Showing papers on "Emergency management published in 2022"

Remote Sensing Methods for Flood Prediction: A Review

Abstract: Floods are a major cause of loss of lives, destruction of infrastructure, and massive damage to a country’s economy. Floods, being natural disasters, cannot be prevented completely; therefore, precautionary measures must be taken by the government, concerned organizations such as the United Nations Office for Disaster Risk Reduction and Office for the coordination of Human Affairs, and the community to control its disastrous effects. To minimize hazards and to provide an emergency response at the time of natural calamity, various measures must be taken by the disaster management authorities before the flood incident. This involves the use of the latest cutting-edge technologies which predict the occurrence of disaster as early as possible such that proper response strategies can be adopted before the disaster. Floods are uncertain depending on several climatic and environmental factors, and therefore are difficult to predict. Hence, improvement in the adoption of the latest technology to move towards automated disaster prediction and forecasting is a must. This study reviews the adoption of remote sensing methods for predicting floods and thus focuses on the pre-disaster phase of the disaster management process for the past 20 years. A classification framework is presented which classifies the remote sensing technologies being used for flood prediction into three types, which are: multispectral, radar, and light detection and ranging (LIDAR). Further categorization is performed based on the method used for data analysis. The technologies are examined based on their relevance to flood prediction, flood risk assessment, and hazard analysis. Some gaps and limitations present in each of the reviewed technologies have been identified. A flood prediction and extent mapping model are then proposed to overcome the current gaps. The compiled results demonstrate the state of each technology’s practice and usage in flood prediction.

Deduction of sudden rainstorm scenarios: integrating decision makers' emotions, dynamic Bayesian network and DS evidence theory

Abstract: Event scenarios serve as the basis for emergency decision making after sudden disasters, and the accuracy of scenario deduction directly determines the effectiveness of emergency management implementation. On July 20, 2021, an exceptionally heavy rainstorm disaster occurred in Zhengzhou, Henan Province, China, causing serious urban waterlogging, river floods, flash floods and landslides and resulting in major casualties and property losses:14.79 million people affected, 398 people killed or missing (380 people in Zhengzhou) and a direct economic loss of 120.06 billion RMB. In order to investigate the complex evolution process of this disaster, a dynamic Bayesian network, evidence theory and emotion update mechanism are integrated to develop an efficient and effective scenario deduction model, with an emphasis on combining subjective and objective factors. In this model, more attention is given to subjective factors such as decision makers' emotions. The elements of scenario deduction are classified into the situation status, meteorological factor, emergency activities, decision makers' emotions and emergency goals, the coupling relationship between the elements are comprehensively analyzed, and the influence of these elements on the evolution mechanism of the rainstorm disaster is investigated, so as to facilitate targeted emergency management measures for the rescue operations. The empirical results show that the proposed dynamic Bayesian network can effectively simulate the dynamic change process of scenario deduction, the improved Dempster–Shafer evidence theory can reduce the subjectivity of the model in dealing with the uncertainty of the evolution process, and the emotion update mechanism can adequately quantify and decrease the influence caused by the emotional changes of decision makers. The model may better replicate actual events, and it may apply to the scenario deduction of other disasters, making an impact on the study of sudden catastrophes.

Machine Learning in Disaster Management: Recent Developments in Methods and Applications

Abstract: Recent years include the world’s hottest year, while they have been marked mainly, besides the COVID-19 pandemic, by climate-related disasters, based on data collected by the Emergency Events Database (EM-DAT). Besides the human losses, disasters cause significant and often catastrophic socioeconomic impacts, including economic losses. Recent developments in artificial intelligence (AI) and especially in machine learning (ML) and deep learning (DL) have been used to better cope with the severe and often catastrophic impacts of disasters. This paper aims to provide an overview of the research studies, presented since 2017, focusing on ML and DL developed methods for disaster management. In particular, focus has been given on studies in the areas of disaster and hazard prediction, risk and vulnerability assessment, disaster detection, early warning systems, disaster monitoring, damage assessment and post-disaster response as well as cases studies. Furthermore, some recently developed ML and DL applications for disaster management have been analyzed. A discussion of the findings is provided as well as directions for further research.

Multinational enterprises and natural disasters: Challenges and opportunities for IB research

Abstract: The purpose of this paper is to encourage and to extend research on natural disasters and international business (IB). More specifically, we review the characteristics of natural disasters and the unique challenges they pose to the business environment and examine how they differ from other types of disasters/crises often researched in the IB literature. Next, we investigate the applicability and challenges of core IB theories to the study of natural disasters. By extending new internalization theory (NIT) to overcome challenges of bounded rationality and reliability, we identify effective strategies for managing the threat of natural disasters through establishing multi-sector partnerships and alternative supply chains. Integrating research on the characteristics of natural disasters and the insights from NIT, we propose natural disaster management strategies for multinational enterprises (MNEs) based on varying degrees of geographic scope of natural disasters and MNEs. This paper concludes with proposing new research opportunities for IB scholars in disaster preparedness, cross-organizational collaborations, and supply chain management.

Emergency logistics management—Review and propositions for future research

Abstract: Emergency logistics management has evolved as a prominent international theme due to multiple global disasters in the last couple of decades. Although such global disasters have significantly raised humanitarian support in relief supply and distribution, emergency logistics remain critical during and after a disaster. Hence, it is critical to ensure that an effective and efficient emergency logistics management system is in place to cater to any uncertainties. To commemorate the twenty-five years of Transportation Research Part E (TR-E), we present a brief review of papers published over this period in TR-E on emergency logistics management. Specifically, we highlight the impact, topics, and methodological reach of the journal in the area of emergency logistics. This review provides an overview of the topical areas over those twenty-five years and links these to some of the key debates among logistics/transportation researchers and practitioners. Further, we also highlight the recent trends and propose topics such as “Self-Organized Response System for Emergency Logistics Management” and an architecture for “Integrated Emergency Transportation-Logistics System” for future research in emergency logistics management. More importantly, we believe that this article would pave the way for an integrated and intelligent disaster management framework.

Post-Disaster Temporary Shelters Distribution after a Large-Scale Disaster: An Integrated Model

Abstract: This paper develops an integrated model for the distribution of post-disaster temporary shelters after a large-scale disaster. The proposed model clusters impacted areas using an Adaptive Neuro-Fuzzy Inference System (ANFIS) method and then prioritizes the points of clusters by affecting factors on the route reliability using a permanent matrix. The model’s objectives are to minimize the maximum service time, maximize the route reliability and minimize the unmet demand. In the case of ground relief, the possibility of a breakdown in the vehicle is considered. Due to the disaster’s uncertain nature, the demands of impacted areas are considered in the form of fuzzy numbers, and then the equivalent crisp counterpart of the non-deterministic is made by Jimenez’s method. Since the developed model is multi-objective, the Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Firefly Algorithm (MOFA) are applied to find efficient solutions. The results confirm higher accuracy and lower computational time of the proposed MOFA. The findings of this study can contribute to the growing body of knowledge about disaster management strategies and have implications for critical decision-makers involved in post-disaster response projects. Furthermore, this study provides valuable information for national decision-makers in countries with limited experience with disasters and where the destructive consequences of disasters on the built environment are increasing.

Multinational enterprises and natural disasters: Challenges and opportunities for IB research

Abstract: The purpose of this paper is to encourage and to extend research on natural disasters and international business (IB). More specifically, we review the characteristics of natural disasters and the unique challenges they pose to the business environment and examine how they differ from other types of disasters/crises often researched in the IB literature. Next, we investigate the applicability and challenges of core IB theories to the study of natural disasters. By extending new internalization theory (NIT) to overcome challenges of bounded rationality and reliability, we identify effective strategies for managing the threat of natural disasters through establishing multi-sector partnerships and alternative supply chains. Integrating research on the characteristics of natural disasters and the insights from NIT, we propose natural disaster management strategies for multinational enterprises (MNEs) based on varying degrees of geographic scope of natural disasters and MNEs. This paper concludes with proposing new research opportunities for IB scholars in disaster preparedness, cross-organizational collaborations, and supply chain management.

Approaches to ‘vulnerability’ in eight European disaster management systems

Abstract: While social vulnerability in the face of disasters has received increasing academic attention, relatively little is known about the extent to which that knowledge is reflected in practice by institutions involved in disaster management. This study charts the practitioners' approaches to disaster vulnerability in eight European countries: Belgium; Estonia; Finland; Germany; Hungary; Italy; Norway; and Sweden. It draws on a comparative document analysis and 95 interviews with disaster managers and reveals significant differences across countries in terms of the ontology of vulnerability, its sources, reduction strategies, and the allocation of related duties. To advance the debate and provide conceptual clarity, we put forward a heuristic model to facilitate different understandings of vulnerability along the dimensions of human agency and technological structures as well as social support through private relations and state actors. This could guide risk analysis of and planning for major hazards and could be adapted further to particular types of disasters.وفي حين أنه قد حظي الضعف الاجتماعي في موجهة الكوارث باهتمام أكاديمي متزايد، لا يعرف سوى القليل نسبيًا عن مدى انعكاس تلك المعرفة في الممارسة العملية من جانب المؤسسات المشاركة في إدارة الكوارث. نرسم في هذه الدراسة نهج الممارسين للتعرض للكوارث في ثمانية بلدان أوروبية: المانيا، إيطاليا، بلجيكا، المجر، السويد، النرويج، فنلندا، واستونيا. وتستند الدراسة إلى تحليل مقارن للوثائق و 95 مقابلة مع مديري الكوارث وتكشف عن اختلافات كبيرة بين البلدان من حيث علم الضعف ومصادرة واسستراتيجيات الحد منه وتخصيص المهام ذات الصلة. ولتقدم النقاش وتوفير الوضوح المفاهيمي، طرحنا نموذجا للتوضيح لمختلف مفاهيم الضعف على طول ابعاد الوكالة البشرية والهياكل التكنولوجية فضلاً عن الدعم الاجتماعي من خلال العلاقات الخاصة والجهات الفاعلة. الكلمات الدليلية: التحليل المشترك بين الثقافات، إدارة الكوارث، الضعف، تقييم الضعف.虽然学术界越来越多人开始关注社会面对灾害时的脆弱性，但很少人了解灾害管理机构的实践中反映了多少相关知识。在这项研究中，我们列出了八个欧洲国家应对灾害脆弱性的方法：德国、意大利、比利时、匈牙利、瑞典、挪威、芬兰和爱沙尼亚。该研究通过文件比较分析，并借鉴95次灾害管理人员的访谈，揭示了各国在脆弱性、脆弱性的来源、应对战略和相关职责分配方面的显着差异。为了推进辩论并提供清晰概念，我们提出了一个模型，用于解释由人的想法不同、技术结构不同、以及个人和国家的社会支持不同等造成的对脆弱性的不同理解。 关键词：跨文化分析、灾害管理、脆弱性、脆弱性评估.

Digital twin-driven intelligence disaster prevention and mitigation for infrastructure: advances, challenges, and opportunities

Abstract: Natural hazards, which have the potential to cause catastrophic damage and loss to infrastructure, have increased significantly in recent decades. Thus, the construction demand for disaster prevention and mitigation for infrastructure (DPMI) systems is increasing. Many studies have applied intelligence technologies to solve key aspects of infrastructure, such as design, construction, disaster prevention and mitigation, and rescue and recovery; however, systematic construction is still lacking. Digital twin (DT) is one of the most promising technologies for multi-stage management which has great potential to solve the above challenges. This paper initially puts forward a scientific concept, in which DT drives the construction of intelligent disaster prevention and mitigation for infrastructure (IDPMI) systematically. To begin with, a scientific review of DT and IDPMI is performed, where the development of DT is summarized and a DT-based life cycle of infrastructures is defined. In addition, the intelligence technologies used in disaster management are key reviewed and their relative merits are illustrated. Furthermore, the development and technical feasibility of DT-driven IDPMI are illustrated by reviewing the relevant practice of DT in infrastructure. In conclusion, a scientific framework of DT-IDPMI is programmed, which not only provides some guidance for the deep integration between DT and IDPMI but also identifies the challenges that inspire the professional community to advance these techniques to address them in future research.

Quantitative evaluation of China's disaster relief policies: A PMC index model approach

Abstract: Disaster relief policies play a critical role in improving the effectiveness of disaster relief and reducing disaster damage. This paper uses text mining methods and the policy modeling consistency (PMC) index model to evaluate the effectiveness of disaster relief policies. The analysis presented in this paper constructed an evaluation index system for disaster relief policies and quantitatively evaluated ten representative disaster relief policies in China. The results show that among the ten disaster relief policies, one was rated perfect, five were rated excellent, and four were rated acceptable. Meanwhile, disaster relief policies with a high level of authority score relatively high, and specific policies score relatively low. This Study provides the theoretical reference base for optimizing China's disaster relief policies.

Using School Systems as a Hub for Risk and Disaster Management: A Case Study of Greece

Abstract: The link between climate change and growing poverty levels makes communities more vulnerable to catastrophes, reducing community resilience to disaster consequences. Development practitioners, planners, and researchers must find novel techniques to build community resilience in the face of an ever-growing hazard in such a circumstance with a spectrum of risk and catastrophe. As a result, the focus of this study was on how school systems, as significant social institutions, might effectively minimize disaster risk in communities. People’s standards, beliefs, and behaviors are greatly influenced by societal institutions. After the family, the school is the second most significant socializing institution, in charge of shaping people’s attitudes, knowledge, behaviors, specialized skills, and values in order to ensure social conformity. The prospect of using school systems to increase catastrophe risk reduction in poor areas of Greece was specifically addressed in this study. The study confirmed that the school curriculum has a positive and significant relationship with disaster risk management. Many advantages are realized, according to the research, if catastrophe risk mitigation is made a priority in Greece’s educational systems. Learning about ideas such as civil protection and incorporating disaster risk management into school curricula are both viewed as vital in enhancing disaster risk management.

Effects of Risk Perception on Disaster Preparedness Toward Typhoons: An Application of the Extended Theory of Planned Behavior

Abstract: Abstract This study adopted an extended theory of planned behavior to understand how risk perception affected disaster preparedness behavior. An intercept survey (N = 286) was conducted at a typhoon-prone district of Hong Kong, China in 2019, then the data were analyzed using structural equation modeling. The results indicated that risk perception and intention of preparedness were predictors of disaster preparedness behavior. Risk perception significantly affected intention of preparedness and the effect was partially mediated by subjective norm. Risk perception also significantly affected attitude and perceived behavioral control, but attitude and perceived behavioral control were not significantly correlated with intention of preparedness. Not only may this study supplement the existing literature of disaster preparedness toward typhoons, but also it provides insights for the planning and management of natural hazards and disaster risk reduction in Hong Kong.

A multi-country comparative analysis of the impact of COVID-19 and natural hazards in India, Japan, the Philippines, and USA

Abstract: Several countries have been affected by natural hazards during the COVID-19 pandemic. The combination of the pandemic and natural hazards has led to serious challenges that include financial losses and psychosocial stress. Additionally, this compound disaster affected evacuation decision making, where to evacuate, volunteer participation in mitigation and recovery, volunteer support acceptance, and interest in other hazard risks. This study investigated the impact of COVID-19 on disaster response and recovery from various types of hazards, with regard to preparedness, evacuation, volunteering, early recovery, awareness and knowledge of different types of hazards, and preparedness capacity development. This study targets hazards such as Cyclone Amphan in India, the Kumamoto flood in Japan, Typhoon Rolly in the Philippines, and the California wildfires in the U.S. This study made several recommendations, such as the fact that mental health support must be taken into consideration during COVID-19 recovery. It is necessary to improve the genral condition of evacuation centers in order to encourage people to act immediately. A pandemic situation necessitates a strong communication strategy and campaign with particular regard to the safety of evacuation centers, the necessity of a lockdown, and the duration required for it to reduce the psychological impact. Both national and local governments are expected to strengthen their disaster risk reduction (DRR) capacity, which calls for the multi-hazard management of disaster risk at all levels and across all sectors.

Contribution of Civil Protection to the Urban Economy: Evidence from a Small-Sized Greek City

Abstract: Civil protection has attracted considerable attention due to its role in disaster management and preparedness, being essential in alerting the public about potential disasters and crisis recovery measures. However, there is limited research on civil protection and its vital role in urban economy recovery. Therefore, we sought to comprehensively investigate the impact of civil protection on economic growth and the development of the urban economy, focusing on a small-sized Greek city, Kozani, as a case study. We utilized data from 160 residents of Kozani. The study findings confirmed that the key focus areas of civil protection, namely, the national early warning system, crisis preparedness measures and economy rescue operations, significantly affect economic growth and development. Furthermore, the key strategies essential for improved civil protection, such as government support, positively affect economic growth.

A stochastic programming model for emergency supplies pre-positioning, transshipment and procurement in a regional healthcare coalition

Abstract: A regional healthcare coalition enables its member hospitals to conduct an integrated emergency supply management, which is seldom addressed in the existing literature. In this work, we propose a two-stage stochastic emergency supply planning model to facilitate cooperation and coordination in a regional healthcare coalition. Our model integrates pre-disaster emergency supplies pre-positioning and post-disaster emergency supplies transshipment and procurement and considers two planning goals, i.e., minimizing the expected total cost and the maximum supply shortage rate. With some comparison models and a case study on the West China Hospital coalition of Sichuan Province, China, under the background of the COVID-19 epidemic, we demonstrate the effectiveness and benefits of our model and obtain various managerial insights and policy suggestions for practice. We highlight the importance of conducting integrated management of emergency supplies pre-positioning, transshipment and procurement in the regional healthcare coalition for better preparation and responding to future potential disasters.

Proposed Framework for the Flood Disaster Management Cycle in Malaysia

Abstract: Floods have been reported to be an important disaster in any country and Malaysia has faced similar disasters in the past, resulting in disturbance in daily community routine issues, financial losses, infrastructure damage including railway tracks, bridges, roads, vehicles, properties, and the worst is the loss of lives. The Sarawak region of Malaysia also witnesses yearly disasters in rainy seasons. The purpose of this paper is to explore the possible challenges to manage the flood disaster in Sarawak and to identify the possible solutions to manage floods. In this research, secondary data was used for qualitative assessment. The newspaper articles were collected from the year 2015 until 2019. Targeted interviews were conducted with experts working in flood management disaster schemes to rank and validate the most important factors after content analysis from the past news reports. It is concluded that poor drainage systems, rapid development, heavy rainfall, lack of public awareness, and lack of coordination in executing the disaster management cycle among agencies are the key challenges. Thus, it is recommended that the drainage systems should be upgraded in the case study area. Proper flood management schemes should be planned and flood forecasting should be strengthened. An effective early flood warning system should be designed to activate the plans and a proper public awareness campaign should be initiated to educate and train the local community to deal with such disasters. It is also suggested to assure and maintain proper collaboration among different agencies during such disasters. In the last phase, this paper also proposes a framework for future flood disaster management. The framework will assist the stakeholders to make informed decisions to save human lives and substantial financial losses. The framework can also be used in similar terrain countries.

Review on visualization technology in simulation training system for major natural disasters

Abstract: Major natural disasters have occurred frequently in the last few years, resulting in increased loss of life and economic damage. Most emergency responders do not have first-hand experience with major natural disasters, and thus, there is an urgent need for pre-disaster training. Due to the scenes unreality of traditional emergency drills, the failure to appeal to the target audience and the novel coronavirus pandemic, people are forced to maintain safe social distancing. Therefore, it is difficult to carry out transregional or transnational emergency drills in many countries under the lockdown. There is an increasing demand for simulation training systems that use virtual reality, augmented reality, and mixed reality visualization technologies to simulate major natural disasters. The simulation training system related to natural disasters provides a new way for popular emergency avoidance science education and emergency rescue personnel to master work responsibilities and improve emergency response capabilities. However, to our knowledge, there is no overview of the simulation training system for major natural disasters. Hence, this paper uncovers the visualization techniques commonly used in simulation training systems, and compares, analyses and summarizes the architecture and functions of the existing simulation training systems for different emergency phases of common natural disasters. In addition, the limitations of the existing simulation training system in practical applications and future development directions are discussed to provide reference for relevant researchers to better understand the modern simulation training system.

Emergency preparedness during the COVID-19 pandemic: Modelling the roles of social media with fuzzy DEMATEL and analytic network process

Abstract: While the utility of social media has been widely recognized in the current literature, minimal effort has been made to further the analysis of their roles on disruptive events, such as the COVID-19 pandemic. To address this gap, this work comprehensively identifies the 16 prevalent social media roles in disaster preparedness during the COVID-19 pandemic. Furthermore, an integrated fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and analytic network process (ANP), hereby termed the FDANP methodology, is used to perform the causal analysis of social media roles and to systemically measure the priority of these roles in emergency preparedness. Among the identified roles, those considered top priority are social media roles concerned with the facilitation of public health policy development, prevention of misinformation, and management of public behavior and response. These results were found to be robust, as evidenced by the sensitivity analysis. The implications of these findings were also detailed in this work in the context of a developing country.

Reconstruction of disaster education: The role of indigenous disaster mitigation for learning in Indonesian elementary schools

Abstract: Disaster risk reduction is the main focus of sustainable development . One form of disaster risk reduction is disaster mitigation based on indigenous knowledge. Indigenous Disaster Mitigation is a form of accumulated customary knowledge obtained from the activities and experiences of indigenous people in recognizing potential disaster threats. The purpose of this study is to find patterns of customary knowledge in disaster mitigation in Indonesia and forms of disaster learning in Indonesian elementary schools. This research uses a qualitative meta-analysis approach by analyzing articles from studies on indigenous disaster mitigation and the application of learning in elementary schools. The findings in the research are that there are three patterns or forms of disaster mitigation based on customary knowledge, namely belief, knowledge, and engineering technology, while the disaster learning process uses multiple learning methods that are integrated into each subject. The findings of this study recommend the MISSED LINK model in learning disaster mitigation in elementary schools.