1. Introduction
Globally, disasters are forecasted to occur more frequently and to be more severe in the near future, due to climate change, increasingly unplanned urbanization, and the rising concentration of people and assets in hazardous areas [
1,
2]. Over the past decade, extreme climate events have caused an enormous number of fatalities and a significant amount of economic damage. At least 15,490 natural disasters have been reported, since 1990, in the Emergency Management Database (EMDAT-CRED). These disasters, taken together, have caused more than 32.6 million deaths, affected over eight billion people, and caused a total damage of at least USD 3.5 trillion, worldwide [
3]. To address these severe issues, in 2015, three global policy frameworks, i.e., the Sendai Framework for Disaster Risk Reduction (DRR), the Sustainable Development Goals (SDGs), and the Paris Agreement on Climate Change, were established by the United Nations. Among these three frameworks, vulnerability reduction is one of the most significant approaches for achieving the goal of preventing the creation of new disaster risks [
4].
However, vulnerability is a challenging concept to understand and varies among people in diverse circumstances. It is often considered to be related to predispositions, susceptibilities, fragilities, weaknesses, deficiencies, or a lack of capacities [
5,
6]. Various disciplines have come to define vulnerability from their own point of view. The concept of vulnerability has been elaborated in social, economic, environmental, and geographic disciplines, and therefore the literature contains several different vulnerability definitions, as well as various methodological approaches for its assessment. According to Birkmann [
6], more than 25 different definitions, concepts, and methods relating to vulnerability can be found in previous studies. Although there is no universal definition of vulnerability, regarding the literature and previous studies, the concept of vulnerability has been considered from two main perspectives, that is, in terms of its physical and social dimensions. On the one hand, the physical dimension includes the aspects of geography, location, place, settlement patterns, and physical structures. On the other hand, the social dimension characterizes the inequalities that define the predisposition or susceptibility of social groups in the context of a disaster (e.g., age, gender, and disability). In line with the framework of the United Nations, in this study, vulnerability is defined as the conditions determined by physical, social, economic, and environmental factors or processes that increase the susceptibility of an individual, community, assets, or systems to the impacts of hazards.
Evacuation shelter assignment and evacuation planning are significant components of vulnerability associated with reducing and building resilience to disasters [
7,
8,
9]. When a disaster occurs, evacuation shelters are the most significant means for safeguarding people from hazardous areas and situations. Therefore, they are the key factors for minimizing losses due to calamities. Evacuation shelters not only provide immediate and temporary accommodation for victims of a disaster; they also support those residents in their recovery from the associated trauma and provide them with a base to start the process of coping with and adapting to stresses caused by the situation [
10,
11]. Moreover, the survival of affected victims depends profoundly on the availability and accessibility of evacuation shelters [
12]. However, the challenge of providing and arranging suitable shelters in times of emergencies has become an important part of both government emergency management and scientific disaster research.
Evacuation is commonly acknowledged to be an action that is often required to increase the efficacy of disaster response operations and minimize possible loss of life and risk of physical harm due to disasters. However, evacuations can differ in terms of the scale, objects of relocation, and level of control by authorities. Depending on the disaster type and level of pre-warning in the disaster area, an evacuation can be mandatory, recommended, or optional as a means of moving people away from hazardous zones. Furthermore, since evacuations are specifically concerned with moving people out of hazardous areas, the location of the evacuation shelter and the distance to the evacuation shelter can vary based on how long the threat to human life remains within a particular area.
Therefore, the most important topics for studies on evacuation shelter planning and emergency management include determining the location of evacuation shelters and the allocation of people. Shelters are normally offered and prepared to provide secure places for people who have left or lost their usual accommodation due to an emergency situation or disaster. Previous studies have proposed guidelines for emergency shelters, frequently emphasizing their structural suitability, construction specifications, and function [
13,
14,
15]. However, several studies have revealed that considering site suitability based on physical location is also required in shelter planning and assessment [
16,
17]. Kar et al. investigated existing shelters in Florida using a geographic information system (GIS) and suggested suitable candidate shelters based on the geographical area outside of the hazardous zone.
Moreover, regarding shelter allocation issues, shelter capacity has also been debated in the literature, in relation to determining and estimating shelter ability through an evacuation simulation, for example, whether or not the availability of shelters could provide enough accommodation to all evacuees in the case of earthquakes in Japan [
18,
19] and hurricanes in the USA [
20,
21]. To estimate capacity shortage, the ratio between the amount of demand and the available capacity of designated shelters have commonly been included in the aforementioned studies. However, so far, discussions on demand for shelter capacity have not fit the actual situation due to limited data analysis that capture this in reality [
19]. Numerous studies have assumed that 25% of residents would evacuate to emergency shelters; therefore, they have treated it as an input datum using a simple formula (e.g., 25% × the residential population) and estimated the number of people and evaluated the deficiency in terms of shelter capacity [
20,
21,
22]. However, in reality, the evacuation of residents to an emergency shelter is impacted by several factors.
Spatial distribution is one of the significant issues that requires further discussion in relation to the estimation of demand for and the limited supply of emergency shelters. Considering a population in different scenarios, particularly when a disaster occurs, can aid in the estimation of the affected population in terms of evacuation planning and response. Previous studies and proposed models have considered spatial population distribution through urban and community analyses, using GIS, to analyze emergency shelter demand [
23,
24,
25]. Although most research has placed more emphasis on the spatial distribution of a population, only limited research has taken the spatial distribution of existing emergency shelters into consideration [
26]. However, both factors of distribution are critical issues. They influence the availability of shelters, and also the accessibility of shelters to a population. An imbalance between the spatial distribution of people and shelters could lead to and become a vulnerability that must be assessed in disaster and evacuation planning.
Furthermore, additional aspects that notably influence the accessibility of emergency shelters are the evacuation route conditions and distance. These are important factors influencing a decision to evacuate and the selection of an evacuation destination for people [
27]. Routes inundated by floods or covered by collapsed buildings due to an earthquake decrease the efficiency of an evacuation and impact the travel cost for evacuees. Moreover, traveling along an evacuation route to reach an emergency shelter is considered to be a challenging task, especially for individuals who belong to a vulnerable population group, for example, the elderly [
28,
29,
30]. Previous studies have also investigated the relationship between gender-specific variations in terms of socioeconomic status and evacuation, revealing that women were more likely to evacuate than men [
31,
32].
To estimate the accessibility of facilities, according to previous literature, there are two common methods for measuring approachability, i.e., a distance-based function such as Euclidean distance or network distance, and a time-based function. According to these methods, several models and optimizations have been developed to deliver the best all-purpose evacuation route by minimizing the total evacuation distance and potential devastating damages caused by a disaster [
7,
24,
33,
34]. Ye et al. proposed a mathematical formulation to minimize distance by assuming that shelters become available at different periods [
24]. Another mathematic approach was proposed by Zhao et al. which considered the different degrees of house damage to identify the optimal locations for evacuation shelters [
7]. However, most simulation models have usually been developed on the basis of different demand circumstances and criteria among the various available candidates. Such methods limit administrators with respect to applying valuable unknown criteria in reality. In addition, most methods have concentrated more on developing a new algorithm to simulate evacuation procedures, rather than considering the feasibility of evacuating residents efficiently in practice. Consequently, several studies have revealed that it is not yet clear how the accessibility of disaster sheltering should be evaluated in practice [
10,
35].
In this study, we propose a novel methodology for the evaluation of accessibility, integrating the spatial distribution of both a population and the evacuation shelters for assessing and reducing the vulnerability of disaster shelter planning. The objectives of the study are as follows: First, to investigate and evaluate the spatial distributions in the case study area and estimate the deficiency of an evacuation shelter based on the spatial evacuation demand; second, to analyze the spatial accessibility of the evacuation shelters based on the evacuation route conditions and distance, by comparing the real road network of the normal situation with the real disaster situation; and last, to identify the vulnerability of existing evacuation shelters and populations in terms of disaster risk reduction. As a systematic approach for analysis of spatial availability, integrating all aspects of spatial distribution and spatial accessibility, including distance, and evaluating the physical and social vulnerabilities, the proposed methodology is described in
Section 2. In
Section 3, we demonstrate the evidentiary foundation through a case study using GIS technology. A discussion based on the algorithm, suggestions for future studies, and the summary are presented in
Section 4. The overall target of this study is to support decision makers by providing a useful reference for developing policies and strategies to reduce disaster vulnerability.
4. Discussion
This study proposed a methodology for evaluating the accessibility of evacuation shelters and assessing the vulnerability of existing evacuation shelters and populations regarding disaster risk reduction. Because vulnerability during a disaster is increased by the spatial heterogeneity of an imbalance between population demand and shelter capacity resources, our approach integrated both spatial distribution of shelter demand and resource into the spatial accessibility estimation and shelter deficiency assessment. The above analysis and results indicate that the proposed method, in this study, can be used to map the spatial distribution, and also provide a statistical estimation of shelter demand and the vulnerability of shelters and populations. In most of the previous researches, a specific population ratio was applied to calculate and evaluate shelter demand [
20,
21,
22]. However, this is not realistic, given the diversity of disaster situations. In actual catastrophe circumstances, several factors can influence the real demand and accessibility of shelters, including where the population and shelters are located. Therefore, the proposed algorithm integrated the aspects associated with the location, particularly the spatial distribution of both shelters and population to evaluate the imbalance between shelter demand and existing resources of shelters in a real disaster situation. Applying this algorithm in the case study area in Japan, the method revealed that the shelter capacity was reduced to 43.86% by the flood. In addition, GIS-based mapping was also an essential tool for the assessment of the spatial distribution of evacuation shelters and was used to further support shelter assignments and evacuation planning. The specific locations of the closest shelters to each population area were identified and visualized, using the appropriate distance, as suggested by the guidelines for the case study area, since it has been reported that the residents in Mabi did not know where to go during the disaster [
55]. Therefore, our results indicate the nearest designated evacuation and travel route on the GIS map, which can support and enhance the awareness of location and accessibility of shelters for disaster preparation.
According to previous studies based on statistical planning [
18,
19], in the case of an evacuation, there should be sufficient public shelters available for 25% of both the total population and vulnerable residents. However, our results, in the case study area, revealed that the total shelter capacity planning was available to 13.76% of the total population and 43.45% of the senior group in the town of Mabi. Without considering spatial distribution, it is possible that planning assessment does not reflect the real situation of where residents and evacuation shelters are located when a disaster occurs, including how people can access the shelters. After applying the method, in the case study area, our findings show the spatial heterogeneity of the diverse distribution of population and evacuation shelters. The numerous areas with high population density are located in the northeastern, middle, and southeastern parts of the town, whereas, the areas with high capacity of evacuation shelters are mostly located only in the northeastern and middle part of the case study area. The visualized results confirm that spatial distribution is the critical issue that impacts the availability of shelter and accessibility of residents.
Moreover, the condition and distance of the evacuation routes were also considered in conjunction with this approach. The distance-based function of the actual road network was taken into account in the study, rather than using the Euclidean distance, to estimate the accessibility of facilities, because, in the real world, travel routes could be covered, collapsed, or disconnected due to a disaster, which could decrease the efficiency and impact the evacuation and accessibility of shelters [
25]. By comparing the results with the 2018 flooding situation, we also observed that due to the disconnected road network, the shelter demand around the flooding area, based on our study, was significantly increased and enormously exceeded the designated shelter capacity. However, it is not an easy task to build a new shelter to provide greater accommodation capacity in a city where there is limited space. Moreover, it is challenging for the local authorities to determine the designated capacity of evacuation shelters for all the evacuees in a large-scale disaster. On the basis of the statistical results for the case study area, our findings indicated the shelter demand and the location of the remaining sites due to the flood, especially the locations with a demand that exceeds its capacity. Our findings suggest and offer information that could be used by city authorities and disaster administration for planning and managing essential supplies to meet the demand, such as food and sanitation facilities, for example, toiletries and bathroom supplies. In particular, emergency healthcare or medical support should be provided for those considered to be vulnerable groups in this research, who were directly impacted by the disaster situation. The estimated 3976 seniors who experienced the disaster and survived may have lasting mental health impacts [
62,
63], which, in this case, could require both urgent care and extended plan support. Therefore, this study provides vital evidence for policymakers and practitioners for long term disaster management.
Furthermore, the method also showed that people located around the area of the border of the case study area had difficulties evacuating due to the mountainous condition of their geographic location and the long evacuation distance to the shelters. The results for these specific areas provide beneficial evidence that the local government needs to manage and prepare for evacuations of these areas, specifically the elderly population in these areas, who tend to hesitate to evacuate if the evacuation distances are long [
29,
30]. On the basis of our findings, it is recommended that some other options for shelters be arranged in those areas, or cooperation with the neighboring towns should be coordinated. Providing more convenient facilities with easier access, particularly facilities within walking distance, would reduce the risk and stress of evacuation [
25,
26]. In addition, informal shelters, such as parks, temples, local residences, and community halls, could be used to provide accommodation for evacuees during a disaster.
In the future, this study could be further improved. In this study, only people aged 65 and older, as vulnerable groups, were taken into account, since Japan, as a “super-aging” society, has an extremely high proportion of elderly citizens, both in the rural and urban areas. Therefore, additional vulnerable populations, such as children, adolescents, people living with disabilities, and disabled persons, could be included in future research to make the findings more generalizable. Moreover, this research mainly calculated the evacuation routes based on the evacuation distance, which were suggested as guidelines for evacuation, because the objective of the study was to investigate the primary accessibility of evacuation shelters. Differences in terms of altitude were not taken into the account in this study, and this also constitutes a limitation of this research and an area for future improvement. The evacuation time, considering more real-world aspects, should be calculated in the future. Additionally, the hazardous area data applied in this work were from the previous 2018 flooding disaster and the population data were from 2015. Hence, the population distribution could have been altered by the time of this analysis. Additionally, the assessment of the distribution and shelter accessibility could also be investigated in other disaster scenarios, such as earthquakes or tsunamis. Furthermore, this methodology could be implemented in a wide variety of studies due to the advantage of it being a concise technique and the requirement for a minimum number of data, which are usually available for countries like Japan and other countries. A future study could implement the method to assess the impact of further disaster conditions and identify the vulnerability of another area or at a broader scale.