Post-disaster Situations Research Articles

A victim risk identification model for nature-induced urban disaster emergency response.

In recent years, nature-induced urban disasters in high-density modern cities in China have raised great concerns. The delayed and imprecise understanding of the real-time post-disaster situation made it difficult for the decision-makers to find a suitable emergency rescue plan. To this end, this study aims to facilitate the real-time performance and accuracy of on-site victim risk identification. In this article, we propose a victim identification model based on the You Only Look Once v7-W6 (YOLOv7-W6) algorithm. This model defines the "fall-down" pose as a key feature in identifying urgent victims from the perspective of disaster medicine rescue. The results demonstrate that this model performs superior accuracy (mAP@0.5, 0.960) and inference speed (5.1ms) on the established disaster victim database compared to other state-of-the-art object detection algorithms. Finally, a case study is illustrated to show the practical utilization of this model in a real disaster rescue scenario. This study proposes an intelligent on-site victim risk identification approach, contributing significantly to government emergency decision-making and response.

Design for Resilient Post-Disaster Wood Waste Upcycling: The Katrina Furniture Project Experience and Its “Legacy” in a Digital Perspective

Wood is one of the main materials used in buildings and furniture worldwide. After a disaster, indeed, a considerable amount of timber waste is produced. Wood waste is generally downcycled—i.e., recycled into low-quality products, incinerated for energy production—or, worse, landfilled, but in a post-disaster situation, it not only represents a quantitative issue and an environmental hazard but also acquires a cultural, social, economic and emotional value, thus requiring more effective ways to be managed. The Katrina Furniture Project, led by Sergio Palleroni in 2006 for the regions hit by hurricanes Katrina and Rita, provides a valuable precedent. Through pilot initiatives in New Orleans, furniture design emerged as a resilient practice within the reconstruction process. Affected people were involved for six weeks in a collaborative design workshop, enabling the generation of income, the acquisition of professional skills and, moreover, the rebuilding of a sense of community through collective work and the intrinsic gathering value of the crafted objects. The research develops a desk analysis and an on-field survey to reflect on the social, cultural, economic and environmental impacts of this case study and on the role of furniture design for resilient wood waste upcycling. Finally, the paper discusses the “legacy” of such practices from a digital perspective, analyzing limitations and opportunities within current research in design and manufacturing.

Spatial analysis for water supply in seismic emergencies: the Lima-Callao metropolitan area

Introduction: In urban areas exposed to high-magnitude earthquakes, the drinking water supply would be severely damaged, and domestic services would be disrupted for a large part of the population in the event of an earthquake. The Lima-Callao metropolitan area in Peru, South America, is expected to experience an 8.8 Mw earthquake, and it is estimated that approximately 90% of the population would not have immediate access to emergency water in the case of such an event. The main objective of this paper is to define criteria for a spatial analysis method to guide the design criteria for an Emergency Water Supply System (EWaSS).Methods: This paper combines territorial, urban resilience and participatory approaches and presents the results of an interdisciplinary research with social impact. Thus, it examines the urban territory at macro-, meso- and micro scales; physical-spatial variables indicating risk levels and possible public spaces to implement the system; and socio-spatial variables regarding the population, risk perception and participation in management to strengthen urban resilience. Normative tools and the Geographic Information System are used to spatialize and systematize quantitative and qualitative information.Results and discussion: The EWaSS is an alternative for safe water supply in a post-disaster situation that would provide immediate and autonomous operation during the first 72 h of the emergency. The results show the physical-spatial and social viability of urbanized areas and the system design criteria that guide local actors in making decisions at the three levels of emergency management.

An improved ALNS for hybrid pickup and drones delivery system in disaster by penalizing deprivation time

Humanitarian logistics aims to reduce the time relief goods and services take to reach affected areas; deprivation time is one of the most significant factors in such conditions. Thus, utilizing a suitable transport fleet, including modern vehicles like drones, is essential. This paper introduces a new hybrid vehicle routing problem with pickup and delivery services, minimizing deprivation costs with multiple trucks and drones in a disaster. The model is presented as a mixed-integer linear programming problem focusing on minimizing deprivation cost in post-disaster situations through proper routing and inventory decisions made by heterogeneous vehicles. The deprivation time is divided into three main categories based on the arrival time of relief goods to affected areas and will be served by multiple relief goods. Due to the complexity of the problem, an improved adaptive large neighborhood search (ALNS) metaheuristic has been developed. This algorithm employs a heuristic algorithm to generate high-quality initial solutions and improve solutions with 17 destroy and repair operators. The algorithm was tested on a large-scale dataset based on real-world data from a crisis such as the Tehran earthquake, and the results demonstrate its superiority in providing better-quality solutions and lower solution time.

Construction of Rules for Recognizing Landslides Along Highways Induced By Rainfall

After the "7-20" concentrated rainfall, many landslides occurred along the highways in Jiaozuo City, which seriously threatened the transportation safety and brought serious economic losses to the government and the residents along the highways. In order to investigate the development pattern and distribution characteristics of landslides along highways under extreme weather, we took Jiaozuo City Highway as the research object, based on the Sentinel-2 remote sensing data, and on the basis of analyzing the spectral characteristics of landslide hazards, we used the band ratio method to establish the identification rules of loess landslides along highways; based on the topography, geology, human impacts, and meteorological and hydrological selected 11 impact factors, and used geoprospectors to investigate the The driving factors of landslides. The following conclusions and understandings were obtained: (1) a total of 256 landslides along the highway in Jiaozuo City were identified, and the overall identification accuracy of 69.9% was obtained through visual interpretation and on-site research; (2) the ratio of the surface true reflectance of red and green light fused with the slope (>15°) can be used to carry out the identification of landslides in large-scale post-disaster situations; (3) the human activities and topography have a greater impact on landslide development; (4) the identification rule has a greater impact on the development of landslides with similar geological backgrounds. rule is useful for the identification and prevention of landslides along highways in low-hill loess-covered areas with similar geologic backgrounds.

Analysing barriers to humanitarian logistics for distributing relief aid in pre- and post-disaster situations

The purpose of this paper is to analyze key challenges in implementing the relief measures of humanitarian logistics (HL) in the pre- and post-occurrence of the disaster. Analyzing the severity of barriers to humanitarian logistics assists decision-makers and policymakers in reducing societal vulnerability and ensuring efficient allocation of resources in a disastrous environment. An integrated decision-making framework comprising Grey-Delphi and Grey-DEMATEL is employed based on the survey results obtained from various experts and stakeholders in humanitarian logistics. A recent natural calamity that happened in the state of Assam, India, has been selected as a viable case study for the study. Existing barriers to HL have been identified from the prior literature. The factors are further validated by the practitioners and experts in the case context using the Grey-Delphi technique. Further, the causal-prominence relation between HL barriers is revealed by using the Grey-DEMATEL tool. The findings of the study suggest that obsolete IT infrastructure, inconsistent quality monitoring procedures of the relief aids, uncertain and complex geographical conditions, failure of early warning systems, difficulties in last-mile deliveries, and poor coordination among stakeholders serve as critical factors that hinder the efficient functioning of humanitarian logistics in the Indian context. Several managerial and theoretical implications are based on the findings of the study.

Machine learning prediction models for ground motion parameters and seismic damage assessment of buildings at a regional scale

This study examines the feasibility of using a machine learning approach for rapid damage assessment of reinforced concrete (RC) buildings after the earthquake. Since the real-world damaged datasets are lacking, have limited access, or are imbalanced, a simulation dataset is prepared by conducting a nonlinear time history analysis. Different machine learning (ML) models are trained considering the structural parameters and ground motion characteristics to predict the RC building damage into five categories: null, slight, moderate, heavy, and collapse. The random forest classifier (RFC) has achieved a higher prediction accuracy on testing and real-world damaged datasets. The structural parameters can be extracted using different means such as Google Earth, Open Street Map, unmanned aerial vehicles, etc. However, recording the ground motion at a closer distance requires the installation of a dense array of sensors which requires a higher cost. For places with no earthquake recording station/device, it is difficult to have ground motion characteristics. For that different ML-based regressor models are developed utilizing past-earthquake information to predict ground motion parameters such as peak ground acceleration and peak ground velocity. The random forest regressor (RFR) achieved better results than other regression models on testing and validation datasets. Furthermore, compared with the results of similar research works, a better result is obtained using RFC and RFR on validation datasets. In the end, these models are utilized to predict the damage categories of RC buildings at Saitama University and Okubo Danchi, Saitama, Japan after an earthquake. This damage information is crucial for government agencies or decision-makers to respond systematically in post-disaster situations.

MANAGEMENT OF DISASTER THROUGH KNOWLEDGE MANAGEMENT SYSTEM: A CASE STUDY ON SAMBALPUR DISTRICT, ODISHA

Odisha is one of the hazard-prone state and suffers both natural and man-made hazards extensively threatening millions of lives and causing large-scale losses. Disaster management in India also saw a paradigm shift after 2002 from-the humanitarian relief and rehabilitation of victims to the holistic management of disasters viewpoint. The present research addressed this absence of information related to hazards and disasters affecting the district-level Sambalpur. This research aimed to find out some aid in the management of disasters at the district level by collecting and synthesizing all related information about disasters that occur in Sambalpur using an integrated approach. The research used publicly available tools as well as data from credible sources (e.g., government reports). To full-fill the aim, the research compiled information about disasters in the Sambalpur district and prepares a spatial database. Based on socio-economic factors-population density and working population, exposure of the blocks was calculated. Risk and exposure to it assisted in making a vulnerability map of the district at the block level. Based on vulnerability, blocks were prioritized for the policy-makers to ease their management in pre-during and post-disaster situations. The result of this paper would assist policy makers to take proper and quick decisions for the management of the blocks making their management efficient and effective and it could be replicated for other districts of Odisha and India.

Rapid Geometric Evaluation of Transportation Infrastructure Based on a Proposed Low-Cost Portable Mobile Laser Scanning System.

Efficient geometric evaluation of roads and tunnels is crucial to traffic management, especially in post-disaster situations. This paper reports on a study of the geometric feature detection method based on multi-sensor mobile laser scanning (MLS) system data. A portable, low-cost system that can be mounted on vehicles and utilizes integrated laser scanning devices was developed. Coordinate systems and timestamps from numerous devices were merged to create 3D point clouds of objects being measured. Feature points reflecting the geometric information of measuring objects were retrieved based on changes in the point cloud's shape, which contributed to measuring the road width, vertical clearance, and tunnel cross section. Self-developed software was used to conduct the measuring procedure, and a real-time online visualized platform was designed to reconstruct 3D models of the measured objects, forming a 3D digital map carrying the obtained geometric information. Finally, a case study was carried out. The measurement results of several representative nodes are discussed here, verifying the robustness of the proposed system. In addition, the main sources of interference are also discussed.

Game-theoretic algorithm for interdependent infrastructure network restoration in a decentralized environment.

Having reliable interdependent infrastructure networks is vital for well-being of a safe and productive society. Systems are vulnerable to failure or performance loss due to their interdependence among various networks, as each failure can propagate through the whole system. Although the conventional view has concentrated on optimizing the restoration of critical interdependent infrastructure networks using a centralized approach, having a lone actor as a decision-maker in the system is substantially different from the actual restoration decision environment, wherein infrastructure utilities make their own decisions about how to restore their network service. In a decentralized environment, the definition of whole system optimality does not apply as each decision-maker's interest may not converge with the others. Subsequently, this results in each decision-maker developing its own reward functions. Therefore, in this study, we address the concern of having multiple decision-makers with various payoff functions in interdependent networks by proposing a decentralized game theory algorithm for finding Nash equilibria solutions for network restoration in postdisaster situations.

Evaluating UAV Alternatives for Post-Disaster Situations: An Integrated Decision-Making Methodology

Evaluating UAV Alternatives for Post-Disaster Situations: An Integrated Decision-Making Methodology

An Evaluation of Design Proposals for Temporary Shelters Focused on Vulnerable Groups in Post-Disaster Situations

Vulnerable group-oriented temporary space design considers the unique needs and challenges specified groups face during emergencies and aims to create a supportive environment that promotes safety, comfort, and accessibility both physically and psychologically. In this study, the vulnerable group was addressed to women, and a literature study was conducted covering the design of temporary spaces in emergencies and the requirements of the identified group. Alternative temporary space designs were analyzed according to criteria determined from the literature study, and examples were examined with the space syntax method via Depthmap software. As a result, it was suggested that the role of architecture is a significant factor in improving the living conditions and welfare of vulnerable groups, especially women in post-disaster environments, considering different socio-demographic structures and many problems can be corrected with the determined design criteria.

A new planetary affective science framework for eco-emotions: Findings on eco-anger, eco-grief, and eco-anxiety

Emotions play a critical role in human health and behavior yet have largely been overlooked in the context of the global environmental crisis (GEC). Despite recent emphasis on climate anxiety and eco-anxiety, there is a lack of psychometric or dimensional measures assessing the fuller range of GEC-associated emotions, especially beyond Western, educated, industrialized, rich, and democratic (WEIRD) contexts. Further conceptual gaps hinder structured inquiry and generalizability. This exploratory study applies a new planetary affective science framework to holistically and systematically address these issues. We used a circumplex model to map core affect and structured interviews with 15 Turkish environmentalists to explore the range of eco-emotions. Our findings suggest the prevalence of eco-anger and eco-grief over the eco-anxiety most often assessed in WEIRD contexts. Similar findings in post-disaster situations underscore participants’ heightened vulnerability to cumulative stressors and the dangers of emotion-specific omissions (e.g., anger) in assessment tools. We identified environmental justice, developing country tension, self-efficacy dimensions, and responsibility attributions to the Turkish government and Global North as key contextual factors in these differentiated eco-emotional patterns. Findings constitute the first step toward more holistic, diverse, and conceptually rigorous eco-emotions research, urgently needed for more effective pro-environmental health and behavioral interventions amidst the intensifying GEC.

Natural disaster is a wakeup call before it becomes social disaster and tourophobia of eco-destinations

ABSTRACT This paper summarizes the current state of crisis and disaster at the eco-destination of Thailand and investigates its impact on tourists’ preferences. The study authenticates the claim of the inevitability of disasters at eco-destinations, explains the effects of timely response by relevant authorities, and provides inputs to diffuse the chaotic post-disaster situation and the development of tourophobia. It further notes the contribution of destination reputation and crisis communication to maintaining tourists’ trust and making Thailand the first choice for eco-tourism enthusiasts. This paper provides insights into effective post-disaster management before it turns eco-destinations into tourophobic destinations.

AN ANALYSIS OF POST-DISASTER RECOVERY EFFORTS IN TURKEY ACCORDING TO KURT LEWIN'S CHANGE MODEL EXAMPLE OF KAHRAMANMARAŞ AND HATAY PROVINCES

Turkey, which has a surface area of 780 thousand square kilometers, is a country that is in the position of a bridge between the European and Asian continents, most of which is in the Asian continent. Due to its location, Turkey's territory is highly prone to natural disasters and has faced many disasters such as earthquakes, floods, landslides and avalanches. This high- risk geography has hosted major earthquakes, floods, landslides and avalanches every five years on average. Turkey, which has been exposed to disasters whose exact location, time and type cannot be determined, is in a constant state of change in terms of managing and improving the post-disaster crisis situation, especially in terms of physical, economic and social losses after these natural events. Especially social losses after disasters can be classified as losses that take longer to recover, require more labor and cause countries to spend more energy after the crisis compared to physical and economic losses. Post-disaster social losses require adaptive measures and change management with reference to the previous situation, which has become obligatory to change. This study aims to examine post-disaster recovery efforts in Turkey in the context of Kurt Lewin's Three Stages of Change Model. In this direction, the studies related to the Three Stages of Change Model have been analysed and the social context of post-disaster recovery efforts around the theory has been evaluated within the framework of Kahramanmaraş and Hatay earthquakes.

PDNA of Post Flood Event in Pasir Mas, Kelantan, Malaysia

Extreme rainfall variations generally result in either extreme precipitation accompanied by flood risk events. Globally, flooding has been a major worry, particularly in Malaysia. In recent years, the frequency and magnitude of floods have grown substantially. Severe precipitation has caused significant devastation to human life and property. Exposure, vulnerability, and risk analysis use inventories of elements-at-risk (EaR), also known as assets, to determine who and what is at risk. The recent occurrence that occurred in February and December 2022 were unprecedented and cause RM29.8 million of economic losses in Kelantan. Numerous problems that range from structural, social, environmental, economical to psychological impacts strike over the community in this flood prone area. Almost 230, 424 people and 54, 924 houses were directly impacted by this flood event. The primary objective is to determine the entire amount of a disaster’s effect on a nation and based on these findings, to develop an executable and sustainable Recovery Plan for mobilising financial and technical resources. The methodology and procedure for a full evaluation of damages, losses, and requirements, leading to the establishment of a Recovery Strategy. Assessment and Recovery Strategy produced during the PDNA is a necessity as it is a more thorough recovery planning, especially in the event of large-scale disasters. Mapping the impact of the flood catastrophe and gathering all information related to the communities to get back to their daily lives a comprehensive assessment is imperative. With these building back better is feasible for this exposed community. The PDNA analyses disaster consequences and implications. It uses analytical approaches, tools, and strategies for post-disaster evaluations and recovery planning to ensure comparability and uniformity. It provides complete picture of the post-disaster situations highlighting the various requirements and goals of different sectors, social groups, and sub-groups.

Combating energy poverty via small-scale solar for initial electrification and post-disaster recovery in Guatemala and Puerto Rico communities

Despite the ubiquity of electricity in many parts of the world, there are still over a billion people who do not have access to a reliable electric grid. Distributed solar energy has emerged as a low-cost solution for these off-grid communities to gain access to electricity. These communities tend to be in rural, remote, or agricultural regions where it can be expensive to extend existing electrical infrastructure. Such regions have also been shown to be the slowest to recover in post-disaster situations, where electrical infrastructure has been damaged. Addressing this need, our group installed small-scale solar kits (100–400 W) in different regions of non-electrified Guatemala and post-Hurricane Maria Puerto Rico. To improve the efficacy of our installations and future efforts, we surveyed households about their current circumstances, energy consumption, and energy needs. Our results show that despite different circumstances impacting energy access (non-electrified Guatemala versus for disaster recovery in Puerto Rico), there were similarities in their socio-economic statuses and their energy needs. We found that the small-scale solar kits enabled the usage of basic devices such as in-home medical equipment, lighting, phone-charging, and other small devices of interest to the families. Herein, we address the link between energy poverty, solar electrification for powering small devices, and the quality of life of households in both communities.

Using the EEG+VR+LEC evaluation method to explore the combined influence of temperature and spatial openness on the physiological recovery of post-disaster populations

Natural disasters have always been a substantial threat to human survival and development. Due to climate change, the number of weather-related disasters has more than doubled worldwide, further emphasizing the need for research on post-disaster environments. However, conducting comprehensive studies in actual disaster settings poses a number of challenges. This study proposes a novel approach that combines electroencephalography (EEG), virtual reality (VR), and laboratory environmental control (LEC) to investigate the joint effects of temperature and spatial openness on the psychological recovery of post-disaster populations. The integration of these techniques provided a controlled and immersive experimental environment for simulating post-disaster scenarios. This study conducted a controlled group experiment focusing on two variables in post-disaster environments: temperature range and spatial openness. Three temperature ranges were selected for the temperature condition: high (30 °C–36 °C), mid (22 °C–28 °C), and low temperature zones (12 °C–20 °C); the temperature environments were controlled by LEC. In terms of spatial openness, three levels were chosen: temporary emergency shelters (enclosed space), the semi-outdoor area of the emergency building (BBBC) designed by the project team (semi-open space), and open natural environments (open space). This research then established a temperature-spatial openness matrix. The study involved emotional recovery experiments for nine patterns of post-disaster environments, using physiological parameters such as EEG, skin conductance, and heart rate, as well as psychological parameters established through subjective questionnaires. The findings of this study will be beneficial for efficiently and reasonably optimizing human-centered spatial environment designs in post-disaster situations featuring limited resources.

Simulation of Shotcrete in RC Tunnel Using Finite Element Method

Nowadays, tunnels are gaining importance with the developing transportation networks. Different solutions are made in the design of tunnels according to the land structure and ground condition. Various retrofitting methods are used in damaged tunnels. Especially in recent years, natural disasters in the world have also affected the tunnels. There may be damage and collapse in the tunnels during and after the disaster. It is predicted that in the event of a possible collapse in the event of a disaster, loss of life and property may also occur. After the disaster, even if the tunnels have not collapsed, they are damaged. In this case, collapse may occur in the next disaster due to collapse or environmental vibrations. It is also known that in post-disaster situations, it is vital that the transportation network remains active in order to deliver the necessary aid to the region. For all these reasons, in this study, the shotcrete method, which is one of the retrofitting methods of tunnels, is mentioned. Thus, the effect of the shotcrete method applied on an exemplary tunnel on modal parameters has been demonstrated. In this comparative study, it was observed that the stiffness of the tunnel increased with the shotcrete method. As a result of this study, it is suggested to retrofitting the tunnels with the shotcrete method, taking into account the state of the tunnel lining or mirror and environmental factors.

Analytical Study on Retrofitting Concrete Retaining Wall with Concrete Lining

Today, retaining walls are gaining importance with the developing transportation networks. Different solutions are made in the design of retaining walls according to the land structure and ground condition. Various retrofitting methods are used in damaged retaining walls. Especially in recent years, natural disasters in Turkey have also affected the retaining walls. There may be damage and collapse in the retaining walls during and after the disaster. It is predicted that in the event of a possible collapse in the event of a disaster, loss of life and property may also occur. After the disaster, even if the retaining walls have not collapsed, they are damaged. In this case, collapse may occur in the next disaster due to collapse or environmental vibrations. It is also known that in post-disaster situations, it is vital that the transportation network remains active in order to deliver the necessary aid to the region. For all these reasons, in this study, the concrete lining method, which is one of the retrofitting methods of retaining walls, is mentioned. Thus, the effect of the concrete lining method applied on an exemplary retaining wallon modal parameters has been demonstrated. In this comparative study, it was observed that the stiffnessof the retaining wall increased with the concrete lining method. As a result of this study, it is suggested to retrofitting the retaining walls with the concrete lining method, taking into account the state of the walland environmental factors.