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With the process of urbanization in China, the urban waterlogging caused by rainstorms occurs frequently and often leads to serious damage to the natural environment, human life, and the city economy. Rapid detection of rainstorm and urban waterlogging disasters is an essential step to minimize these losses. Weibo, a popular microblog service in China, can provide many real-time Weibo posts for rapid detection. In this paper, we propose a method to identify microblogs with rainstorm and waterlogging information and apply them to waterlogging risk assessment. After pre-processing the microblog texts, we evaluate the performance of clustering (k -means) and classification (support vector machine, SVM) algorithms in the classification task. Apart from word vector features, we also introduce sentiment and publisher features for more real-time and accurate results. Furthermore, we build a waterlogging intensity dictionary to assess the waterlogging risk from the Weibo texts and produce a risk map with ArcGIS. To examine the efficacy of this approach, we collect Weibo data from two rainstorms and waterlogging disasters in Beijing city as examples. The results indicate that the SVM algorithm can be applied for a real-time rainstorm and waterlogging information detection. Compared to official-authentication and personal-certification users, the microblogs posted by general users can better indicate the intensity and timing of rainstorms. The location of waterlogging points is consistent with the risk assessment results, which proves our proposed risk assessment method can be used as a reference for timely emergency response. [ABSTRACT FROM AUTHOR]

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This paper studies a location-allocation problem to determine the selection of emergency shelters, medical centers, and distribution centers after the disaster. The evacuation of refugees and allocation of relief resources are also considered. A mixed-integer nonlinear multiobjective programming model is proposed to characterize the problem. The hierarchical demand of different refugees and the limitations of relief resources are considered in the model. We employ a combination of the simulated annealing (SA) algorithm and the particle swarm optimization (PSO) algorithm method to solve the complex model. To optimize the result of our proposed algorithm, we absorb the group search, crossover, and mutation operator of GA into SA. We conduct a case study in a district of Beijing in China to validate the proposed methodology. Some computational experiments are conducted to analyze the impact of different factors, such as the target weight setting, selection of candidate shelters, and quantity of relief resources. [ABSTRACT FROM AUTHOR]

Abstract: With the urban rail transit network in Beijing becoming gradually intensive, the passenger flow organization also develops towards the type of the network mode. This paper analyzes the development trend of the urban rail transit network in Beijing. On the basis of a reasonable classification of emergencies occurred in urban rail transit, this paper puts forward the passenger organization model of rail transit network under emergency conditions, and then set a certain train accident of Beijing Metro Line 1 as an example to illustrate the practical application of the passenger emergency organization mode. [Copyright &y& Elsevier]

Accurate mapping of dams can provide useful information about geographical locations and boundaries and can help improve public dam datasets. However, when applied to disaster emergency management, it is often difficult to completely determine the distribution of dams due to the incompleteness of the available data. Thus, we propose an automatic and intelligent extraction method that combines location with post-segmentation for dam detection. First, we constructed a dataset named RSDams and proposed an object detection model, YOLOv5s-ViT-BiFPN (You Only Look Once version 5s-Vision Transformer-Bi-Directional Feature Pyramid Network), with a training method using deep transfer learning to generate graphical locations for dams. After retraining the model on the RSDams dataset, its precision for dam detection reached 88.2% and showed a 3.4% improvement over learning from scratch. Second, based on the graphical locations, we utilized an improved Morphological Building Index (MBI) algorithm for dam segmentation to derive dam masks. The average overall accuracy and Kappa coefficient of the model applied to 100 images reached 97.4% and 0.7, respectively. Finally, we applied the dam extraction method to two study areas, namely, Yangbi County of Yunnan Province and Changping District of Beijing in China, and the recall rates reached 69.2% and 81.5%, respectively. The results show that our method has high accuracy and good potential to serve as an automatic and intelligent method for the establishment of a public dam dataset on a regional or national scale. [ABSTRACT FROM AUTHOR]

Abstract: Keep in pace with the 2008 Beijing Olympics and the 2010 Shanghai Expo, engineering events of different types and sizes are coming to China more than it had ever happened during years. Obviously, these could all cause safety problems. To organize the event perfectly, a lot of questions occur: How to provide the best safety to everyone participate in our event? How to deal with the emergencies during the event? These questions are the most important element of holding a successful event. This paper discusses the necessity of engineering risk management during events. [Copyright &y& Elsevier]

Abstract: To take into account reasonably the safety requirements of the disabled on emergency evacuation in the design, usage, management and emergency response of public places, the authors of this paper organized on-site experiments for 100 disabled individuals (40 people with no supporting tools, 20 people using a single crutch and 40 people two crutches) and 17 healthy people at a subway station in Beijing. The experiments were designed to measure the unimpeded free walking speed of the participants during horizontal and stair ascending/descending movement, and to assess the possible impact of passage width on movement speed. Based on the results of the tests, the authors systematically analyzed the speed variation patterns with disability grade, gender and passage width. The validity of the value of an important parameter for evacuation safety design in the prescribed fire codes in mainland China, the width of a single stream of people, is assessed. Finally the results of the experiments are compared with that from other researches to identify the similarities and differences between them. [Copyright &y& Elsevier]

When responding to crises, a joint approach is often used, which requires coordination among government agencies and other institutions. In this article we combine the vertical and horizontal dimensions to develop a theoretical framework to explain the patterns and performance of coordination. By drawing on structural-instrumental and institutional perspectives, we examine the coordination structures and mechanisms in China's crisis management at the central and local levels. We outline the main structural characteristics of the Chinese system and the overall challenges it faces. We then discuss four crises that have happened in and around Beijing, using these to illustrate the crucial factors driving coordination successes and failures. Lastly, we discuss some comparative features and the theoretical and policy implications of our main results. [ABSTRACT FROM AUTHOR]

Social media has been applied to all natural disaster risk-reduction phases, including pre-warning, response, and recovery. However, using it to accurately acquire and reveal public sentiment during a disaster still presents a significant challenge. To explore public sentiment in depth during a disaster, this study analyzed Sina-Weibo (Weibo) texts in terms of space, time, and content related to the 2018 Shouguang flood, which caused casualties and economic losses, arousing widespread public concern in China. The temporal changes within six-hour intervals and spatial distribution on sub-district and city levels of flood-related Weibo were analyzed. Based on the Latent Dirichlet Allocation (LDA) model and the Random Forest (RF) algorithm, a topic extraction and classification model was built to hierarchically identify six flood-relevant topics and nine types of public sentiment responses in Weibo texts. The majority of Weibo texts about the Shouguang flood were related to "public sentiment", among which "questioning the government and media" was the most commonly expressed. The Weibo text numbers varied over time for different topics and sentiments that corresponded to the different developmental stages of the flood. On a sub-district level, the spatial distribution of flood-relevant Weibo was mainly concentrated in high population areas in the south-central and eastern parts of Shouguang, near the river and the downtown area. At the city level, the Weibo texts were mainly distributed in Beijing and cities in the Shandong Province, centering in Weifang City. The results indicated that the classification model developed in this study was accurate and viable for analyzing social media texts during a disaster. The findings can be used to help researchers, public servants, and officials to better understand public sentiments towards disaster events, to accelerate disaster responses, and to support post-disaster management. [ABSTRACT FROM AUTHOR]