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"DISASTER PREVENTION"
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Factors Influencing Public Participation in Community Disaster Mitigation Activities: A Comparison of Model and Nonmodel Disaster Mitigation Communities
Public participation in community-organized disaster mitigation activities is important for improving disaster mitigation capacity. With data from 260 questionnaires, this study compared the current status of public participation in model disaster mitigation communities and nonmodel communities in a geological-disaster-prone area. Three community-organized disaster mitigation education activities were compared cross-sectionally. A binary logistic regression was used to analyze the effects of attitude, perceived behavioral control, disaster experience, and other key factors on the public’s choice to participate in community disaster mitigation activities. The analysis results indicated that model communities had higher public participation in two efforts, evacuation drills and self-help skills training, and lower participation in activities that invited them to express their feedback than nonmodel communities. The influence of attitudinal factors on the decision to participate in disaster mitigation activities had a high similarity across community types. The public participation in model disaster mitigation communities is influenced by factors such as subjective norms and participation cognition; the behavior of people in nonmodel communities is influenced by factors such as previous experience with disasters, perceived behavioral control, risk perception, and participation cognition and has a greater potential for disaster mitigation community construction. This study provides practical evidence and theoretical support for strengthening the sustainable development of disaster mitigation community building.
Journal Article
Community-Based Disaster Risk Reduction
Communities are at the core of disaster risk reduction (DRR), and community based approaches are getting increasing focus in national DRR plans. In the case of past disasters, communities were always the first responders, and took leading roles in the post disaster recovery. The roles of communities in pre-disaster preparedness are also very important. This is the first comprehensive book available on CBDRR (community based disaster risk reduction) which outlines both research and practice, citing field examples and research results. It provides an overview of the subject and looks at the role of governments, NGOs, academics and corporate sectors in community based disaster risk reduction. It proceeds to examine experiences from Asian and African countries, and concludes by looking ahead to the future perspective of CBDRR.
eBook
Exploring medical and public health preparedness for a nuclear incident : proceedings of a workshop
\"The National Academies of Sciences, Engineering, and Medicine held a workshop on August 22-23, 2018, in Washington, DC, to explore medical and public health preparedness for a nuclear incident. The event brought together experts from government, nongovernmental organizations, academia, and the private sector to explore current assumptions behind the status of medical and public health preparedness for a nuclear incident, examine potential changes in these assumptions in light of increasing concerns about the use of nuclear warfare, and discuss challenges and opportunities for capacity building in the current threat environment. This publication summarizes the presentations and discussions from the workshop.\"--Publisher's description.
Book
Environment Disaster Linkages
This is one of the first books to focus on explicit linkages between the changing environment and disasters and suggests proactive approaches towards disaster management. A ready-reference for field practitioners it covers areas such as elements of environmental entry, impacts of environment and disaster, strategies, planning and the way forward.
eBook
Catastrophe in the making : the engineering of Katrina and the disasters of tomorrow
Based on the false promise of widespread prosperity, communities across the U.S. have embraced all brands of \"economic development\" at all costs. In Louisiana, that meant development interests turning wetlands into shipping lanes. By replacing a natural buffer against storm surges with a 75-mile long, obsolete canal that cost hundreds of millions of dollars, they guided the hurricane into the heart of New Orleans and adjacent communities. The authors reveal why, despite their geographic differences, California and Missouri are building--quite literally--toward similar destruction. Too often, the U.S. \"growth machine\" generates wealth for a few and misery for many. Drawing lessons from the most expensive \"natural\" disaster in American history, Catastrophe in the Making shows why thoughtless development comes at a price we can ill afford.
eBook
Disaster Diplomacy
When an earthquake hits a war zone or cyclone aid is flown in by an enemy, many ask: Can catastrophe bring peace? Disaster prevention and mitigation provide similar questions. Could setting up a flood warning system bring enemy countries together? Could a regional earthquake building code set the groundwork for wider regional cooperation?This book examines how and why disaster-related activities do and do not create peace and reduce conflict. Disaster-related activities refer to actions before a disaster such as prevention and mitigation along with actions after a disaster such as emergency response, humanitarian relief, and reconstruction. This volume investigates disaster diplomacy case studies from around the world, in a variety of political and disaster circumstances, from earthquakes in Greece and Turkey affecting these neighbours' bilateral relations to volcanoes and typhoons influencing intra-state conflict in the Philippines. Dictatorships are amongst the case studies, such as Cuba and Burma, along with democracies such as the USA and India. No evidence is found to suggest that disaster diplomacy is a prominent factor in conflict resolution. Instead, disaster-related activities often influence peace processes in the short-term-over weeks and months-provided that a non-disaster-related basis already existed for the reconciliation. That could be secret negotiations between the warring parties or strong trade or cultural links. Over the long-term, disaster-related influences disappear, succumbing to factors such as a leadership change, the usual patterns of political enmity, or belief that an historical grievance should take precedence over disaster-related bonds.This is the first book on disaster diplomacy. Disaster-politics interactions have been studied for decades, but usually from a specific political framing, covering a specific geographical area, or from a specific disaster framing. As well, plenty of quantitative work has been c
eBook
Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China
The main goal of this study was to use the synthetic minority oversampling technique (SMOTE) to expand the quantity of landslide samples for machine learning methods (i.e., support vector machine (SVM), logistic regression (LR), artificial neural network (ANN), and random forest (RF)) to produce high-quality landslide susceptibility maps for Lishui City in Zhejiang Province, China. Landslide-related factors were extracted from topographic maps, geological maps, and satellite images. Twelve factors were selected as independent variables using correlation coefficient analysis and the neighborhood rough set (NRS) method. In total, 288 soil landslides were mapped using field surveys, historical records, and satellite images. The landslides were randomly divided into two datasets: 70% of all landslides were selected as the original training dataset and 30% were used for validation. Then, SMOTE was employed to generate datasets with sizes ranging from two to thirty times that of the training dataset to establish and compare the four machine learning methods for landslide susceptibility mapping. In addition, we used slope units to subdivide the terrain to determine the landslide susceptibility. Finally, the landslide susceptibility maps were validated using statistical indexes and the area under the curve (AUC). The results indicated that the performances of the four machine learning methods showed different levels of improvement as the sample sizes increased. The RF model exhibited a more substantial improvement (AUC improved by 24.12%) than did the ANN (18.94%), SVM (17.77%), and LR (3.00%) models. Furthermore, the ANN model achieved the highest predictive ability (AUC = 0.98), followed by the RF (AUC = 0.96), SVM (AUC = 0.94), and LR (AUC = 0.79) models. This approach significantly improves the performance of machine learning techniques for landslide susceptibility mapping, thereby providing a better tool for reducing the impacts of landslide disasters.
Journal Article
Identifying Evacuation Needs and Resources Based on Volunteered Geographic Information: A Case of the Rainstorm in July 2021, Zhengzhou, China
Recently, global climate change has led to a high incidence of extreme weather and natural disasters. How to reduce its impact has become an important topic. However, the studies that both consider the disaster’s real-time geographic information and environmental factors in severe rainstorms are still not enough. Volunteered geographic information (VGI) data that was generated during disasters offered possibilities for improving the emergency management abilities of decision-makers and the disaster self-rescue abilities of citizens. Through the case study of the extreme rainstorm disaster in Zhengzhou, China, in July 2021, this paper used machine learning to study VGI issued by residents. The vulnerable people and their demands were identified based on the SOS messages. The importance of various indicators was analyzed by combining open data from socio-economic and built-up environment elements. Potential safe areas with shelter resources in five administrative districts in the disaster-prone central area of Zhengzhou were identified based on these data. This study found that VGI can be a reliable data source for future disaster research. The characteristics of rainstorm hazards were concluded from the perspective of affected people and environmental indicators. The policy recommendations for disaster prevention in the context of public participation were also proposed.
Journal Article