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Bazhong City is located on stratum dominated by red-bed conditions. This type of weak geological condition with sand and mudstone interbedding is very easily affected by climatic conditions to produce rainfall-type landslides. On the basis of landslide data statistics collected in Bazhong City from 2011 to 2019, this paper uses ERA5-Land rainfall data to statistically analyze the correlation between rainfall and landslide events in Bazhong City. The landslide events in Bazhong City are greatly affected by rainfall events lasting for 10 days. Considering the influence of rainfall seepage and other processes, an effective cumulative rainfall-duration threshold curve for Bazhong City is obtained via median nonlinear fitting. Then, on the basis of the prediction interval, the rainfall threshold formula under different landslide occurrence probabilities is obtained and the critical threshold curve with a non-exceeding probability of 1% in Bazhong City is calculated and verified. Subsequently, a continuous probability distribution fitting function of landslide occurrence is established and a continuous probability distribution surface with a good fitting effect in Bazhong City is obtained. This allows a definite probability of whether future rainfall events will induce landslides to be obtained, providing an important basis for engineering disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

Communities in the Hindu Kush Himalayan (HKH) region of Pakistan are highly vulnerable to climate change. Capacity building of local communities is integral to adopt an evolving strategy to address adverse effects of climate change. This paper examines the significance of adaptive capacity through training and orientations and its efficacy to address climate induced hazards. Data from remittance receiving 246 households in treatment group and 247 households in control group were collected from selected villages of Districts Hunza and Nagar in Gilgit-Baltistan, Pakistan. The difference in difference (DiD) method was used to examine the impact of the intervention—adaptation and effects. The results of the study revealed that enhanced capacity building of local communities in terms of financial literacy, investment in flood preparedness and adoption of disaster risk reduction have significant impact and corelation with improved resilient planning strategies and practices. The study recommends further actions, trainings and to governmental and non-governmental organizations to emphasize on proper utilization of remittances and to orient the mountain communities about proper plans and actions to mitigate the climate change impact. [ABSTRACT FROM AUTHOR]

In this paper, the combined static-dynamic loading tests on refabricated parallel fissured granite were conducted with SHPB system at six confining pressures (0, 10, 20, 30, 50, and 60% of the UCS) and three dip angle (0, 45, and 90 °). Moreover, a non-contact monitoring device, the DIC, was used to fully detect the full-field strain of the specimen. Comprehensively the initiation, expansion, penetration process and failure mode of double-fractured specimens were investigated, and the deformation and failure characteristics and strength change law during the failure process were discussed. The fractures had a significant degradation effect on the dynamic compressive strength of the rock. Parallel double fractures showed the large principal and shear strains at and near the fissure tips firstly during damage and extended through each other, causing damage to the specimens. There were two main types of cracks: tensile cracks and shear cracks in the failure process. The displacements of key cracks in 45 and 90 ° specimens were analyzed, which showed that the slip displacement gradually increased with the increase in axial pressure, while the tension displacement showed an increase first and then a decrease. The angle of inclination of parallel double fissures is critical to the initial generation of tensile strain zones and the subsequent development and expansion of tensile strain zones. The research results will provide an important theoretical basis for the development and utilization of underground engineering structures and disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

Most emergency responses involve collaborative efforts from teams operating in the field and in the backstage. Collaboration within and across agencies should therefore be regarded as an essential service in emergency management. We propose a conceptual lens to analyse the technological support to collaboration services in emergency management. The proposed lens is based on the 3C Model, which regards collaboration services as the articulation and composition of three other services: communication, coordination and cooperation. Using this lens, we conduct a scoping literature review of the emergency management domain. The review contributes to better understand the relationships between collaboration services and technology support in emergency management. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to identify and review literature relevant to the medical response to the 921 earthquake in order to analyse Taiwan's immediate and long-term management of the medical issues arising from the disaster. Methods: Pubmed and Google Scholar searches were conducted in June 2008 to identify papers relevant to the topic. These were reviewed and the findings of each collated to develop a critical review of Taiwan's response to the earthquake. Pubmed and Google Scholar searches were conducted again in March 2010 to verify the currency of the literature reviewed. Results: A total of 14 papers were identified and reviewed. Many concluded that while disaster response efforts were initiated quickly, the inexperience of the authorities, the timing and location of the earthquake, and the associated destruction of vital infrastructure, meant much of the initial rescue planning and coordination was improvised. This resulted in poor response times by emergency teams, inefficient mobilisation of military and medical resources, poor cooperation between authorities and a failure to fully utilise international assistance when it arrived. Conclusion: Taiwan was unprepared for a disaster of the magnitude of the 921 earthquake. The government has since taken initiatives to ensure Taiwan is better prepared for any future large scale disaster, including the establishment of the National Institute for Disaster Management. There is a paucity of literature on the medical response to the disaster. Only one new paper of relevance to the topic has been listed on Pubmed or Google Scholar in recent years. [ABSTRACT FROM AUTHOR]

Presently, the Internet of Things (IoT) and big data analytics technology offer enormous opportunities to disaster risk management services. Recent disaster risk management patterns involve disaster risk reduction to avoid future disaster risks, minimize current disastrous risks, resilience building, and disaster loss reduction. The main challenges in disaster management are communication within a disaster zone which is being disrupted. In this paper, the Internet of Things assisted disaster risk management framework (IOTDRMF) has been proposed for technical resources to communicate the emergency time and better visibility into reliable and prompt decision-making through observing, evaluating, and forecasting natural disasters. This IOTDRMF utilizes big data analytics to analyze disaster risk management build a kind of spatial data communication network infrastructure, making it a priority to establish rules, protocols, and knowledge sharing. The experimental results show the IOTDRMF, and big data analytics compensate for a weak communication network infrastructure and better decision-making to handle disaster risk management. [ABSTRACT FROM AUTHOR]

Japan is one of the disaster-prone countries. Then, various disaster education is conducted in schools and local communities for alleviating the damage caused by disasters. However, according to various surveys, disaster prevention awareness among young people is known to be lower than in other age groups in Japan. Therefore, we worked with Kanagawa Prefecture, Japan, on establishing an ICT-based program on disaster prevention and mitigation to raise awareness of disaster prevention and mitigation among young people. The program is based on the workshop consisting of town watching and group discussion using DITS/DIMS (disaster information tweeting and mapping system) proposed in the previous studies. In this paper, we introduce the contents of the established education program on disaster prevention and mitigation for the young generation. Moreover, we report on the results of the workshops for disaster prevention and mitigation using this program at several junior high and high schools in Kanagawa Prefecture, Japan. The results of the post-questionnaire show that many participants had a positive impression on the developed disaster education program. [ABSTRACT FROM AUTHOR]

Search and rescue are essential applications of disaster management in which people are evacuated from the disaster-prone area to a safer place. This overall process of search and rescue can be more efficient if an automated system can quickly locate the human or area where rescue is required. To provide a faster and accurate search of those places, this paper proposes a novel approach to search and rescue using automated drone surveillance. In this paper, a complex scene classification problem is solved using the proposed 3DCNN model. The proposed model uses spatial as well as temporal features of the video for the classification of the scene as help or non-help in the natural disaster. Due to the unavailability of such kind of dataset, it is impossible to train the model. Therefore, it is essential to develop a dataset for search and rescue. The proposed dataset is a first and unique dataset for scene classification using drone surveillance. The major contribution of this paper is (1) a novel 3DCNN powered model for scene classification in drone surveillance, (2) to develop the required dataset for the training of scene classification model, and (3) particular swarm optimization (PSO)-based hyper-parameter tuning for getting the best value of multiple parameters used for training the model. Our hybridization of parameter tuning with PSO helps for the convergence of parameter values of proposed 3DCNN model, and the proposed scene classification model (3DCNN+PSO) is applied to the dataset. The proposed model gives an impressive performance to help situation identification with 98% training and 99% validation accuracy. [ABSTRACT FROM AUTHOR]

Qinghai-Tibet Plateau is one of the most seismically active aeras of China and rock mass structures or geological structure are also complex here. Earthquake-induced geological disasters are occurred frequently in this region. Among them, plane failure is often generated on bedding rock slope especially in destructive area of the Wenchuan earthquake which caused numerous casualties and serious economic loss. To reveal failure mechanism of bedding rock slope, this paper studied the seismic response and investigated progressive failure characteristics of the bedding rock slope through a large-scale shaking table test. A bedding rock slope of 45° contained an unfilled joint set with spacing of 0.1 m that dipped at an angle of 34° out of the surface, was conducted in a rigid model box, with a length of 3.47 m, width of 0.68 m, and height of 1.2 m, respectively. A series of tests results show that acceleration amplification factor in horizontal direction (AAF-X) increases with the increase of the slope elevation and acceleration amplification factor in vertical direction (AAF-Z) amplifies at lower part of the slope. When the shaking intensities are over 0.2 g, the slope crest and its vicinity start to show nonlinear dynamic response. Existence of bedding planes let the isoline morphology of AAF-X redistribute and dominate the seismic amplification at the crest. The progressive failure progress of the model under earthquake can be divided into four stages. This novel experiment offers some important insights to mechanism of bedding plane landslides triggered by earthquakes, evaluation stability of slopes under earthquake, and disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

Abadeh, A., Iran Abdelouahed, L., France Abdelsalam, S. I., Egypt Abedini-Nassab, Roozbeh, Iran Acharya, N., India Adeli, M., Iran Agarwal, M., India Ahmadi Khoshooei, M., Canada Akram, N., Malaysia Amini, Y., Iran An, W., China Anand, K., India Annamalai, K., India Ao, W., China Azhagurajan, A., India Balasubramanian, D., India Bandyopadhyay, A., India Bannach, G., Brazil Benyoucef, A., Algeria Bernardin, A. M., Brazil Bobrowicz, J., Poland Chang, D.-H., Korea Che, D., China Cheema, T. A., Pakistan Chen, W.-c., Taiwan Chen, M., China Chen, C.-C., Taiwan Chen, R., China Chen, D., China Chen, W.T., Taiwan Chougule, S. S., India Conceicao, M. M., Brazil Duan, X., China Durak, H., Turkey Ge, H., China Greco, A., Italy Hou, H.-Y., Taiwan Hui, S., China Jiang, H., USA Jin, B., China Keppert, M., Czech Republic Kobelnik, M., Brazil Kök, M. V., Turkey Kossoy, A., Russian Federation Kou, K., China Kristiawan, B., Indonesia Kumasaki, M., Japan Lin, C.-P., Taiwan Liu, S.-H., China Meikap, B. C., India Mukherjee, P., USA Obracaj, D., Poland Pan, X.-H., China Pan, W.-P., USA Pan, R., China Qian, X.-M., China Qiang, X., China Schiraldi, A., Italy Shu, Y.-L., Taiwan Song, Z., China Talebizadeh Sardari, P., UK Tang, Y., China Trache, D., Algeria Tsai, Y.-T., China Wang, Z.-R., China Wang, C., China Wang, Q., China Wang, K., China Wang, Q., USA Wen, K.-L., Taiwan Wu, S.-H., Taiwan Wu, D., Germany Xiao, Y., China You, M.-L., Taiwan Yousei, B., Canada Zeng, Q., China Zhang, B., China Zhang, Y., China Zhang, H., China Zhang, J.-Q., China Ziganshin, M. A., Russian Federation Zuo, W., China Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Worldwide, the chemical market alone serves the $5 billion market and directly employs millions of people. Graph I Guest Editor i Graph This compilation is based on the peer-reviewed and selected papers presented at LPPSTA 2019. [Extracted from the article]

Integrated disaster risk management in a changing climate is a key concern for disaster reduction and global sustainable development now and in the future. This study conducted descriptive statistical and bibliometric analysis of 488 articles on integrated disaster risk in a changing climate from 2008 to 2020 using Excel, CiteSpace, and Gephi. The research process of integrated disaster risk in a changing climate was divided into three periods, 2008–2010, 2011–2015, and 2016–2020, which is similar to the changing characteristic of the number of publications. Results showed that, first, although the number of papers was increasing exponentially, the number of publications in each period remained relatively small. Second, the main features of the cooperation network of authors across the world showed a small concentration of groups, large dispersion, and weak connections. Third, the literature focused on five key issues, including basic disaster theory research; the construction of databases; research on underlying concepts, relationships, determinants and influences of vulnerability, risk, adaptability and resilience; the construction of frameworks and models of integrated disaster risk; and impact analysis of integrated disaster risk assessment and governance in regard to the relationships and interactions among disasters, nature, society, and human behavior. Fourth, the priorities, foci, and frontiers of integrated disaster risk research were mainly reflected in five aspects, including disasters; climate change adaptation; climate change impacts; health, insurance, critical infrastructure, communities, and various frameworks; and research on key regions and countries. [ABSTRACT FROM AUTHOR]

Based on the upper limit theorem of limit analysis and the Hoek-Brown failure criterion and considering the adverse influence of the seepage force, we established a stability analysis method of analyzing the water-resistant rock mass of a karst tunnel face, developed a critical safety thickness criterion for water inrush caused by the instability of the tunnel face, and conducted a sensitivity analysis of the main influencing parameters. We defined the safety coefficient (k) of the tunnel face's resistance to water-inrush instability during the tunnel excavation process and analyzed the dynamic evolution characteristics of the tunnel face's stability during the tunnel construction according to the safety coefficient. We used the method introduced in this paper to calculate the safe thickness of the water-resistant rock mass of the Xiema tunnel face in the first horizontal line of the Chongqing Expressway where it is adjacent to karst cavity 268. We compared these results with the calculation results of a method that did not consider the adverse influence of the karst water seepage force. The results showed that the safety thickness of the water-resistant rock mass calculated using the method proposed in this paper more accurately conformed to the actual situation of the project, which can more effectively ensure the construction safety of the tunnel segment adjacent to the anterior, concealed, high-pressure, water-rich karst cavity. The results of this study hold great significance for improving the predictability and targeted prevention of water-inrush disasters in karst tunnels. [ABSTRACT FROM AUTHOR]

The theory about the impacts of natural disasters on firms is ambiguous and the empirical evidence on this topic is scarce, which hampers the design of disaster risk reduction and climate change adaptation policies. In this paper we identify the short-run impacts of storms and floods on firm growth in labor, capital, and sales, using Enterprise Census data (2000–2014) for Vietnam. We define storms and floods with three different disaster measures: physical intensities, number of deaths, and economic damage. The performance of these disaster measures is compared by estimating dynamic growth models using the Blundell–Bond system generalized method of moments. We find evidence that flooding increases labor growth and capital growth but reduces sales growth significantly up to 3 years after flooding. We also find some evidence of positive impacts on labor growth and capital growth but mostly negative impacts on sales growth for storms within 3 years after storms strike. The impacts of floods and storms on firm growth are more pronounced and persistent for small and medium sized firms. Finally, unlike at the macro level, the direction and scale of disaster impacts found at the firm level are fairly consistent across the three disaster measures. [ABSTRACT FROM AUTHOR]

The use of autonomous vehicles for source localisation is a key enabling tool for disaster response teams to safely and efficiently deal with chemical emergencies. Whilst much work has been performed on source localisation using autonomous systems, most previous works have assumed an open environment or employed simplistic obstacle avoidance, separate from the estimation procedure. In this paper, we explore the coupling of the path planning task for both source term estimation and obstacle avoidance in an adaptive framework. The proposed system intelligently produces potential gas sampling locations that will reliably inform the estimation engine by not sampling in the wake of buildings as frequently. Then a tree search is performed to generate paths toward the estimated source location that traverse around any obstacles and still allow for exploration of potentially superior sampling locations.The proposed informed tree planning algorithm is then tested against the standard Entrotaxis and Entrotaxis-Jump techniques in a series of high fidelity simulations. The proposed system is found to reduce source estimation error far more efficiently than its competitors in a feature rich environment, whilst also exhibiting vastly more consistent and robust results. [ABSTRACT FROM AUTHOR]

The post-disaster humanitarian logistic operations deal with the supply of emergency relief materials to mitigate damages in the affected areas. Immediately after the disaster, it is challenging to estimate the demand for emergency relief materials. As a result, the demand for such materials at the point of demand and the corresponding transportation costs for the entire supply chain network becomes uncertain. This paper proposes a new probabilistic fuzzy goal programming model for making decisions to manage the post-disaster supply of emergency relief materials. A suggested procedure converts the proposed model to its deterministic equivalent when the demands for the relief materials follow uniform distributions. We implement the differential evolution, a metaheuristic technique, for analyzing demand satisfaction for relief materials under various scenarios. A case example based on the Nepal Earthquake in 2015 demonstrates the usefulness of the proposed approach. The solution of the model will help the Disaster Management Agency coordinate with the humanitarian organizations and foreign countries to provide the required emergency relief materials so that an adequate level of supply can be assured to the affected areas with the least possible transportation cost. [ABSTRACT FROM AUTHOR]

Every year, natural disasters such as earthquakes, floods, volcanos, etc. cause millions of victims. So a quick response to these disasters is vital to reduce their negative consequences. Vehicle routing models can make important contributions to faster response, and thus, save lives. This paper proposes a vehicle routing problem to deliver relief resources from origins to destinations in response to disasters. For this purpose, a multi-period, multi-depot, multi-trip mixed-integer linear programming model is developed. Minimizing the sum of arrival times is considered as a service-based objective function for the increase of the survival rate. For the first time, the problem is solved using a grouping metaheuristic algorithm. Then its performance is compared with two other grouping algorithms. To evaluate the solution method, the algorithms are implemented on various test problems and compared statistically. Additionally, to show the validity of the model, sensitivity analyses are performed and managerial insights are given. [ABSTRACT FROM AUTHOR]

Quality management has been widely discussed in the literature, and recent special issues on humanitarian supply chains and relief operations have emphasized the increasing importance of quality management in this key emerging area. In this paper, we provide an extensive literature review in the field of quality management in humanitarian operations and disaster relief management. Our comprehensive review, comprising 61 articles published from 2009 to 2018, leads to the identification of enablers (e.g., transparency, policy framework), challenges (e.g., financial services, identity protection), and theory development approaches, as well as numerous research gaps that must be addressed. [ABSTRACT FROM AUTHOR]

People are increasingly paying much attention to battery technology, especially the zinc-nickel battery and the lithium battery, for solving energy shortages and environmental contamination. Meanwhile, the drastic change in the external outside environment has brought a huge challenge to manage the battery industry chain. Therefore, in the uncertain external environment, the study of supply chain competition between lithium battery and new nickel battery manufacturers is the focus of this paper. We build a cooperative game model under the demand disturbance and a non-cooperative game under the background of product promotion. The results show that (i) the price set by the manufacturer increases with technical improvement when consumers are more sensitive to the technical level. (ii) The optimal price of all manufacturers will drop as the CETRC (carbon emission technology renewal coefficient) increases. (iii) The price of zinc-nickel batteries will be higher than that of lithium battery as the market promotion rate is in the middle range. In the model, the supply chain determines different optimal prices according to the different ranges of the demand disturbance. [ABSTRACT FROM AUTHOR]

The presence of geological hazards on the Sakhalin shelf creates difficulties in the design, construction, and maintenance of offshore oil and gas facilities. Identification and assessment of geological hazards in the coastal area of the northeastern shelf of Sakhalin Island will allow avoiding environmental disasters, minimizing the risks of accidents, and developing recommendations for ensuring safety in the development of oil and gas fields. The paper presents the results of an analysis of data from expeditionary surveys carried out at two sites using geophysical surveys and bathymetric surveys. The zones of ice gouging in the coastal part of site no. 1 caused by gouging of the seabed by stamukhas have been identified. Gas zones and paleo-incisions were found and mapped in the bottom part of the section at site no. 2. [ABSTRACT FROM AUTHOR]

Landslide susceptibility analysis based on the strong ability of data mining of Geographic Information System (GIS) has become a hot topic in international landslide research. This paper used optimized decision tree and GIS databases to analyze the sensitivity in the northwest mountain areas of Yunnan province of China, and then discussed the formation mechanism of the landslide happened in the area. The translational landslide located in the area with an average gradient less than or equal to 28.7° was reclassified as a higher level 3 sensitive area than before according to the normalized different fault index (NDFI). The results showed that the data mining based on GIS 3D space–time information database can help to find the unique topography, geology hydrology and the other typical spatial information of some special typed of landslides such as translational landslides, thus it can illustrate the relationship between the landslides and their sensitivity factors. The improved landslide susceptibility analysis will provide a new method for identifying the genetic mechanism of landslide, and play an important role in the government regional planning and disaster prevention measures. [ABSTRACT FROM AUTHOR]

Pacific Island countries are among the list of countries that face the highest disaster risk globally—in per capita terms. In recent years, governments in the region have been confronted by a rise in damages from extreme catastrophic events, many increasingly linked to climate change. These events pose significant challenges to Pacific governments in terms of maintaining fiscal stability and the operation of their limited and under-diversified economies and shallow financial sectors. Governments in the region generally play a leading role in domestic economies and are responsible for leading disaster prevention, mitigation, and recovery efforts. Accordingly, measures to improve financial sustainability and the public sector's ability to provide public services in the aftermath of major disasters must be prioritized. This paper examines the literature on fiscal resilience to disasters, the estimated impacts of major events in the Pacific, and analyses the applicability of available financial instruments to facilitate both ex ante and ex post disaster fiscal risk management in the region. The paper also discusses policies that can improve resilience against fiscal risks. [ABSTRACT FROM AUTHOR]

Underground coal mining activities are likely to cause changes in surface structure, resulting in damage to buildings, which seriously threaten the safety of life and property of the residents within the mining area. In this paper, the synthetic aperture radar time-series analysis method is combined with the building damage level empirical model to conduct a health assessment of the residential buildings in the Panji mining area of Huainan. Through the processing of 50 Sentinel-1A satellite radar images from April 2015 to May 2018, it is indicated that the residential areas in Huainan Panji Mining Area continued to be affected by underground coal mining during this period, and severe settlement occurred. Large areas of buildings in residential areas were damaged. Until May 2018, 202,000 m2 of buildings in the residential area of Panji mining have reached the Class II damage and 41,575 m2 have reached the Class III damage. After field investigation, the actual damage situation of the building is in good agreement with the results of this paper. Therefore, synthetic aperture radar time-series analysis combined with building damage level empirical model can be used as an effective tool for rapid and efficient deformation monitoring and health assessment of buildings. It is of great significance for the identification, early warning and disaster prevention decision making of such disasters. [ABSTRACT FROM AUTHOR]

Social vulnerability assessments of disaster risks related to natural or man-made hazards have become state of the art, while not undisputed. One critique—that most assessments are static—is addressed here by analysing indicators over a 10-year period at a research area in Germany using county-level administrative units. The indicators (and an index) are displayed as maps using publicly available statistical data from a single government source to establish consistency. In addition, maps of changes in indicator values per 5 or 10 years are visualised. As a result, spatial regions within Germany that have received increases in, for instance, higher numbers of elderly citizens can be visualised. Maps visualise the increasing susceptibility to hazards such as floods, heatwaves, storms or technological accidents. At the same time, increases or decreases in capacities, such as hospital density or care homes, highlight regions that have adjusted or still have to adjust to demographic change demands. The main purpose of this paper is to test stability and heterogeneity of indicators over time and offer advice on a selection of indicators that are not only based on static and singular assessments but also take dynamics and related richness of additional temporal change information into account for longitudinal monitoring of disaster risk with a focus on vulnerability. [ABSTRACT FROM AUTHOR]

Global warming of 1.5 °C above preindustrial levels and a commensurate increase in global greenhouse gas emissions pose an unprecedented danger to human settlements, livelihoods and the sustainable development of Small Island Developing States (SIDS), yet these challenges present tremendous opportunities to rethink development pathways. The paper has two objectives. One is to critically review present vulnerabilities and adaptation strategies employed by the state, private sector, non-governmental organisations, community-based organisations and households. The other is to discuss vulnerabilities and identify adaptation and resiliency strategies which are considered most applicable beyond the 1.5 °C limit. The Caribbean Region is the focus of the paper. A key finding of the paper is that temperature change above the 1.5 °C limit set by the Paris Conference of the Parties will make the natural and human systems of SIDS even more highly vulnerable than they are already. Another finding is that Caribbean states have implemented various innovative climate change adaptation strategies, but their relevance should the 1.5 °C target be exceeded, requires further exploration. The paper is useful to policymakers, decision-makers and finance agencies in search of practical solutions to avert the implications for Caribbean settlements, economies and ecosystems should the temperature warming exceed 1.5 °C. [ABSTRACT FROM AUTHOR]

Death, injury, conflict, and disorder caused by natural and man-made disasters have resulted in significant challenges to good governance and impeded the goal of achieving the benign development of society. This paper uses a particular method for analyzing the research situation and identifying current trends and focuses. It then proceeds to explore future research needs. The study finds that future researchers will shift their emphasis from the risks caused by natural disasters to those arising from man-made disasters; meanwhile, the study will consider the complex systems of interaction to understand causality. The objectives of management, hence, should change from investigating the impacts of risks to crisis control. Eventually, an evolutionary disaster-based social-risk framework is established, and some suggestions for future research are provided. [ABSTRACT FROM AUTHOR]

A critical prerequisite of risk prevention measures for natural hazards is from the results of forensic disaster investigations (FDIs). The current studies of the FDIs are limited by data issues including data availability and data reliability. The applications of crowdsourcing method in natural disasters indicate the potential to provide data support for the FDIs. However, there is very limited existing research on the use of crowdsourcing data for the FDIs. Following the requirements published by the Integrated Research on Disaster Risk program for FDIs, this paper establishes the process map for conducting the FDIs by scenario analysis approach with the crowdsourcing and crowdsensor data. Hurricane Harvey is used as the case study to implement the process map. The results show that the use of crowdsourcing data for the FDIs is feasible. Though this paper takes practical measures for improving the reliability of crowdsourcing data (i.e., little data size) in the case study, future research can focus on the development of advanced algorithm for the crowdsourcing data quality validation. [ABSTRACT FROM AUTHOR]

This paper deals with the challenges associated with modelling a friction-type shock indicator used during product distribution. Cost-effective mechanical shock indicators are widely used to reveal if a package has been subjected to a shock event exceeding a predetermined acceleration threshold. Such devices are an important part of the quality control and monitoring process during the distribution of fragile products. However, there is growing evidence that, in many cases, false detection or no detection have been experienced producing misleading information hence loss of confidence in the data. This paper describes the development and validation of a mathematical and numerical model that fully characterises the behaviour of a mechanical shock detector device. The device uses the displacement of a magnet when a pre-determined acceleration threshold is exceeded. The aim of the model is to assist in understanding the mechanical behaviour of the device and how it responds to different types of impulsive excitation. Modelling friction with a unary coefficient was found to have shortcomings and a more sophisticated approach to predict the effects of friction was developed. The numerical model was validated by producing a variety of excitation motions using a programmable actuator. The paper discusses the challenges associated with experimentally establishing the mechanical parameters of the device, especially friction coefficients, and shows that an adoption of the Stribeck friction model to characterise the motion of the magnet produces accurate results. [ABSTRACT FROM AUTHOR]

An introduction to articles published within the issue is presented on topics including social media platforms and disaster management, the use of microblogging platforms by emergency response organisations, and integrating social media from outside DM organizational boundaries.

At present, unmanned aerial vehicles (UAVs) have been widely used in communication systems, and the fifth-generation wireless system (5G) has further promoted the vigorous development of them. The trajectory planning of UAV is an important factor that affects the timeliness and completion of missions, especially in scenarios such as emergency communications and post-disaster rescue. In this paper, we consider an emergency communication network where a UAV aims to achieve complete coverage of potential underlaying device-to-device (D2D) users. Trajectory planning issues are grouped into clustering and supplementary phases for optimization. Aiming at trajectory length and sum throughput, two trajectory planning algorithms based on K-means are proposed, respectively. In addition, in order to balance sum throughput with trajectory length, we present a joint evaluation index. Then relying on this index, a third trajectory optimization algorithm is further proposed. Simulation results show the validity of the proposed algorithms which have advantages over the well-known benchmark scheme in terms of trajectory length and sum throughput. [ABSTRACT FROM AUTHOR]

Cascading failure in metro networks is a dynamic chain process induced by the interaction of passenger flow and network topology. In this paper, a bi-directional coupled map lattice model is proposed to study the cascading failure of metro networks. The model considers the two-way traffic problem, and the results are closer to those of actual metro networks than the previous one-way coupling models. A η -based flow redistribution method is proposed, and different passenger flow redistribution strategies after station failure can be achieved by changing the flow redistribution coefficient η from 0 to 1. Moreover, the robustness of metro networks can be optimized by searching for the optimal η that can maximize the critical perturbation leading to global network failure. We study the actual case of Nanjing metro. The analysis results show that the network is more vulnerable to intentional attacks than to random failures, and global network failure is triggered more easily on the largest strength station than on the stations with the largest betweenness and largest degree. The influence of coupling strengths on the critical perturbation is also investigated. The results show that larger coupling strengths correspond to smaller critical perturbations, but a change in the coupling strengths has a small impact on the optimal η . Under the given traffic data, the optimal η for Nanjing metro is approximately in the range (0.3, 0.4). This study provides a reference for developing strategies for dynamic safety evaluation and emergency management of passenger flow in metro networks. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has exposed a suboptimal response to this threatening global disaster, including the response to the psychological impact. Both the economic hardship and the continuous media coverage of alarming news have exacerbated this effect which also includes increased domestic violence. Aim: To address this important aspect of disaster management and provide recommendations on how to mitigate these effects. Methods: This is a narrative review written by three experts in community medicine, disaster medicine and psychiatry reflecting the interdisciplinary approach in managing disasters. Selected important papers, personal published papers, PUBMED articles and media news related to the disaster management of the psychological effects of COVID-19 pandemic were collected over the last year, critically appraised and used in writing this manuscript. Results: The COVID-19 pandemic causes major emotional distress. Lack of effective treatments and availability of the current vaccines for this virus increases the fear of being infected and infecting others. Negative emotions are common and are related to adjustment but may progress in the long term to anxiety, depression, and post-traumatic stress syndrome. The COVID-19 pandemic has a major impact on mental health. The most common distress reactions include anxiety, insomnia, perception of insecurity, anger, fear of illness, and risky behaviors. Patients having mental disorders are vulnerable during the pandemic because of (1) somatic vulnerability, (2) cognitive and behavioral vulnerability, (3) psychosocial vulnerability, and (4) disruption to psychiatric care. Psychiatric wards, which are commonly separate from main hospitals, should be included in the disaster management plans. Acute care physicians carry the psychological and ethical impact of difficult triage decisions when ending the support of some patients to save others. A combination of fear and guilt may overcome normal human tolerance levels in vulnerable health workers. The moral injuries can be carried for a long time. Conclusions: Addressing the psychological effects is an essential component of disaster management of infectious pandemics. This should be implemented through the whole spectrum of disaster management including preparedness, mitigation, response, and recovery. [ABSTRACT FROM AUTHOR]

Due to China's exposure and susceptibility to natural hazards, it is important for governments and aid agencies to have tools that enable effective post-disaster livelihood recovery in creating self-sufficiency for the affected population. This paper introduces a framework of critical components that constitute a successful livelihood recovery by studying the perceptions and perspectives of those affected by the 2013 Lushan earthquake in Sichuan Province. A mixed method, namely a pilot study, questionnaire survey and interviews, was used. While the populations surveyed valued the employment benefits of creating new market and economic sectors in areas where rural farming was predominant prior to the earthquake, they considered that recovery of their housing was most essential for livelihood diversification. External assistance was also regarded highly in assisting with livelihood recovery, in which family ties and social connections seemed to have played a larger role than that of government agencies and NGOs. Lastly, the results highlighted that a goal of livelihood recovery cannot be achieved without individual well-being being considered, in relation to people's perceptions about quality of life and their physical and mental health. This paper aims to assist the Chinese policy makers and practitioners in disaster recovery in setting an agenda of preparing for livelihood recovery in peace times, or of post-disaster recovery planning should a disaster event occurs so that the economic impact and livelihood burdens of those affected can be effectively mitigated. [ABSTRACT FROM AUTHOR]

Nowadays the fuzzy graphs gained popularity due to their wide applications in different areas of science, engineering, social sciences, etc.In this paper, we consider covering problem in fuzzy graph. Different types of covering problems have been defined in this paper. Almost all problems are new. For each of these problems separate study is required. Also, the covering set, strong covering set, minimal covering set, etc., are defined and explained with examples. In a graph, each vertex can cover only those vertices that lie within its covering radius along shortest path and no vertex can cover itself. Here, an algorithm is designed to find the different types of covering sets on a fuzzy graph. An imprecise number, instead of a real number, namely interval number and triangular fuzzy number are considered as arc length of a fuzzy graph. To the best of our knowledge no works are available for covering problem on fuzzy graphs/networks. An application of covering set in natural disaster management is discussed to highlight the importance of the covering problem. In this application, an algorithm is designed to find all the facility vertices (or supply vertices) for given vertex and covering radius. [ABSTRACT FROM AUTHOR]

The strong spatial nonuniformity of dam soil is a key factor for studying the safety and stability of landslide dams. In this paper, a 500 × 500 × 500 mm cubic model box was made, and the dam soil was deposited in it by layered deposition and different sliding angles to investigate the nonuniformity of the deposition. The depositional characteristics and particle size distribution (PSD) variations in different zones of different depositions were analyzed. Furthermore, based on the basic principle of grading entropy, the particle distributions of different depositions using the entropy parameter A−B coordinates were discussed. Finally, an index of nonuniformity Nd was proposed to quantitatively assess the nonuniformity degree of the deposition. We yielded that as the sliding angle increased, the deposition showed prominent sorting characteristics in the sliding direction. The coarser and finer particles were mainly concentrated in the front and back parts of the deposition, respectively. Compared with the traditional characteristic parameters, the grading entropy is more meticulous for characterizing the PSD curve. In the entropy parameter A−B coordinates, the points for the expected uniform deposition are more concentrated, which indicates that the nonuniformity of this deposition is smaller. The points of different zones for the sliding deposition are arch-shaped, and their distribution is more dispersed and directional in these coordinates, which indicates a greater nonuniformity of this deposition. For the sliding deposition, the index of nonuniformity Nd of different depositions tends to increase and then decrease with increasing sliding angle. The Nd of the deposition made by the sliding angle of 60° is the largest at 0.173. However, that of the expected uniform deposition is only 0.057. This study improves the understanding of spatial nonuniformity and aids the disaster prevention and mitigation of landslide dams. [ABSTRACT FROM AUTHOR]

Urban rainstorm and waterlogging occurred more frequently in recent years, causing huge economic losses and serious social harms. Accurate rainstorm and waterlogging simulation is of significant value for disaster prevention and mitigation. This paper proposed a numerical model for urban rainstorm and waterlogging based on the Storm Water Management Model (SWMM) and Geographic Information System (GIS), and the model was applied in Lianhu district of Xi'an city of China. Furthermore, the effects of rainfall characteristics, pipe network implementation level and urbanization level on waterlogging were explored from the perspectives of spatial distribution of waterlogging points, drainage capacity of pipe network and surface runoff generation and confluence. The results show that: (1) with the increase of rainfall recurrence period, the peak of total water accumulating volume, the average decline rate of water accumulating volume and the number of waterlogging nodes increase; (2) optimizing the pipe diameter can shorten the average overload time of the pipe network from the entire pipe network, but for a single pipe, optimizing the pipe diameter may lead to overloading of unoptimized downstream pipeline; (3) the lower the imperviousness, the less the number of waterlogging nodes and average time of water accumulating, and (4) the west, northwest and southwest areas are relatively affected by the imperviousness, only improving the underlying surface conditions has limited influence on waterlogging in the study area. This study can provide reference for urban waterlogging prevention and reduction and pipe network reconstruction. [ABSTRACT FROM AUTHOR]

In this paper, we discuss rescue planning for disaster victims trapped in a partially collapsed multistory building. Before the rescue teams enter the building, the number and approximate locations of victims should be determined leading to efficient planning of the search and rescue paths for saving more lives. We develop the MLOCATE algorithm based on the assumption that several victims have cell phones and the paths are partially intact. The MLOCATE algorithm performs localization and clustering of victims. Next, the rescue priorities of the clusters and floors are computed. Finally, prioritized paths are presented in visual format, avoiding obstructions introduced due to debris or fire. The results of simulation run of the algorithm are discussed showing quick and efficient rescue path planning. [ABSTRACT FROM AUTHOR]

Applications such as disaster management enormously benefit from rapid availability of satellite observations. Traditionally, data analysis is performed on the ground after being transferred—downlinked—to a ground station. Constraints on the downlink capabilities, both in terms of data volume and timing, therefore heavily affect the response delay of any downstream application. In this paper, we introduce RaVÆn, a lightweight, unsupervised approach for change detection in satellite data based on Variational Auto-Encoders (VAEs), with the specific purpose of on-board deployment. RaVÆn pre-processes the sampled data directly on the satellite and flags changed areas to prioritise for downlink, shortening the response time. We verified the efficacy of our system on a dataset—which we release alongside this publication—composed of time series containing a catastrophic event, demonstrating that RaVÆn outperforms pixel-wise baselines. Finally, we tested our approach on resource-limited hardware for assessing computational and memory limitations, simulating deployment on real hardware. [ABSTRACT FROM AUTHOR]

Natural disasters are very unexpected in human life. The best prevention from such natural disasters is an early warning system which gives a good period to take some necessary measures during the occurrence of disasters. Social media is the best medium to broadcast ominous massages and this can be done by integrating the internet of things with Social Networks. This paper proposes pre-identification of communities that may expose to natural disasters and identification of the best node where the broadcasting system can be placed. A smart broadcasting device that includes a Programmable IoT board like Raspberry Pi or Jetson Nano can be placed at a node with high centrality. The proposed work is very useful to prevent human causality by issuing early warnings of natural disasters like rain flooding, the collapse of old buildings, old bridges, earthquakes, land sliding. [ABSTRACT FROM AUTHOR]

Implementing management practices for the control of invasive species can be a complex task with multiple dimensions, where the identification of stakeholders and drivers of those practices is of paramount importance. The invasive hornet Vespa velutina has spread across Europe and Asia from its native range in SE Asia in recent years. A common control method is the removal and destruction of its nests on citizens' request to call centers. In this paper we have explored the knowledge and main factors that influence the perceptions of the citizens on the species in an invaded municipality in NW Spain, as well as the management practices of the municipal emergency unit responsible for nest removal activities. Our analysis brings out multiple drivers of management practices that derive both from the citizens' and practitioners' knowledge, and highlights several points of conflict between both stakeholder groups connected to (1) the degree of service provided to the local population, (2) the risk of allergic reactions as a motive to urge removals, or (3) the quality of information provided by mass media. Our results support the crucial importance of environmental education programs that seek to increase the knowledge of the general public about the threats of invasive species. Such programs might be incorporated to implement and optimize management plans of V. velutina by enhancing communication between experts and local population. [ABSTRACT FROM AUTHOR]

Using geolocated tweets to achieve situational awareness is an often researched topic in disaster and emergency management. However, little has been done in the area of drug cartels, which, as transnational crime organizations, continue to pose great risk to the stability and safety of our communities. This paper made an initial effort in using geolocated social media (specifically Twitter) to achieve situational awareness of drug cartels through temporal and spatial analysis of derived named entity clusters. The results show that detecting peaks in the time series of frequently occurring entity clusters enabled the tracking of important events in public discourse surrounding drug cartels. Correlations between time series also provided valuable insights into the synchronicity between different events. Further examining the spatial distribution of key events for different countries, we identify thematic hotpots of public discourse on cartel activity. Our methodology also addresses issues of language ambiguity when working with noisy social media data in order to achieve situational awareness on drug cartels. [ABSTRACT FROM AUTHOR]

Many of Iraqi's high-hazard dams lack an Emergency Action Plan, which should include a flood inundation map to show which downstream areas would be flooded if the dams were to fail. This article presents the results of the simulation of a hypothetical 2D dam break for the 58 m high Khassa Chai dam in Kirkuk, Iraq, using HEC-RAS 2D 5.0.7 software. The Khassa Chai dam is situated 7.4 km north of Kirkuk. The simulations revealed that the dam-break flood will affect eight major bridges and the majority of Kirkuk city's metropolitan neighborhoods. Within an hour, the floodwaters will reach the city's center. The flood hazard map revealed that if the Khassa Chai dam fails, many people, vehicles, and structures will be at danger. The findings of this paper can be used to identify evacuation routes and refuge sites as well as build suitable warning systems in order to limit the risk for fatalities if the Khassa Chai dam fails. Moreover, as the effect of modeling bridges downstream of failed dams has not been explored yet, to the knowledge of the authors, eight bridges have been modeled. It was concluded that ignoring bridges in such a large dam break model will not affect the results significantly, which saves the time of data collection and model development. [ABSTRACT FROM AUTHOR]

Fast and accurate semantic analysis of natural disaster images is crucial for rational rescue plans and resource allocation. However, the scarcity of meticulously labelled datasets and the ignorance of region-of-interest scale variations of popular general-purpose methods lead to undesirable performance. In this paper, we propose a novel triple-strip attention mechanism (TSAM) to solve the generalization problem of disaster images that can be combined into general networks. Our TSAM accumulates features of three parallel-strip attentions (row strip attention, column strip attention, and channel strip attention), and the output is multiplied with original input features for further processing. Our attention mechanism can effectively overcome the defect of ignoring global features caused by the convolution and enhance the performance of the network by weighting the features from both spatial and channel aspects more comprehensively. Besides, we employ both the compression and expansion operations in the weighting operation to reduce the amount of parameters, leading to negligible computational overhead. Experiments validate that our TSAM outperforms other state-of-the-art methods on natural disaster segmentation. Due to its concise form, plug-and-play pattern, and high promotion rate, our TSAM can be combined with many existing neural networks for better performance improvement. [ABSTRACT FROM AUTHOR]

Landslide susceptibility assessment is highly valuable for disaster prevention and mitigation. This study utilized the aspects of data and content to comprehensively examine the research status of landslide susceptibility. First, we used CiteSpace to visually analyze papers with "landslide susceptibility" as their theme word in the Web of Science database from 1991 to 2020. Next, we summarized the characteristics of quantitative trends, journals, authors, organization types, and keywords, and created a map of authors, institutions, and keywords. Then we presented the common methods and their advantages and disadvantages of landslide inventory, evaluation index, evaluation unit, evaluation model and verification method, combs the shortcomings of each part at the present stage, and looks forward to the possible research direction in the future. Finally, the research difficulties of landslide susceptibility in spatial scale, qualitative and quantitative problems, and spatial representation of landslide information are discussed. We find that the development of 3S and new technology in computer field promotes the development of landslide susceptibility research, makes landslide inventory more efficient and accurate, makes the assessment factor system considering factor contribution more reasonable, and makes more intelligent models applied to landslide susceptibility research. The results are beneficial for researchers to understand the current landslide susceptibility condition and can provide a reference for subsequent landslide susceptibility studies. [ABSTRACT FROM AUTHOR]

A country's preparedness to face crises is a multidimensional competence that depends on several attributes (economic factors, governance features, infrastructure and institutional endowments). This paper proposes a new approach to rank countries based on their degree of preparedness to deal with large-scale crises. The measured characteristics of countries have made it possible to compile an index of preparedness to face shocks and, therefore, predict their performance against the COVID-19 health crisis to verify the relevance of the proposed composite index. Fortunately, it appears that countries with a high degree of preparedness according to our aggregate index were able to respond adequately and effectively to this crisis. This is reflected in a lower mortality rate and more administered tests. [ABSTRACT FROM AUTHOR]

Three consecutive typhoons hit Korea within a short period not only in 2012 (typhoons Bolaven, Tembin, and Sanba) but also in 2020 (typhoons Bavi, Maysak, and Haishen). This paper aims to explore how the tracks of typhoons that occur within short intervals can be predicted accurately, toward achieving the ultimate goal of disaster management. The key finding is that the tracks of the three typhoons in 2012 and 2020 moved sequentially from west to east due to the North Pacific anticyclone, the prevailing weather systems, and the Earth's rotation. This knowledge is useful in predicting the tracks of future typhoons in Korea, as well as in enhancing disaster mitigation, disaster preparedness, and psychological relief efforts. [ABSTRACT FROM AUTHOR]

Tropical cyclones are among the most detrimental hazards to the environment, societies, and economies, each year affecting millions of people and resulting in substantial casualties and material destructions in coastal communities. In this context, maritime cultural heritage, encompassing material evidence for the engagement of people with the sea, both on land and under water, is particularly vulnerable. Despite the significant number of archaeological sites exposed to tropical cyclones and other extreme sea-level events, maritime cultural heritage in the MENA region is rarely included in coastal vulnerability indices or incorporated in mitigation strategies, disaster management, sustainability, and resilience policies. In this study we examine the impact of tropical cyclones on the maritime archaeology of Oman with emphasis on the Dhofar region. This paper builds on existing coastal research in the Dhofar region—an area identified as the most cyclone-prone administrative region in Oman, but also an area that contains substantial archaeological remains. Central among Dhofar's maritime cultural heritage is Al-Baleed, a Medieval seaport with unparalleled evidence of engagement with international trade networks. [ABSTRACT FROM AUTHOR]

The summer monsoon–affected area is a suitable area for agricultural production in China. Against the background of climate warming, the activity of the summer monsoon is changing significantly. The drought and flood disasters in this region are becoming more and more frequent and have a greater and more serious impact on agricultural production. Therefore, based on observational data from meteorological stations and yield loss data in agriculture caused by drought and flood disasters in summer monsoon–affected areas, this paper studied the characteristics of the hazard of disaster-causing factors, the risk of losses to agriculture caused by droughts and floods, and their correlation. Moreover, it compared and analyzed the variability of drought and flood hazard and risk to agriculture before and after a temperature rise. The results showed that the precipitation in summer monsoon–affected areas is obviously affected by monsoon activities, and there is an overall though non-significant positive correlation between annual average standardized precipitation evapotranspiration index (SPEI) and the summer monsoon activity index (MI). The drought disaster comprehensive loss rate (DCLR) was generally higher than the flood disaster comprehensive loss rate (FCLR). This shows that the impact of drought on agriculture production is significantly greater than that of floods in this area. The high hazard and risk areas for drought were mainly distributed along the edge of the summer monsoon area and in its vicinity, whereas the high hazard and risk areas for flooding were mainly distributed in the lower reach of the Yangtze, Songhua, and Liaohe Rivers. Among them, Liaoning, Jilin and Heilongjiang are high-risk superposition areas of drought and flood disasters. The hazards of drought and flood dominate the risk of disaster loss. Climate warming has significantly expanded the high-hazard and high-risk ranges in China for drought and flood disasters and has also changed their spatial distribution patterns. The high-hazard area for drought has shifted to the monsoon edge area, the high-risk area for drought has moved northward, and both the high-hazard and the high-risk areas for floods have clearly moved southward. The impact of climate warming on drought was more significant than on floods. This study provides important scientific guidance for formulating drought and flood disaster prevention planning and agricultural production development patterns in China. [ABSTRACT FROM AUTHOR]

Over the past decade, the cost of disasters on lives and livelihoods has increased many folds. However, there are few tools available that can be used to measure the level of livelihood preparedness for disruptions caused by natural hazards. By studying the experience and perceptions of communities affected by the 2016 Kaikōura earthquake in New Zealand, this paper aims to develop an assessment tool for measuring livelihood preparedness. Results from a survey of 140 residents in Kaikōura who lived through the earthquake and its aftermath identified four indicators of livelihood preparedness, namely (1) resource accessibility, (2) individual adaptive capacity, (3) livelihood diversity, and (4) the effectiveness of disaster risk reduction (DRR) measure. Structural equation modelling approach was used to establish the quantification of these four indicators, and as a result, a numerical model was developed that can be used as a tool to assess livelihood preparedness at an individual level. It is hoped that this tool will be used by policymakers and individuals living in hazard prone locations to evaluate livelihood preparedness prior to a disaster to facilitate improvement or as a forensic tool post disaster. [ABSTRACT FROM AUTHOR]

Emergency management with oil spill is a very complex decision problem. This paper targets efforts to propose and develop a new technology: an extension of grey relational analysis for facilitating group consensus model to deal with this problem. In this model, firstly, two parts of the extension of grey relational analysis are presented and proposed. One is to simultaneously compute grey relational degree to positive reference sequence (PRS) and negative reference sequence (NRS), on the basis of the basic concept of a relative closeness degree of TOPSIS. The other is to determine index weights by a developed mathematical optimization model implemented by Matlab 2012a, which also matches the basic concept of the first part of the extension. Secondly, a group consensus facilitation method based on three-dimension leg-mark selected location method is proposed to aggregate individual preferences in order to address the problem of ranking inconsistency during the evaluation of multi-criteria decision making methods. What's more, the calculation steps and processes of n-dimension leg-mark selected location method for facilitating group consensus are given and explored. A simulation case study on oil spill emergency management demonstrates and verifies the feasibility and effectiveness of our proposed model by comparative analysis with the previous research papers. [ABSTRACT FROM AUTHOR]