This special issue summarizes some of the findings of the first half of our international joint research between Japan, Thailand, and Vietnam. This collaborative research is based on the framework of the e-ASIA Joint Research Program (e-ASIA JRP) and lasts for three years. Rainfall-induced landslides are a common disaster in many Asian countries. Our goal is to develop a practical method for landslide susceptibility mapping so that there are fewer landslide disasters in the future.

The e-ASIA JRP is an international joint initiative of public funding organizations in the East Asia Summit member countries. Based on the co-funding mechanism, support for the research teams is received from the funding organizations in their respective countries. Since 2019, the Japanese, Thai, and Vietnamese teams have been supported by the Japan Science and Technology Agency (JST), the National Science and Technology Development Agency of Thailand (NSTDA), and the Ministry of Science and Technology of Vietnam (MOST), respectively.

In the first half of our project, we completed the basic steps for developing the system. In this special issue, we are proud to present some of our achievements, including studies on slope failure analysis, landslide prevention works, meteorological observations, landslide monitoring, statistical or wide-area risk evaluations, mathematical models, and flash flood control. In addition to the above, we also present other valuable research achievements that related members have provided to help ensure the achievement of our goals. In total, 20 papers are published here. We believe that our comprehensive research activities will dramatically increase future landslide disaster mitigation, especially in monsoon Asia, and will strongly augment the roadmap for achieving the global Sustainable Development Goals (SDGs) as a common desire of humanity.

Numerous annual slope failures are induced by heavy rainfall during the monsoons, especially in developing countries in Asia. The authors have developed a simple method to predict rising groundwater levels in natural slopes at a relatively shallow depth based on parametric studies conducted using the finite element method. An assumption of a semi-infinite homogeneous slope was adopted in the analysis. Addtionally, the authors numerically modelled the vertical infiltration and the lateral seepage flow. Using this method implies that the finite element analysis is not mandatory in the evaluations of practical slopes. Such a simplified approach helps avoid time-consuming tasks in rigorous computations. However, a semi-infinite assumption used in the developed method may provide us with unsuitable solutions, particularly in cases where the slopes include heavily terraced topography with local small cliffs, because theoretically, the first slope failure tends to occur in steep slopes, like the edge of a rice terrace, even though they are very small cliffs. Nevertheless, these local solutions do not affect the conclusions for disaster risk reduction. Moreover, such unsuitable alternatives must be eliminated during analysis. To address this matter, the current study proposes a novel concept of specific lengths. This procedure provides a representative length within the specified length range. The averaged slope gradient is defined by focusing on the secant lines between each topographical grid, while those defined outside the specified range – for example, local cliff angles – are ignored in the slope stability calculation. Consequently, the proposed concept was confirmed to be efficient and can be applied to evaluate the terraced rice fields in Sapa, northern Vietnam. In the past, this area had experienced rainfall-induced slope failures; hence, the proposed method may be able to simulate these occurences. The proposed concept’s effectiveness when applied to terraced fields should continue to be verified through case studies conducted in areas with extensive smallterraced topography.

Helical anchors, sometimes referred to as screw anchors, screw piles, and helical piles, are a steel screw-in piling and ground anchoring system used for building deep foundations. Screw piles are manufactured using varying sizes of tubular hollow sections for the pile or anchor shaft. This paper presents an innovation of the helical anchor for horizontal drains, a form of subsurface drainage systems for slope protection. To address the adverse effect of groundwater, an expansion of the application of the helical anchor structure in civil engineering is needed, and new drainage solutions are being considered. The features of the helical anchor type for horizontal drainage equipment, analyses of some of its advantages, and conditions of application are presented. Generally, a helical anchor for horizontal drainage is convenient for installation, maintenance, or removal, and is effective for both horizontal drainage and for anchoring the revetment. It is also a typical construction in drainage works, generally performed by a cranking handle or a rotary-percussion-type drilling machine. The helical anchor pipe for horizontal drainage has many segments with joints using a cranking hand for installation and is quite effective where the installation space is narrow or there is no machine. In particular, the installation of this equipment differs significantly from other drilling methods because it can be driven into a sand layer without a hole wall.

The active landslide located in the Tavan-Hauthao, Sapa district, Laocai province, Vietnam was investigated using geophysical methods (2D Electrical Resistivity and Tomography), geotechnical investigations, and a ground survey to assess the geologic condition of the sliding block and surrounding ground. Landslide displacement was measured using 15 surface monitoring points. Numerical modeling was done to assess the behavior of an active landslide. This multi-disciplinary approach helped in interpreting landslide stratigraphy, geotechnical characteristics of the sliding groundmass, depth, and nature of the sliding plane. The surface area of the slide is approximately 1200 m². Studying this active landslide is important as it affects the road No. 152, which is an important road connecting the Sapa Ancient Rock Field. This study involved surface topographical survey, surface and sub-surface geological, and geotechnical investigations including Standard Penetration Test and Electrical Resistivity Tomography. Geologic and geotechnical data were used to characterize an active landslide block, which is composed of different soil layers underlaid by granitic rock. The surface electrical-resistivity measurements across the Sapa landslide resulted in inverted-resistivity sections with distinct resistivity contrasts that correlated well with the geology and geo-hydrology observed in boreholes.

In this study, the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS), v2.1 program, and module SLOPE/W in the Geostudio package were adopted for assessing rainfall-induced slope failure. TRIGRS was developed by the United States Geological Survey to determine the time-varying groundwater table at the regional scale under rainfall infiltration. The program employs partial differential equations represented by one-dimensional vertical flow in homogeneous materials for unsaturated conditions. With the application of a simple runoff routing scheme combined with the mass balance between rainfall, infiltration, and runoff over the study area, the distribution of the transient pore-water pressures within the entire landscape was simulated considering both the surface and subsurface flow. Additionally, compared to the traditional two-dimensional approach, the topographical conditions were also considered during the groundwater simulation. For conducting the slope stability analysis, a typical cross-section was constructed based on the site description. The predicted water-tables at the observed time of failure of the typical section were extracted and used in SLOPE/W to conduct the time-dependent modelling of rainfall-induced slope failures. In this study, the non-linear method was employed for simulating unsaturated soil shear strength, and the stability of the slope was evaluated using Bishop’s simplified method. We applied the approach to the landslide event that occurred on August 5, 2019, in Sapa district, Lao Cai province, Vietnam. The event resulted in severe damage and blocked the road for days. The predicted results on the stability of the slope as the factor of safety were compared with the actual slope failure during the event. The results showed that, by inputting accurate data, the applied approach could provide valuable evidence about the time of the slope failure.

Tinh Tuc town, Cao Bang province, Vietnam is prone to landslides due to the complexity of its climatic, geological, and geomorphological conditions. In this study, in order to produce a landslide susceptibility map, the modified analytical hierarchy process and landslide susceptibility analysis methods were used together with the layers, including: landslide inventory, slope, weathering crust, water storage, geology, land use, and distance from the road. In the study area, 98% of landslides occurred in highly or completely weathered units. Geology, land use, and water storage data layers were found to be important factors that are closely related with the occurrence of landslides. Although the weight of the “distance from the road” factor has a low value, the weight of layer “<100 m” has a high value. Therefore, the landslide susceptibility index very high is concentrated along the roads. For the validation of the predicted result, the landslide susceptibility map was compared with the landslide inventory map containing 47 landslides. The outcome shows that about 90% of these landslides fall into very high susceptibility zones.

Landslides are considered one of the most serious problems in the mountainous regions of the northern part of Vietnam due to the special topographic and geological conditions associated with the occurrence of tropical storms, steep slopes on hillsides, and human activities. This study initially identified areas susceptible to landslides in Ta Van Commune, Sapa District, Lao Cai Region using Analytical Hierarchy Analysis. Ten triggering and conditioning parameters were analyzed: elevation, slope, aspect, lithology, valley depth, relief amplitude, distance to roads, distance to faults, land use, and precipitation. The consistency index (CI) was 0.0995, indicating that no inconsistency in the decision-making process was detected during computation. The consistency ratio (CR) was computed for all factors and their classes were less than 0.1. The landslide susceptibility index (LSI) was computed and reclassified into five categories: very low, low, moderate, high, and very high. Approximately 9.9% of the whole area would be prone to landslide occurrence when the LSI value indicated at very high and high landslide susceptibility. The area under curve (AUC) of 0.75 illustrated that the used model provided good results for landslide susceptibility mapping in the study area. The results revealed that the predicted susceptibility levels were in good agreement with past landslides. The output also illustrated a gradual decrease in the density of landslide from the very high to the very low susceptible regions, which showed a considerable separation in the density values. Among the five classes, the highest landslide density of 0.01274 belonged to the very high susceptibility zone, followed by 0.00272 for the high susceptibility zone. The landslide susceptibility map presented in this paper would help local authorities adequately plan their landslide management process, especially in the very high and high susceptible zones.

Since 2017, there have been recurring landslides in the red mud basins of the Nhan Co alumina factory, Dak Nong Province, Vietnam, during the rainy seasons. Changes in physical and mechanical soil parameters due to rain water infiltration and the formation of tension cracks have been considered as the main causes of slope instability. The soil cohesion and angle of internal friction decreased nearly thrice and twice, respectively, as the soil became saturated. An economical and environmentally friendly reinforcement using bamboo stem piles in combination with slope regrading is suitable for the site conditions. With a light slope regrading, a bamboo stem pile spacing of 5.3 m ensures that the slope factor of safety (FS) is 1.30, which satisfies the requirements specified by the national technical regulations. The results are helpful and serve as practical fundamentals for a comprehensive control of slope stability of the red mud basins in the Nhan Co alumina factory to avoid possible catastrophic destruction of the local ecology by the spreading of an extremely high pH fluid and mud from the red mud basins due to the landslides into the red mud basins.

Every year, especially in the rainy season, landslides occur quite often in Lao Cai – a northern mountainous province of Vietnam. Specifically, in the year 2019, several landslides were observed to occur near the Sapa Ancient Rock Field in Hau Thao commune, Sapa town, Lao Cai province. In December 2019, a landslide investigation was conducted to examine the mechanism and possible causes of the landslides. Besides that, as the landslide distribution in this area is still unclear, this study will also aim to show the landslide denseness in a 700 m × 700 m square map as well as survey results in 2019 of two main landslides in such map. According to the survey, the landslide is the main phenomenon of geomorphological development in this area, being a combination of multiple different landslides with varying sizes and dissimilar triggers. The first survey landslide is about 50 m wide and 350 m long and has still been going on in recent years, with annual horizontal displacement being around 0.8 m. Meanwhile, the second one is a typical flash-landslide caused by rainfall. Despite being quite small in scale, about 15 m × 40 m, its characteristics indicate a dangerous implication in the future. This information will be the basis for further ongoing studies.

Hau Thao Village is located in Sa Pa Prefecture, in northern Vietnam. The village contains one of the most picturesque landscapes with terraced paddy fields located in landslide topography formed on a gentle slope. However, the creation of the topography has not been sufficiently clarified. In this study, samples of soil and stone are taken from two landslide areas in Hau Thao Village for mineral composition analysis, clarifying that the sauce rock of the deposits comprising the landslide areas is made up of granitoids, forming the upper slope above the fault located in the hinterland. The landslides occurring in Hau Thao Village are caused by the remobilization of the secondary deposits transported from the upper part of the slope by debris flow.

Measuring the amount of rainfall is essential for a wide-area evaluation of the risk of landslide disaster using a real-time simulation. In Thailand, located in Monsoon Asia, point observation is conducted using a rain gauge. Interpolation calculation is crucial for obtaining the planar rainfall intensity for the wide-area analysis from scattered point observation data. In this study, to accurately calculate rainfall intensity using the inverse distance weighting (IDW) method, the parameters affecting the results are examined. Additionally, using obtained rainfall data, a simple prediction calculation of groundwater level fluctuation by Wakai et al. [1] and Ozaki et al. [2] is performed. Finally, the relationship between the rainfall intensity and the fluctuation of groundwater level will be discussed.

This study’s purpose is to analyze the degree of risk and vulnerability involved in landslide and flash flood prone community areas in Thepparat sub-district, Sichon district, Nakhon Si Thammarat province, Thailand. It also aims to analyze and understand the socio-economic impacts on the community at the household level, and assess the community’s risk and vulnerability by examining its risk perception. The risk perception was done using focus group discussions and a questionnaire survey with key stakeholders. It mainly focused on how the risk of landslides and flash floods influences the community’s risk perceptions, which was tested in two parts: at the organizational and community levels by focusing on government officials and households, respectively. A correlation matrix was used to understand the relationship of the indicators selected. The Pearson correlation result has shown that the degree of risk awareness positively correlates with the income level, education level, and controllability, signifying that the risk of landslides and flash floods influences household risk perceptions. The qualitative assessment recommends community-level preparedness as being paramount to reduce the risk for a resilient community.

The density-based spatial clustering of applications with noise (DBSCAN) algorithm is a well-known algorithm for spatial-clustering data point clouds. It can be applied to many applications, such as crack detection, rockfall detection, and glacier movement detection. Traditional DBSCAN requires two predefined parameters. Suitable values of these parameters depend upon the distribution of the input point cloud. Therefore, estimating these parameters is challenging. This paper proposed a new version of DBSCAN that can automatically customize the parameters. The proposed method consists of two processes: initial parameter estimation based on grid analysis and DBSCAN based on the divide-and-conquer (DC-DBSCAN) approach, which repeatedly performs DBSCAN on each cluster separately and recursively. To verify the proposed method, we applied it to a 3D point cloud dataset that was used to analyze rockfall events at the Puiggcercos cliff, Spain. The total number of data points used in this study was 15,567. The experimental results show that the proposed method is better than the traditional DBSCAN in terms of purity and NMI scores. The purity scores of the proposed method and the traditional DBSCAN method were 96.22% and 91.09%, respectively. The NMI scores of the proposed method and the traditional DBSCAN method are 0.78 and 0.49, respectively. Also, it can detect events that traditional DBSCAN cannot detect.

This study aims to improve the accuracy of landslide detection in satellite images by combining two object detection models based on a faster region-based convolutional neural network (Faster R-CNN) with a classification decision tree. The proposed method combines the predicted results from the two Faster R-CNN models and classifies their features with a classification decision tree to generate a bounding-box that surrounds the landslide area in the input image. The first Faster R-CNN model is trained by using a training set of color images (RGB images). The second model is trained by using grayscale images that represent digital elevation models (DEMs). The results from both models are used to construct features for training a classification decision tree. The resulting bounding-box is selected from the following four classes: the box obtained from the RGB model, the box obtained from the DEM model, the intersection of those two boxes, and the smallest box that contains the union of them. The evaluation results show that the proposed method is better than the RGB model in terms of accuracy, precision, recall, F-measure, and Intersection-over-Union (IoU) score. It is slightly better than the DEM model in almost all evaluation metrics, except the precision.

A reservoir flood routing simulation software with spillway operation rules that are readable and configurable by the spillway operator is developed in this study. The software is part of the Dam Safety Remote Monitoring System used by the Electricity Generating Authority of Thailand. The flood routing simulation is implemented using a storage-indication routing method, which is a hydrologic method. The spillway operation rules are exhibited in a tree-based structure, in which the spillway gate opening is derived from the current reservoir water level (RWL), spillway gate opening, and flood situation if the peak inflow has passed. The simulation results show that the simulated RWL is similar to the RWL data in the dam construction manual. This verifies the accuracy of the reservoir flood routing simulation, which is useful for planning the spillway operation.

More than 4,000 dams are constructed in Thailand for several purposes, including water supply, flood control, irrigation, and hydropower generation. Among these dams, 14 large dams are operated by the Electricity Generating Authority of Thailand (EGAT). As a dam operator, EGAT is committed to ensuring dam safety by regularly conducting dam inspections and maintenance. This paper presents the development and practical applications of the Dam Safety Remote Monitoring System (DS-RMS). The objective of DS-RMS is to enhance the EGAT’s implementation of its dam safety program in terms of dam monitoring by instrumentation to satisfy international recommendations. DS-RMS consists of five subsystems: Dam Behavior, Reservoir Operation, Earthquake Monitoring, Expert System and Public Communication. DS-RMS has been deployed at 14 large EGAT-operated dams across the country since 2016. Results show that the novel features of DS-RMS enable faster and more reliable dam safety monitoring and evaluation processes.

In recent years, airborne laser scanning has been used for terrain surveys of broad areas in Japan. This study attempted to extract the landslide-prone slope based on geomorphological and slope stability analyses using Digital Elevation Model obtained by airborne laser scanning. The study site is located in the mountainous region of the Shikoku Mountains, where landslides occur on the gentle slope deformed by mass rock creeps. Implementing slope stability analysis to incorporate “potential to increase pore water pressure” found that landslides occur in areas with low factor of safety. In the future, it is expected that the method developed in this study could contribute to the planning of basin-based disaster management.

To fully and rapidly develop a real-time early warning judgment system for slope failure at the time of heavy rains including overseas, it is necessary to predict water movement in the soil at the time of rainfall. In addition, to apply the system to a place where insufficient geotechnical and geological data have been amassed, it is necessary to evaluate the risk of slope failure based on physical properties obtained from a simple soil test. Therefore, in this study, the authors set Gogoshima Island in Ehime Prefecture as a study site and evaluated the water movement over time in the soil during heavy rain using a simple prediction equation of rainfall seepage process. Soil properties were determined through simple in-situ and laboratory tests. As a result, it was found that the factor of safety for slope failure in the head and wall of a valley dissecting the hillside slope composed of granodiorite in which weathering has progressed can be planarly evaluated using the simple prediction equation.

In recent years, sediment disaster has frequently been caused by heavy rainfall and has cost many human lives and great property losses. To estimate such risks, Wakai et al. [1] proposed a simplified prediction method to calculate the variation of groundwater levels in natural slopes both at the time of rainfall in wide areas and in real time. To calculate the variation of groundwater levels using this method, the slope conditions (such as material constant and initial conditions) must be determined in advance. This study takes the 2017 heavy rainfall in Northern Kyushu as an example to analyze surface layer thickness, one of the slope conditions that most significantly influences slope stability, over wide areas. The findings reveal that the prediction of slope failure distribution differs depending on how the surface layer thickness and sliding surface are determined.

Landslide damage has been reported in many limestone areas in Europe, where the population lives close to limestone areas, and in Guilin in southern China and Ha Long in Vietnam, which are known for their unique limestone landscapes. There are few studies on the mechanism and type of landslide motion in and around such limestone areas. The lack of basic data is a problem for risk assessment and countermeasures in limestone areas. In this study, we summarized the causes and mechanisms of landslide occurrence, including geology and groundwater, focusing on six landslides that occurred in limestone areas in northern Vietnam, and classified them into six types of landslide movement. In the case of Japan, the occurrence of landslides in limestone areas is rare despite the wide distribution of limestone, and it is difficult to classify the type of movement. Differences in the landslide mechanisms are caused by the difference between limestones generated in the pelagic environment of Japan and limestones developed along the Tethys Sea coast, which are mixed with pelitic rocks as shallow-water sediments in Europe, China, and Vietnam. It is necessary to elucidate the relationship between landslides and the formation environment and sedimentary characteristics of limestone as an accretionary prism based on comparisons of a wide range of cases in future studies.

In this study, novel finite element approaches are proposed for numerical analysis of stress-dependent landslide movement with groundwater fluctuation by rainfall. Two new constitutive parameters that are capable of directly controlling the relationship between the apparent factor of safety and sliding velocity are incorporated into a specific material formulation used in finite element analysis for the first time. For the numerical simulation of the measured time history of the sliding displacement caused by the groundwater fluctuations, such required analytical parameters can also approximately be determined by back analysis. The proposed models are applied to a landslide field experiment on a natural slope caused by rainfall in real time in Futtsu City, Chiba Prefecture of Japan to check its applicability. The predicted and measured time histories along the horizontal direction on the upper, middle, and lower slope are compared. In addition, the deformation pattern, shear strain pattern, and possible failure mechanisms of the natural slope of such a field experiment landslide are discussed in detail based on the analysis results of the finite element method (FEM)-based numerical simulation. Moreover, the creeping landslides and possible landslide sites for further application of the proposed models are briefly discussed in the cases of Nepal and Japan as examples in Asia. It is believed that the proposed newly developed numerical models will help in understanding the secondary creep behavior of landslides triggered by extreme rainfall, and at the same time, long-term management of such landslides will be much easier in monsoon Asia. Finally, it is expected that this study will be extended for simulation of the tertiary creep behavior of landslides induced by rainfall in the near future.

Natural hazards continue to be an increasing challenge to societies around the world, with many societies being impacted by multiple types of hazard events. To reduce the impact of these hazards, we must not only quantify the hazard and risk associated with multi-hazard events but also understand the uncertainty associated with these events. Resilience can only be improved by considering all these factors. Multi-hazard and risk-modeling approaches are receiving increasing attention globally; however, the challenges of assessing uncertainty in both single- and multi-hazard risks are considerable. Without a clear understanding of the risks and their uncertainties, measures to mitigate these risks and to increase resilience face difficult decisions. In the present Special Issue, we have five papers and one report on the Tokyo Metropolitan Resilience Project: Interdisciplinary and Industry-Academia Collaboration Research for Enhancing Social Resilience to Natural Disasters in the Tokyo Metropolitan Area –DEKATSU Activity–, Multi-Data Integration System to Capture Detailed Strong Ground Motion in the Tokyo Metropolitan Area, Development of the Training Tool “KUG” for Temporary Lodging Facilities and Companies for Stranded Commuters, Development of Matching Modeling for Human Resource Allocation of Shelter Management by the Set Theory, Time-Cost Estimation for Early Disaster Damage Assessment Methods, Depending on Affected Area, and A Report of the Questionnaire Survey on Awareness of COVID-19 and Shelters.

In 2007, we initiated a 5-year-research project named the “Tokyo Metropolitan Resilience Project.” This project is intended to improve the resilience to natural disasters, particularly earthquakes, in the Tokyo metropolitan area. For this purpose, we have organized multi-disciplinary research including social sciences, natural sciences such as seismology, and civil engineering, with a focus on earthquake engineering. In addition, we facilitate mutual communication between industry and academia. We established the “Data Use and Application Council for Resilience” (Japanese abbreviation: DEKATSU) to organize private and public stakeholders. The DEKATSU council consists of four sectors: industry, government, NPO/NGOs, and academia. The policy promoted to the participating organizations is “When we make organizations resilient, the Tokyo metropolitan area also becomes resilient.” To date, 67 organizational members and 13 personal members have joined, and the targeted idea is becoming accepted but not fully implemented in society.

To accurately capture ground motion in the Tokyo metropolitan area, we have developed a multi-data integration system that combines a large amount of ground motion data gathered from nationwide strong-motion seismograph networks (K-NET and KiK-net); Metropolitan Seismic Observation network (MeSO-net), which covers the Tokyo metropolitan area with a high density of about 300 observation stations; observation equipment held by private companies; and smartphone-based seismographs. K-NET, KiK-net, and MeSO-net are operated by National Research Institute for Earth Science and Disaster Resilience. The seismic waveform data recorded by MeSO-net, which are based on borehole observations, are one of the most important data sets for this system. To ensure collection of the waveform data, we strengthened the data center functions and made the collected data available to the public. In addition, to estimate the ground motion at the surface, which is important for disaster prevention, from the waveform data of MeSO-net, we carried out temporary seismic and microtremor array observations on the ground surface at each MeSO-net borehole station, and estimated ground amplification characteristics and the S-wave velocity structure. We also developed a smartphone-based seismograph with the aim of realizing seismic observations for tens of thousands of sites in the future. We recruited monitors to deploy the smartphone seismometers in the Tokyo metropolitan area, and developed a function to notify monitors of the results of a rough evaluation of the soundness of buildings based on observation data acquired during an earthquake. Furthermore, we have developed a Tokyo metropolitan area version of Kyoshin Monitor, the strong motion monitor system, with which the current ground motion in the Tokyo metropolitan area can be captured in real time by integrating and visualizing observation data from K-NET, KiK-net, and MeSO-net on a map on the website. We can capture the propagation of the ground motion in detail directly from the high-density data set integrated from these three networks. In addition, we also integrated data from Super-Dense Real-time Monitoring of Earthquakes (SUPREME) network of Tokyo Gas Co., Ltd., which operates about 4,000 observation stations in the Tokyo metropolitan area, after applying a time correction. We verified the integration method by reproducing the ground motion in the Tokyo metropolitan area during the 2011 Tohoku earthquake. The study findings have made it clear that the ground motion in the Tokyo metropolitan area can be captured in more detail by the integration of data produced by the public and private sectors.

In order to restrain stranded commuters from returning home en masse in the event of an earthquake, in recent years in large cities across Japan, it has been necessary to encourage stranded commuters, who have no place to go to, to remain on their company premises or stay in temporary lodging facilities. However, specific plans and systems that provide appropriate accommodation for stranded commuters vary greatly depending on the state of the disaster, the characteristics of the facilities, and the affected region. Considering the issue of responsibility, it is difficult for business operators to permit stranded commuters to stay. Therefore, local governments have been making efforts to regard their offices as temporary lodging facilities through agreements and setting up a subsidy system for stockpiling. However, they have not yet made progress in securing temporary lodging facilities, nor in the preparations for restraining small and medium-sized enterprise workers from simultaneously returning home in large numbers. To address this issue, this study developed a training tool on the map with which offices can consider the stay and acceptance of stranded commuters and evaluated its usefulness through a workshop and a questionnaire survey.

The purpose of this study is to develop a support system for planning human resource allocation of shelter management by modeling the matching between the shelter and the staff on the basis of the set theory approach to enable sufficient days off, reduce long work hours, and consideration for appropriate rotation without causing the mental and physical deterioration of the shelter management staff. Using this matching model, a basic study was conducted to determine the appropriate human resource allocation to manage the shelter with a small number of staff members, free from unbalanced work days. The study results elucidate the relationship between the number of possible consecutive work days and that of required consecutive days off. In addition, the human resource allocations with experience in shelter management and the setting method of days off were modeled and their results are presented in this study.

In recent years, various types of disasters have occurred frequently in Japan. Such incidents require a rapid response. It is necessary to grasp the full extent of the disaster at an early stage. Research and development of effective methods to achieve this are in progress. Although each method has its own characteristics, from a business perspective it is necessary to know when and which method should be used to obtain the full extent of the damage. As of yet, there is no comparison among methods to answer this question. Therefore, the purpose of this study is to position the time-cost per unit area as one of the evaluation criteria to understand or estimate damage. To achieve this objective, the procedure of each method is clarified, the area to be analyzed by each method is identified, and the time-cost of each procedure is estimated. The time-cost per unit area is calculated by dividing the time-cost by the area of interest. Particularly, the time required for the preparation of each method, which is independent on the area, is positioned as the initial time-cost that is also derived and added. Based on the above, a linear function with the area of damage as a variable is determined. Simulations are performed to derive the estimated time-cost. Depending on the assumed area of damage, results are obtained when each method is applied.

The 2019 novel coronavirus, or COVID-19, has rapidly spread across the world, and has since become not only a health problem but also a socioeconomic problem. In disaster-prone countries like Japan, there is substantial concern about the occurrence of natural disasters during the COVID-19 pandemic. When a natural disaster occurs, many people evacuate to shelters, and an outbreak of infectious disease often happens in shelters. In this situation, we should consider the management of evacuation shelters under this pandemic situation. Many types of research have investigated infectious diseases in shelters after a natural disaster. However, these are about infectious diseases after a disaster, and not about the occurrence of natural disasters under a pandemic like the ongoing COVID-19 pandemic. Moreover, such researches mainly focus on medical teams or local governments who respond to infectious diseases. Based on the above mentioned information, the purpose of this study is to clarify (i) the change in citizens’ awareness of risk influenced by the spread of COVID-19 and (ii) the measurement and decision necessary for evacuating people under COVID-19. We administered a questionnaire to Japanese citizens from April to May 2020, and found that majority of people do not want to have evacuation life under COVID-19, and this tendency is larger among people who live together with the aged and the care-needed. In addition, this research confirmed the risk awareness structure applicable to both COVID-19 and natural disasters. The results show that many people firmly ask governments to take measures against infectious disease such as using hotels as shelters, securing personal spaces in shelters, storing masks and disinfectors, and so on during an outbreak of an infectious disease. However, it is not enough to take such measures only; it is necessary to provide accurate information and mental support to reduce anxiety in people. Based on these results, we should consider more about the management of shelters under COVID-19 as soon as possible before the arrival of typhoon season.

Effective preparation can help minimize the number of victims and the amount of damage caused by volcanic eruptions, as well as facilitate the recovery of victims’ livelihoods after such disasters. Hence, it is crucial to coordinate and integrate all stakeholders in a management information system in which each stakeholder is interrelated but has different roles and functions. This paper presents the design of a disaster management information system (DMIS) with consideration for the volcano’s location and characteristics. This includes identifying disaster management stakeholders and their respective roles and the volcano’s location and characteristics combined with accessible databases. To validate the design, the results of the DMIS calculations of the needs of refugees from the eruption of Mount Merapi in November 2020 in Kalitengah Lor, Glagaharjo Village, Sleman were compared with the number of real items distributed by the government and donors. The results of this comparison showed that the needs of refugees were fulfilled at a percentage ranging from 66–99%.

The National Research Institute for Earth Science and Disaster Resilience deployed a lightning mapping array (LMA) in the Tokyo metropolitan area in March 2017. Called the “Tokyo LMA,” it obtains detailed three-dimensional observations of the total lightning activity (cloud-to-ground and intracloud flashes) in storms. The network initially consisted of 8 receiving stations, expanded to 12 stations in March 2018. Real-time total lightning images were first opened on the webpage in Japan. Real-time observations from the Tokyo LMA will be used in nowcasting lightning hazards and mitigating lightning disasters. Archived data will be used to develop lightning prediction techniques and a lightning climatology for the Tokyo metropolitan area.

This paper presents a case study comparing the latest algorithm version of Global Satellite Mapping of Precipitation (GSMaP) data with C-band and X-band Multi-Parameter (MP) radar as high-resolution rainfall data in terms of localized heavy rainfall events. The study also obliged us to clarify the spatial and temporal resolution of GSMaP data using high-accuracy ground-based radar, and evaluate the performance and reporting frequency of GSMaP satellites. The GSMaP_Gauge_RNL data with less than 70 mm/day of daily rainfall was similar to the data of both radars, but the GSMaP_Gauge_RNL data with over 70 mm/day of daily rainfall was not, and the calibration by rain-gauge data was poor. Furthermore, both direct/indirect observations by the Global Precipitation Measurement/Microwave Imager (GPM/GMI) and the frequency thereof (once or twice) significantly affected the difference between GPM/GMI data and C-band radar data when the daily rainfall was less than 70 mm/day and the hourly rainfall was less than 20 mm/h. Therefore, it is difficult for GSMaP_Gauge to accurately estimate localized heavy rainfall with high-density particle precipitation.

A supplementary textbook for disaster prevention education was analyzed for understanding the content educators wish to include in disaster prevention curriculums. The text was a condensed textbook – edited by schoolteachers and boards of education in the local governments – from wide areas with a population of one million who were severely affected by the damage and deaths caused by the Great Hanshin-Awaji and the Great East Japan Earthquakes. The targets for analysis were supplementary textbooks for students in junior high schools, published by the five boards of education in Miyagi, Sendai, Iwate, Hyogo, and Kobe. 147 subjects of five supplementary textbooks for disaster prevention education were evaluated as to their applicability to 46 evaluation items. The average of the evaluation items was 11.59 (SD = 2.92). Numerous “Records” (111 subjects, 75.5%) and “Images” (109 subjects, 74.1%), resulted from each evaluation. A remarkable majority of disaster types included “Earthquake disasters” (108 subjects, 73.5%) and “Tsunami disasters” (85 subjects, 57.8%). “Related Fields,” “Social studies” (30 subjects, 20.4%), and “Science” (29 subjects, 19.7%) were the most common subjects. In “Related Fields,” “Special activities” included the highest subjects (59 subjects, 40.1%), after “Ethics,” which included 56 subjects (38.1%). “Writer and persons involved” and “Student who writes compositions and is involved as a learner” included 72 subjects (49.0%). Subsequently, there were “Local residents,” (52 subjects, 35.4%), “Researchers and experts” (36 subjects, 24.5%), and “Unaffected persons” (35 subjects, 23.8%), which included volunteers. Regarding “Type of disaster prevention education,” learning activities for “Prepare for disasters” included the most subjects at 92 (62.6%). Subsequently, learning activities to “Enrich the mind (love for family and community, compassion, the importance of life,)” by raising students’ included 60 subjects (40.8%). Regarding “Qualities and abilities expected to be acquired,” “Knowledge” showed the highest 91 subjects (61.9%). Next was “Self-awareness” (64 subjects, 43.5%), “Social participation/community contribution” (48 subjects, 32.7%), and “Kindness to disaster-affected people” (47 subjects, 32.0%). Moreover, cluster analysis (ward method) was performed using a data set of the subject evaluation of the supplementary textbooks. The analysis with subjects presented six types: “Life-saving measures,” “Fortifying town,” “Measures required for disaster survival,” “Awareness of joining local community,” “Disaster comradery,” and “Living with family and community.” All the five supplementary textbooks featured those six types. More than half of the subjects were featured content regarding student emotions. The first three types were combined and understood as “Countermeasures” with “Knowledge.” In addition, the latter three types were combined and understood as subjects to teach the “Will to live together,” with a relation such as that of ethics and emotional learning. When the same data set was subjected to cluster analysis (ward method) using the evaluation items, four types were obtained: “Knowledge to prepare for earthquake and tsunami disasters,” “Solidarity with family and residents,” “Emergency Response Judgement,” and “Knowledge and skills useful at disaster time.” The types correspond to the classification of the conceptual model of disaster prevention education conducted by Sato et al. [1]. Additionally, all types have corresponding qualities and abilities. The results led teachers to believe that disaster prevention education should be implemented, not simply as life-saving education, but also as instructions that promote the emotional growth of children while cultivating humanity.