Emergency Management Capability Research Articles

Urban community security system model from the perspective of resilience: a study on Chinese cities

To enhance urban governance and bolster community disaster resilience, it is urgent to innovate and develop an urban community security system to cope with the complex and volatile social security situation. From the perspective of resilience, the concept, layout, and structure of the security system are organized. Considering the current situation and development trend of the social security system, and based on the constructed cost-capability model, the cost and benefit of the two modes are analyzed and compared. Subsequently, from the perspective of multi-agent participation, a game model between governments and enterprises is constructed. The evolutionary stability strategies of enterprises are analyzed, and simulation analysis is conducted on the factors influencing enterprises. Finally, to propose targeted improvement measures based on the community security capabilities of different communities, a grey fuzzy comprehensive evaluation method is employed. The community security comprehensive capabilities of the top 10 cities in China are quantitatively analyzed and evaluated. The results indicate that the urban community security system from a resilience perspective is more comprehensive compared to the traditional security system. Adopting mode 2 is relatively effective to improving government emergency management capability. In a certain range, reducing C, increasing F, reducing R2, and increasing h can achieve the effect of promoting enterprise to participate in construction. The urban community security capability is within the upper-medium level in general, close to the level of good. The urban community security system constructed in this paper can provide a theoretical basis for the government to formulate policies of the urban community security system and serve as a reference for strengthening the comprehensive capability of the urban community security.

Turning every disaster into an opportunity: An exploratory study on refugees’ perceived emergency management capacity and community resilience

This article explores the perceived emergency management capabilities and community resilience among refugees residing in Texas. Adopting the theoretical framework of structural and cognitive social capital, we conducted in-depth interviews with refugees from Afghanistan, Congo, Iran, Myanmar, Somalia, and Thailand. The study identifies the specific needs of the refugee community regarding disaster management and their simultaneous vulnerability and resilience. Based on our research findings, we suggest that local disaster management agencies identify and collaborate with the community leaders in refugee communities to efficiently achieve their communication goals, strengthen refugees' community resilience, and better integrate refugee communities into the local community's resilience development.

A study of collaborative governance of online users tourism information (Revision 2)

ABSTRACT With the rapid development of the Internet, the spread of tourism information is more rapid, and tourism information governance is increasingly important. This research adopts a system dynamics approach to construct a system dynamics model of collaborative tourism information governance from government, netizens, tourism enterprises, and the information itself, using the Huangshan information as a case study. The results show that the impact of ‘information popularity’ is the largest, ‘government credibility’ in the second place; ‘emergency management capability of tourism enterprises’, ‘the intensity of information disposal efforts’ and ‘role of opinion leaders’ have the weak influence to the tourism information governance. It is proposed to improve the public’s judgment, strengthen its judgment, improve the efficiency of the use of official media, promote the openness of information, and encourage the government to take the initiative and increase the level of interaction, strengthen the emergency management training of tourism enterprises, improve the ability to respond to the leading role of opinion leaders, correct guidance and other strategies.

Government's public panic emergency capacity assessment and response strategies under sudden epidemics: A fuzzy Petri net-based approach

In the post-epidemic era, public panic has emerged as a highly significant secondary disaster, necessitating an urgent enhancement of emergency management capabilities by governments at all levels. In order to ensure a robust assessment of the government's ability to manage public panic, it is crucial to effectively address the influence of uncertain and ambiguous factors associated with such scenarios. This paper proposes a governmental public panic emergency management capability assessment method based on fuzzy Petri nets. By analyzing the factors influencing public panic across the four evolutionary stages, namely gestation, outbreak, diffusion, and fading, we establish a hierarchical evaluation index system for assessing emergency management capabilities. Additionally, we develop a range of multi-scenario emergency management strategies. To address the challenges posed by uncertainty, randomness, fuzziness, and insufficient statistical data within the assessment index system, we introduce fuzzy Petri nets and fuzzy reasoning rules to evaluate the emergency management capability of the assessment system and derive the optimal emergency management strategy. According to example simulations, the effectiveness and practicality of models and rules constructed using fuzzy Petri nets are demonstrated, highlighting their superiority over traditional assessment methods. This comprehensive approach equips the government with a versatile toolkit for effectively managing public panic emergencies.

Methods for Constructing a Refined Early-Warning Model for Rainstorm-Induced Waterlogging in Historic and Cultural Districts

Against the backdrop of increasingly severe global climate change, the risk of rainstorm-induced waterlogging has become the primary threat to the safety of historic and cultural districts worldwide. This paper focuses on the historic and cultural districts of Beijing, China, and explores techniques and methods for identifying extreme rainstorm warnings in cultural heritage areas. Refined warning and forecasting have become important non-engineering measures to enhance these districts’ waterlogging prevention control and emergency management capabilities. This paper constructs a rainstorm-induced waterlogging risk warning model tailored for Beijing’s historical and cultural districts. This model system encompasses three sets of models: a building waterlogging early-warning model, a road waterlogging early-warning model, and a public evacuation early-warning model. During the construction of the model, the core concepts and determination methods of “1 h rainfall intensity water logging index” and “the waterlogging risk index in historical and cultural districts” were proposed. The construction and application of the three models take into full account the correlation between rainfall intensity and rainwater accumulation, while incorporating the characteristics of flood resilience in buildings, roads, and the society in districts. This allows for a precise grading of warning levels, leading to the formulation of corresponding warning response measures. Empirical tests have shown that the construction method proposed in this paper is reliable. The innovative results not only provide a new perspective and method for the early-warning of rainstorm-induced waterlogging, but also offer scientific support for emergency planning and response in historical and cultural districts.

What Leads to Effective Emergency Management? A Configurational Analysis of Empirical Cases of Local Chinese Governments

This study investigates the foundational elements that contribute to effective emergency management in urban settings, with a particular focus on experiences from Chinese municipalities. Drawing on resource dependence theory and attention allocation theory, this research develops an analytical framework encompassing four pivotal factors: environmental resources, information sharing, social participation, and leadership attention allocation. Utilizing Qualitative Comparative Analysis (QCA), we examine these factors across sixteen critical incidents of urban accidents and disaster responses in China. Our findings reveal that a high degree of leadership attention allocation is an essential prerequisite for municipal governments to exhibit robust emergency management capabilities during crises. Furthermore, two primary pathways affecting emergency management capacity were identified: the “resource–leadership attention type” and the “social participation–resource coordination type”. These findings contribute to a nuanced understanding of the complexities of emergency management and enlighten the local governments to take some effective measures to enhance emergency management capacities to mitigate disaster losses.

Enhancing urban emergency management: A two-stage network DEA analysis of Chinese cities

In order to scientifically evaluate the emergency management capabilities of major cities in China, this article conducts a comprehensive study on the input and output indicators of emergency response in each city. A two-stage network DEA model was used to construct an evaluation model that reflects the emergency management capacity of cities. A dataset containing emergency management data from 36 well-known cities in China was selected to effectively evaluate its performance, and the city that demonstrated the most effective input-output ratio in the field of emergency management was ultimately determined. The research results show that using a two-stage network DEA model as the foundation to construct an evaluation model that reflects urban emergency management capabilities can promote a wise combination of subjective and objective evaluations, and achieve scientific investment in urban emergency assets.

Challenges in managing emergency offshore: A comparison of offshore and onshore perspectives

Three segments, which are the upstream, midstream, and downstream, make up the oil and gas business. At each stage of these oil and gas operations, there are differences in hazard and risk management that affect emergency management. Offshore emergency management presents more challenges compared to onshore emergency management, this is largely due to the remote and harsh environment, limited resources, and potential risk to human lives. The type of emergency also affects the level of challenge faced by offshore and onshore emergency management. The Covid-19 pandemic has had a major impact on effective emergency management in the oil and gas industry, requiring companies to adapt and adjust their emergency response plans, procedures, and technology to ensure the safety of personnel and the public while maintaining effective emergency management capabilities. The main objective of this study is to identify the challenges of emergency management and compare the offshore and onshore emergency management processes based on the element of effective emergency management. Document review using the PRISMA analysis was applied to compare offshore and onshore emergency management based on a review of 22 articles. The PRISMA analysis identified 22 relevant studies that covered a range of topics related to emergency management, including command structures, planning and information management, communication, situation awareness, and resources and logistics. Thereafter, the face validity method was used to examine the perspective of 10 emergency management professionals to validate these findings. Offshore and onshore facilities both possess different risks in emergency situations. Based on the results, it is essential to manage command structure, planning, information management, communication, situation awareness, resources, and logistics during disaster response and recovery stages. These five elements are critical to emergency management. Both offshore and onshore emergency management have their own unique challenges in resource constraints, weather conditions, accessibility and communication.

An integrated group decision-making framework for evaluating the urban fire emergency management capability based on PDHLWPHM and PDHLWPGHM operator

Urban fire accident is a common dangerous accident in urban sudden accidents, which threatens the safety of people’s lives and property. For this reason, in recent years, all cities have incorporated the prevention and emergency management of urban fire accidents into their urban development planning, and actively improved their fire accident emergency management capabilities. However, how to evaluate the urban fire accident emergency management capacity of each city to ensure that people’s lives and property are protected to the greatest extent is an urgent problem to be considered and solved. Therefore, this paper defines a class of probabilistic double hierarchy linguistic Heronian mean (PDHLHM) operator, probabilistic double hierarchy linguistic Power Heronian mean (PDHLPHM) operators, and their dual operators that can reflect the relationship between two attributes during aggregation. Taking urban fire accident risk monitoring and early warning capability, fire infrastructure and communication system, fire-fighting and rescue capability, recovery and reconstruction capability as evaluation attributes, the probabilistic double hierarchy linguistic weight Power Heronian mean (PDHLWPHM) operator model and the probabilistic double hierarchy linguistic weight Power geometric Heronian mean (PDHLWPGHM) operator model are constructed for group decision-making. In addition, the idempotence, boundedness and monotonicity of these operators are studied, and the sensitivity of the parameters involved in the operator model is analyzed. Finally, the new model proposed in this paper is compared with the existing model to verify its scientificity.

Research on Emergency Management of Public Emergencies in Cruise Ports under the Strategy of Free Trade Port in the Context of Informatisation

Abstract The emergency response capability of cruise ports to public emergencies is related to the development of various industries and plays an important role in economic construction and social development. An evaluation system for cruise port’s emergency management and risk warning ability is established based on the 4R crisis management model and enterprise risk warning model in this paper. The subjective weights calculated by the G1 method and the objective weights solved by the COWA operator are combined by the linear weighting method in order to realize the accuracy and objectivity of the index weights. Then the object element topable model is introduced to comprehensively evaluate the emergency management and risk warning capability of cruise ports, and S International Cruise Port is used as an example to verify the validity. The results show that the weight value of emergency response capability in the emergency management capability is 0.3552, and the weight of equipment and facility performance in the risk warning capability reaches 0.3548, and the emergency management and risk management capabilities of the cruise port are significantly correlated at the 10% level. The comprehensive evaluation of the emergency management and risk warning capability of cruise ports can be realized by using the object element topable model, which can provide a guarantee for the improvement of the emergency management capability of cruise ports in public emergencies.

The Mine Emergency Management Capability Based on EWM-CNN Comprehensive Evaluation

By establishing an evaluation system for emergency management capability for coal mine enterprises, the problems and shortfalls in coal mine emergency management can be identified. Moreover, this evaluation method holds promise in enhancing the ability to respond to emergencies in coal mines. The current research conducts both theoretical analysis and field research to determine and extract 26 factors that impact the emergency management capability of coal mining companies. The collected data is analyzed using SPSS version 24.0 and undergoes reliability and validity assessments. Subsequently, the entropy weight technique is utilized to determine the weight of individual evaluation system indices. As an effective evaluation tool, the trained convolutional neural network (CNN) model can accurately and effectively predict the satisfaction of the samples outside the training sample set, providing suggestions for improving coal mine emergency management. The trained model is employed to make empirical predictions and analyze the XY coal mine. The findings indicate that the overall emergency management capacity of the coal mine is II, which is at a good level. The evaluation results are consistent with the actual situation, and suggestions are provided for improving the emergency management ability of coal mines.

Emergency entity relationship extraction for water diversion project based on pre-trained model and multi-featured graph convolutional network.

Using information technology to extract emergency decision-making knowledge from emergency plan documents is an essential means to enhance the efficiency and capacity of emergency management. To address the problems of numerous terminologies and complex relationships faced by emergency knowledge extraction of water diversion project, a multi-feature graph convolutional network (PTM-MFGCN) based on pre-trained model is proposed. Initially, through the utilization of random masking of domain-specific terminologies during pre-training, the model's comprehension of the meaning and application of such terminologies within specific fields is enhanced, thereby augmenting the network's proficiency in extracting professional terminologies. Furthermore, by introducing a multi-feature adjacency matrix to capture a broader range of neighboring node information, thereby enhancing the network's ability to handle complex relationships. Lastly, we utilize the PTM-MFGCN to achieve the extraction of emergency entity relationships in water diversion project, thus constructing a knowledge graph for water diversion emergency management. The experimental results demonstrate that PTM-MFGCN exhibits improvements of 2.84% in accuracy, 4.87% in recall, and 5.18% in F1 score, compared to the baseline model. Relevant studies can effectively enhance the efficiency and capability of emergency management, mitigating the impact of unforeseen events on engineering safety.

Research on the collaborative evolution process of information in public health emergencies based on complex adaptive system theory and social network analysis: a case study of the COVID-19 pandemic.

This review aimed to elucidate the significance of information collaboration in the prevention and control of public health emergencies, and its evolutionary pathway guided by the theory of complex adaptive systems. The study employed time-slicing techniques and social network analysis to translate the dynamic evolution of information collaboration into a stage-based static representation. Data were collected from January to April 2020, focusing on the COVID-19 pandemic. Python was used to amass data from diverse sources including government portals, public commentary, social organizations, market updates, and healthcare institutions. Post data collection, the structures, collaboration objectives, and participating entities within each time slice were explored using social network analysis. The findings suggest that the law of evolution for information collaboration in public health emergencies primarily starts with small-scale collaboration, grows to full-scale in the middle phase, and then reverts to small-scale in the final phase. The network's complexity increases initially and then gradually decreases, mirroring changes in collaboration tasks, objectives, and strategies. The dynamic pattern of information collaboration highlighted in this study offers valuable insights for enhancing emergency management capabilities. Recognizing the evolving nature of information collaboration can significantly improve information processing efficiency during public health crises.

Dynamic Dose-Based Emergency Evacuation Model for Enhancing Nuclear Power Plant Emergency Response Strategies

The safe evacuation of residents near a nuclear power plant during a nuclear accident is vital for emergency response planning. To tackle this challenge, considering the dynamic dispersion of radioactive materials in the atmosphere and its impact on evacuation routes under different meteorological conditions is crucial. This paper develops a dynamic dose-based emergency evacuation model (DDEEM), which is an efficient and optimized nuclear accident evacuation model based on dynamic radiological dose calculation, utilizing an improved A* algorithm to determine optimal evacuation routes. The DDEEM takes into account the influence of radiological plume dispersion and path selection on evacuation effectiveness. This study employs the DDEEM to assess radiological consequences and evacuation strategies for students residing 5 km from a Chinese nuclear power plant. Under various meteorological conditions, including the three typical meteorological conditions, random ordered and random unordered meteorological sequences, optimal routes obtained through the DDEEM effectively reduce radiological dose exposure and mitigate radiation hazards. The results indicate that all evacuation paths generated by the DDEEM have a maximum dose of less than 1 mSv. Through simulations, the model’s effectiveness and reliability in dynamic radiological environments in terms of radiological consequences and evacuation analysis is verified. The research provides valuable insights and a practical tool for nuclear power plant emergency decision-making, enhancing emergency management capabilities during nuclear accidents. The DDEEM offers crucial technical support and a solid foundation for developing effective emergency response strategies.

Evaluation of Community Emergency Management Capability Based on SWOT Analysis—A Case Study

(1) Background: the community is the most basic place to maintain residents’ lives, and therefore it is urgent to strengthen community resilience construction, which is directly related to the economic development, security and stability of urban communities. (2) Methods: this article combines the SWOT (Strengths, Weaknesses, Opportunities, Threats) qualitative analysis method and the AHP (Analytic hierarchy process) qualitative and quantitative analysis method to explore the current status of community emergency management in Xi’an City. A community emergency management evaluation model is constructed, which is based on six dimensions: infrastructure resilience, community organization resilience, risk hazard governance, emergency material security, emergency force construction, and emergency literacy. The evaluation index for community emergency management is established. Focusing on analyzing the strengths and weaknesses of communities in responding to sudden public health emergencies, opportunities and threats are identified. (3) Results: it was concluded that infrastructure resilience and emergency material support are community strengths, community organizational resilience is a community weakness, the emergency literacy dimension is a community opportunity, and risk and hazard management and emergency force construction are community threats. The results of the data research were further analyzed. (4) Conclusions: The final research results provide new theoretical support for community emergency management, while also providing theoretical and methodological references for emergency capacity evaluation in other fields.

Research on the layout of urban disaster-prevention and risk-avoidance green space under the improvement of supply and demand match: The case study of the main urban area of Nanjing, China

Accelerated urbanization has made the disaster situation increasingly severe, especially that related to geological disasters, floods, fires, and other disasters. In response to high-frequency disasters, external disaster prevention spaces, mainly urban green spaces, play a key role in sheltering and housing. While many current studies focus on the balanced layout of green space, which improves their disaster prevention and avoidance capacity to a certain extent, there is insufficient consideration of disaster distribution and population demand, leading to conflicts between green space supply and demand. Therefore, this study further explores the efficiency improvement of disaster-prevention and risk-avoidance green space (DPRAGS) from the perspective of matching supply and demand. Taking the main urban area of Nanjing as an example, we rely on ArcGIS, combined with the maximum capacity limitation coverage model, and conduct green space layout analysis through analysis of urban infrastructure, disaster risk, and the demand and supply of DPRAGS. The research results show that compared with previous green space planning methods involving suitability assessment and accessibility analysis, the unitized planning method, mainly based on supply and demand matching, can better meet the refuge requirements of demand points and improve the rationality of green space layout. This study enriches the theory of urban green space planning and guides the planning of DPRAGS in typical densely populated metropolises, such as Nanjing. Additionally, it can help develop emergency plans and management rules and regulations, ultimately enhancing evacuation efficiency during disasters and improving overall urban disaster prevention and emergency management capabilities.

Emergency management capability evaluation of chemical parks based on PFDEMATEL‐G1 and PFTOPSIS

AbstractConducting an evaluation of the emergency management capacity of the chemical park and implementing targeted improvements based on the assessment results can significantly enhance the emergency preparedness and response capabilities of both the management departments and enterprises. This article proposes an emergency management capability assessment model for chemical parks based on PFDEMATEL (the Pythagorean fuzzy decision‐making trial and evaluation laboratory)‐G1 (the ordinal relation method) and PFTOPSIS (the Pythagorean fuzzy set TOPSIS). Firstly, based on the four stages of emergency management of chemical parks, emergency prevention, emergency preparedness, emergency response, and emergency recovery, an index system for evaluating the emergency management capacity of chemical parks was established. Secondly, PFDEMATEL is used to modify the G1 method to determine the index weight, so as to realize the objective rationality of the G1 method empowerment. On this basis, an emergency management capability evaluation model of chemical park to improve PFTOPSIS is proposed. Finally, taking three chemical parks as examples, the applicability of the evaluation model is verified. The research results can provide a theoretical reference for the emergency management decision‐making of governments and enterprises, improve the status quo of emergency management, and improve the prevention and handling capabilities of emergencies.

Research on the Evaluation and Spatial–Temporal Evolution of Safe and Resilient Cities Based on Catastrophe Theory—A Case Study of Ten Regions in Western China

In today’s highly complex world, urban security has become a focus of attention for people in various positions due to its enormous uncertainty. As an essential path towards urban safety, resilient development can effectively provide emergency management capability for cities when they are exposed to unknown risks. In this study, an evaluation-index system for urban-safety resilience was constructed from the perspective of sustainable urban development. The urban-safety-resilience evaluation model was established with the help of catastrophe theory to study and analyze urban-safety resilience. The corresponding spatial–temporal-evolution analysis used the geographic information system (GIS) and Moran index to evaluate the urban-security resilience of 10 regions in western China. Finally, it was concluded that (1) the urban-safety resilience of most regions in western China showed an increasing trend over time in 2017, 2019, and 2021; (2) the urban-safety resilience of Chongqing, Sichuan, and Shaanxi provinces is at a relatively high level compared to the western region overall; and (3) regions such as Ningxia and Gansu are disaster-prone, and urban infrastructure conditions are relatively backward. Therefore, urban planning and governance should be flexibly transformed to explore and apply appropriate urban-safety-resilience models, with sustainable development as the cornerstone.

An improved semantic segmentation model based on SVM for marine oil spill detection using SAR image

In the oil industry, oil spills occur due to offshore rig explosions, ship collisions, and other reasons. It is crucial to accurately and rapidly identify oil spills to protect marine ecosystems. Synthetic aperture radar (SAR) can all-weather and all-time work and provide a wealth of polarization information for identification of oil spills based on semantic segmentation model. However, the performance of classifiers in the semantic segmentation model has become a significant challenge to improving recognition ability. To solve this problem, an improved semantic segmentation model named DRSNet was proposed, which uses ResNet-50 as the backbone in DeepLabv3+ and support vector machines (SVM) as the classifier. The experiment was conducted using ten polarimetric features from SAR images and results demonstrate that the DRSNet performs best compared to other semantic segmentation models. Current work provides a valuable tool to enhance maritime emergency management capabilities.

Research on an evaluation index system of critical emergency management capability based on machine learning in a complex scientific environment

IntroductionA complex scientific environment requires multiple considerations for handling critical and emergency conditions with an addressing solution. Indexing and prioritizing are standard methods that are used in such settings to improve itinerary solutions. Significance of an indexing system relies on the benchmark solution and the strategy it implies.MethodsThe present study introduces an indexing strategy evaluation method (ISEM) to validate the efficiency of indexing systems. The proposed method identifies the root implication and the strategy parameters to address complex problems. The environmental and problem-specific parameters are determined to estimate the system's initial response. The capability through solution response, lag, and failure analysis is identified post the estimation through linear regression learning. The indexing system's operations are designed through linear itineraries to prevent interrupting failures. In addition, the environmental features are identified as augmenting factors to prevent strategy pausing across multiple indices.Results and discussionThe proposed method employs linear analysis through itinerary levels of index evaluation for optimal, lagging, and failed implications. It also helps to identify specific reasons for solution improvement or retention from previous operations.