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The Global Centre for Disaster Statistics (GCDS) in Tohoku University was established in April 2015. One of its main missions is to support the Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) in the monitoring and evaluation of progress by providing support at a national level for building the capacity to develop nationwide statistics on disaster damage and by establishing an improved global database for such statistics. The objective of this study was to find clues for the effective measurement of disaster damage utilizing disaster statistics. In disaster loss databases, we often encounter so many observed variables that it is difficult to establish how severe each disaster was in total. Thus, it was considered that introducing a whole new compound indicator to estimate the scale of each disaster properly would be beneficial. In this context, the authors conducted a principal component analysis (PCA) to introduce new compound indicators. The material data for the analysis were retrieved via the global disaster-related database (GDB) provided by the GCDS. Consequently, it was posited that the score of the first principal component, calculated by a PCA, could be an effective indicator to estimate the specific impact of a disaster. We believe that the findings and proposal of a new indicator in this study will contribute to the literature in that new clues to establish an evidence-based criteria and threshold of disaster data collection are provided.

It is becoming increasingly important to implement projects with care on environmental conditions. Some projects can be carried out only during the allowable season and interrupted during other seasons. Such a project interruption is expected to affect the quality of the project’s outcome through the decision-making of the stakeholders. This paper investigates the impact of interruption on the decision-making of the project owner and the contractor. We consider a project with some work after the interruption period (two-year project), the owner can select another option (one-year project) where all work is completed before the interruption period. If the fixed cost is higher relative to the benefit, our results show that the contractor prefers the one-year project, even when the owner selects the two-year project. We also represent the two threshold values of the interruption length that determine the owner’s selection and relative quality of outcomes, respectively. It was found that a range of interruption length where the selected project does not provide the higher quality outcome.

We propose a structure-preserving finite difference scheme for the Allen–Cahn equation with a dynamic boundary condition using the discrete variational derivative method [ 9 ]. In this method, how to discretize the energy which characterizes the equation is essential. Modifying the conventional manner and using an appropriate summation-by-parts formula, we can use a central difference operator as an approximation of an outward normal derivative on the boundary condition in the scheme. We show the stability and the existence and uniqueness of the solution for the proposed scheme. Also, we give the error estimate for the scheme. Numerical experiments demonstrate the effectiveness of the proposed scheme. Besides, through numerical experiments, we confirm that the long-time behavior of the solution under a dynamic boundary condition may differ from that under the Neumann boundary condition.

This study conducts a statistical analysis of the impact of disasters on inter-prefectural migration in Japan over 41 years (1973–2013), and estimates the change in emigration and immigration after disasters of different magnitudes. The result reveals that emigration decreases and immigration increases after a modest-sized disaster, while the opposite is observed following a huge disaster. It also shows a disaster threshold requiring external assistance for recovery and quick decision-making afterwards.

We propose a stable and structure-preserving finite difference scheme for a non-local Allen–Cahn equation which describes a process of phase separation in a binary mixture. The proposed scheme inherits characteristic properties, the conservation of mass and the decrease of the global energy from the equation. We show the stability and unique existence of the solution of the scheme. We also prove the error estimate for the scheme. Numerical experiments demonstrate the effectiveness of the proposed scheme.

There are increasing expectations that social sensing, especially the analysis of social media text as a source of information for COP (Common Operational Picture), is useful for decision-making about responses to disasters. This paper reports on a geo-information and content analysis of three million Twitter texts sampled from Japanese Twitter accounts for one month before and after the 2011 Great East Japan Earthquake disaster. The results are as follows. 1) The number of Twitter texts that include geotag (latitude and longitude information) is too small for reliable analysis. However, a method of detecting the tweet’s location from the tweet’s text using GeoNLP (an automatic technology to tag geo-information from natural language text) is able to identify geo-information, and we have confirmed that many tweets were sent from stricken areas. 2) A comparison of Twitter data distribution before and after the disaster occurred does not identify clearly which areas were significantly affected by the disaster. 3) There were very few Twitter texts that included information about the damage in affected areas and their support needs.

The Great East Japan Earthquake (GEJE) of March 11, 2011 severely affected the transportation systems, both in metropolitan areas and remote villages. Lessons learned from the GEJE provide useful insights to improve future disaster preparations and make transportation systems more resilient. This chapter describes the destruction and damage to the transportation infrastructure by the GEJE and tsunami disaster and subsequent restoration of the transportation systems and presents comparisons of damages, costs, and recovery time of the GEJE with the 1995 Great Hanshin Earthquake. This chapter also discusses the transportation problems related to disaster-induced transportation, such as tsunami evacuation and humanitarian logistics supply.

A warmer-than-normal air temperature enhances the probability of extreme hydrologic events. A spring breakup flood is among the most serious hydrologic events in high-latitude regions. This study examined the use of Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) to monitor the spatial and temporal extent of spring breakup floods in the Lena River, Siberia. Although the 30 m spatial resolution of Landsat produced a detailed mapping of the floodplain, acquisition of Landsat images at short-term intervals was difficult because of the long revisit time of Landsat (16 days) and the frequent cloud cover over Siberia. However, information from two sensors (i.e. TM and ETM+) was combined to essentially halve the revisit time. Moreover, frequent Landsat images were acquired at higher latitudes by using information from overlap areas between neighbouring path images. Therefore, the average revisit time was determined to be 2.6 (= 16/3/2) days in the triple overlap area using two sensors. Updated da...

Riparian regions in Siberia have experienced extreme floods in the last decade because winter precipitation has increased. However, detailed statistical information about spring floods is lacking. Remote sensing is an ideal tool for collecting data over large areas. The objective is to evaluate the relative usefulness and limitations of multiple satellite sensors for monitoring spring flooding across the entire Lena River. Spring floods progress at a speed of ~100 km day−1 during the snowmelt period, expanding the width of the floodplain from several kilometers upstream to several tens of kilometers downstream. The 30-m-resolution Landsat and 500-m-resolution MODIS were sufficient to monitor the spatial extent of the flood. However, the upstream floodplain was too narrow to detect using 25-km-resolution AMSR-E. The AMSR-E was barely able to detect the presence or absence of floods at midstream. However, the AMSR-E microwave sensor could monitor day-to-day variation of spring floods. Images from optical sensors such as Landsat and MODIS were considerably limited by cloud cover. The 10-m-resolution PALSAR was unable to monitor spring floods during the 5-year operational period, because the temporal resolution of 46 days was insufficient to monitor floods. It was sometimes possible to obtain meaningful results from a single remote sensor, but it was impossible to fully understand spring flood behavior over the entire Lena River. An assemblage of sensors with different spatial, temporal, and spectral resolutions would be helpful for flood risk management.

The human and social response in Eastern Siberia to possible changes induced by global warming is the main theme of the Research Institute for Humanities and Nature (RIHN) Siberia Project. This presentation explains why we must use an interdisciplinary approach including natural science and human sciences to tackle this theme.

In a period of declining demand, should we sustain some intercity transport even if it is unprofitable? And in which situations should we sustain the plurality of modes of transport? In this paper, the authors analyze the relationship between time-value distribution and multi-modal network shapes. The network shapes considered are dual-mode or single-mode, and a random parameter model is used to describe the route choice of travelers, which takes the time-value distribution into account. First, the relationship between parameters of time-value distribution (i.e., average and dispersion) and the optimal network shape is analyzed; the authors find that a dual-mode network is optimal when the time-value dispersion is large. Second, as demand declines, the optimal network may change from a dual-mode network to a single-mode network. Third, the conditions in which an equilibrium dual-mode network can be established in a given transport market are described. From a comparison between the equilibrium and optimal conditions for a dual-mode network, the authors find that dual-mode networks may be in equilibrium even though they are not optimal. It follows that we need not sustain unprofitable mode service in order to realize the optimal network shape. Moreover, in a period of declining demand, it may be beneficial to move from a dual-mode network to a single-mode network from a market driven dual-mode network.

Although many studies of the rank-size rule have examined cities, few have provided a micro-behavioral foundation for the rule itself. Using a hierarchical branch office location model, this study confirmed that the rank-size rule appears in the hierarchical structure of a firm calculated using the model. Results show that the power coefficient does not change through a numerical decrease in branch offices when the branch set-up cost increases. Results also show, however, that the power coefficient becomes larger and that employment becomes more evenly distributed when the effectiveness of branch offices, in terms of the ability to compress and aggregate business information, is enhanced. Progress in information and communications technology (ICT) has enhanced the effectiveness of branch offices. Therefore, a flatter organization of firms can be expected in the future.