maps or GCPs. [ABSTRACT FROM AUTHOR]

Japan is periodically wracked by "Great Earthquakes" (daijishin) - seismic events so destructive that they leave massive amounts of textual and graphic evidence, much of it produced by people who did not experience the events directly. Using this cache of information, it is possible to see how the idea of the "disaster victim" has changed over time and circumstance. My paper traces this role across five Great Earthquakes that spanned roughly 150 years (1855-2011), a period convergent with modern Japan. I will argue that the sense of who and what has been victimized by the shaking of the earth - who has suffered, what weight to attach to their loss, what actions to take and emotions to feel regarding their situation - has changed regularly, and surprisingly, over this rather short period. There is, in other words, no common Japanese experience of victimhood, even in the context of one disaster type over a relatively short historical period. The article is one contribution to an as-yet unexamined history and comparative study of the modern role of disaster victim. [ABSTRACT FROM AUTHOR]

Questions of continuity and transmission, as well as relationship to the community, have long occupied an important part of folk performance scholarship. These topics take on a different urgency in disaster-affected communities, where preexisting socioeconomic issues become more pressing and endanger not only the continuity of folk practices but the communities themselves. The aftermath of the 2011 Great East Japan Earthquake and tsunami has seen a surge of folk performance revivals in affected areas, hinting to the depth of the ties between local folk performance and community. Following an ethnographic approach, this paper explores the case of the community of Ogatsu (Ishinomaki City, Miyagi Prefecture) and its folk performance, the Ogatsu hōin kagura, as one expression of the revival process in an isolated, rural community extensively affected by the 2011 disaster. Putting in perspective the underlying dynamic of continuity and change that characterizes folk performances, the objective is to explore the nature and usage of the kagura and its relationship to the post-disaster community as it responds to changing circumstances. [ABSTRACT FROM AUTHOR]

Purpose – Attempting to explore the role of direct experience in influencing disaster consciousness and public opinion, the purpose of this paper is to carry out comparative analyses of Japanese people’s knowledge, risk perception, and policy preference about large-scale earthquake disaster before and after the Great East Japan Earthquake. More importantly, aiming to provide implications regarding the application of past experience, the predictive power of direct experience on disaster consciousness is also examined. Design/methodology/approach – This study analyzed parts of the data collected from two nationwide public opinion surveys among Japanese conducted by the Japanese Government. Analyses of variance were performed to examine changes in disaster consciousness. A path model was developed to examine the predicted effects of direct experience. χ2 tests were performed to examine changes in strategy preference. Findings – This study found significant changes in Japanese people’s knowledge of natural hazards and perception of mega disaster risk. Tests of the path model suggested significant positive effect of societal level impact on disaster consciousness and strong predictive power of knowledge on risk perception. Significant changes in strategy preference were also found. Practical implications – Results supported the predictive power of direct experience, highlighting the significance of recalling past experience as well as creating indirect experience to raise public consciousness and motivate appropriate actions. Originality/value – This is one of the few studies that investigate changes in public opinion among Japanese before and after the Great East Japan Earthquake. [ABSTRACT FROM AUTHOR]

Topography results from the interplay between rock uplift and erosion, and studying river responses to active tectonics may enable the rates and spatial distribution of rock uplift to be inferred. Normalized channel steepness index (k sn) is widely used to infer rock uplift rates, and rock erodibility plays a significant role in determining the variation of channel steepness in response to external forces. Various measures may be applied to evaluate rock erodibility; however, since they are essentially qualitative, it is difficult to quantify relationships between rock mass strength and channel forms. In this study, we inferred long-term rock uplift rates along the Futagawa fault, an active normal-dextral fault, and the Idenokuchi fault, an active normal fault, in southwestern Japan, based on morphological characteristics of rivers across substrates with contrasting erodibility. The widely used detachment-limited model predicts that, when the rock uplift rate is spatially uniform, the ratio of erodibility of different rock types can be written by an inverse ratio of their k sn values. We employed this theoretical prediction to quantitatively calibrate the effects of rock mass strength on channel steepness. Within the study area, channel steepness was larger in the eastern part where volcanic rocks were exposed than in the western part where less resistant sedimentary rocks predominated. We calculated ratios of substrate erodibility using drainage basins close to the Futagawa fault that experienced similar rock uplift. Calibrated k sn exhibited a clear difference between the eastern and the western part of the fault, suggesting that contrasting erodibility alone cannot explain the observed channel steepness. We also confirmed that the observed channel steepness could not be explained without differential rock uplift, even when considering the combined effects of channel width, precipitation, and erosion process. The distribution of long-term rock uplift rates inferred from calibrated k sn and vertical slip rates of the fault compiled from published papers agree with the distribution of vertical displacement of the earthquake that occurred on the fault in 2016, suggesting that earthquakes similar to the 2016 event have occurred repeatedly in the study area. • We calibrated channel steepness based on the erodibility of substrate materials. • Spatial distribution of long-term uplift is inferred from bedrock river morphology. • Long-term uplift is similar to the vertical displacement of the 2016 earthquake. [ABSTRACT FROM AUTHOR]

In this paper, we propose a location-dependent earthquake prediction based on recurrent neural network algorithms. The location-dependent prediction consists of clustering the seismic dataset based on its geographical parameters (longitude and latitude) using the K-Means algorithm. In addition, we divide each cluster into two specific subsets. The first set consists of events with an average magnitude between 2 and 5, and the second set contains seismic events with magnitudes >5. Clustering allows our models to focus on each region independently. Associated with splitting methods, it helps them to learn the specific trends of each cluster with accurate performance. Moreover, in our work, the large earthquakes with few events are trained independently and remain unaffected by the other dominant events. We implement our models using the powerful recurrent neural network algorithms: Long Short Memory (LSTM), Gated Recurrent Network (GRU), and their hybrid model (LSTM-GRU). They are tested using data related to three different regions: Morocco, Japan, and Turkey. We evaluate the performance according to three metrics: mean absolute error, mean squared error, and root-mean-square error. Compared to other works in the literature, our models generally perform well, especially in predicting large earthquakes. - A location-dependent prediction using a geographic clustering by K-means algorithm. - Earthquake prediction using recurrent neural network algorithms: LSTM and GRU. - Three different seismic regions are studied: Japan, Turkey, and Morocco. - Discussion and comparison of results. [ABSTRACT FROM AUTHOR]

This paper is based on my ongoing research that was inspired by Japan's recent catastrophes. Now that the 2011 disasters have added another dimension to Japanese society, it is essential to rethink Japan as an earthquake nation and to pay close attention to the effect of earthquakes on various aspects of Japanese culture and society. I explore modern Japanese culture in terms of its relation to earthquakes and discuss the formation of earthquake nationalism through an examination of the history of earthquakes, myths, and legends, as well as media and literary representations of earthquakes. I also discuss nuclear issues in relation to the Fukushima nuclear meltdown accident. Postwar Japan's nuclear development involves not only its international politics but also center-periphery power dynamics between Tokyo and the local host towns of nuclear power plants in which I see the friction (or literally, the "power" struggle) between Japan's earthquake nationalism and the formation of a nuclear empire. The purpose of this paper is to offer a new aspect of modern Japan's cultural formation and to introduce a new dimension of Japanese cultural studies. [ABSTRACT FROM AUTHOR]

Purpose |!|#8211; The purpose of this paper is to provide a method to examine the differences in behaviour during a post-quake period. Design/methodology/approach |!|#8211; Fieldwork and questionnaires were used to collect the households|!|#39; members|!|#39; movement behaviours after the 2004 Chuetsu Earthquake. In total, three study areas were selected in Kawaguchi town (Niigata Prefecture) in order to enhance how the visualisation process can provide support in better understanding the behaviour during evacuation and recovery process. For this purpose the Space-Time-Cube (STC) was used to represent and analyse residents|!|#39; movement paths over time. Findings |!|#8211; Differences appear in the spatio-temporal paths of the three study areas, implying a connection between the geographical location and movement patterns. The city centre shows disorganized Spatio-Temporal-Patterns (STPs) during the first week of the recovery process, eventually becoming organized after the rescuers|!|#39; arrival. Moving towards the isolated areas of the town, a progressive STP organisation can be observed, explaining the faster response after the seismic event. Research limitations/implications |!|#8211; Spatio-temporal data are difficult and costly to collect, especially if a long period of time passes between the seismic event and the survey. Practical implications |!|#8211; The STC can be used as tool to enhance the disaster management techniques and provide support in crisis situations. Originality/value |!|#8211; The paper provides a practical approach to investigate the reactions after a seismic event and can be used in larger study areas to develop better strategies in disaster management. [ABSTRACT FROM AUTHOR]