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Wei Xu
Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing, China

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Research article
Published: 01 January 2021 in Geomatics, Natural Hazards and Risk
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Many empirical typhoon economic loss models consider that the losses caused by typhoons mainly depend on the intensity of the hazards and the exposure in the affected areas. Few studies have attracted attention to the role of disaster-formative environmental factors in typhoon losses. In this study, we chose land use and land cover (LULC) as disaster-formative environmental factors together with typhoon wind speed, rainfall, and gross domestic product (GDP) as predictive factors for typhoon economic losses in Guangdong Province, China. The results showed that the intensity of wind speed was the most important factor, while LULC played weak roles in typhoon economic losses for 23 typical typhoons in terms of county level losses in Guangdong. Subregionally, typhoon economic loss models performed better in coastal areas than in noncoastal areas.

ACS Style

Lianjie Qin; Wei Xu; Mengjiao Qin; Zixuan Li; Yu Qiao; Baoyin Liu; Jing Zheng. Land use and land cover play weak roles in typhoon economic losses at the county level. Geomatics, Natural Hazards and Risk 2021, 12, 1287 -1297.

AMA Style

Lianjie Qin, Wei Xu, Mengjiao Qin, Zixuan Li, Yu Qiao, Baoyin Liu, Jing Zheng. Land use and land cover play weak roles in typhoon economic losses at the county level. Geomatics, Natural Hazards and Risk. 2021; 12 (1):1287-1297.

Chicago/Turabian Style

Lianjie Qin; Wei Xu; Mengjiao Qin; Zixuan Li; Yu Qiao; Baoyin Liu; Jing Zheng. 2021. "Land use and land cover play weak roles in typhoon economic losses at the county level." Geomatics, Natural Hazards and Risk 12, no. 1: 1287-1297.

Journal article
Published: 18 April 2020 in Sustainability
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Typhoon disaster represent one of the most prominent threats to public safety in the Macao Special Administrative Region (SAR) of China and can cause severe economic losses and casualties. Prior to the landing of typhoons, affected people should be evacuated to shelters as soon as possible; this is crucial to prevent injuries and deaths. Various models aim to solve this problem, but the characteristics of disasters and evacuees are often overlooked. This study proposes a model based on the influence of a typhoon and its impact on evacuees. The model’s objective is to minimize the total evacuation distance, taking into account the distance constraint. The model is solved using the spatial analysis tools of Geographic Information Systems (GIS). It is then applied in Macao to solve the evacuation process for Typhoon Mangkhut 2018. The result is an evacuee allocation plan that can help the government organize evacuation efficiently. Furthermore, the number of evacuees allocated to shelters is compared with shelter capacities, which can inform government shelter construction in the future.

ACS Style

Xiujuan Zhao; Peng Du; Jianguo Chen; Dapeng Yu; Wei Xu; Shiyan Lou; Hongyong Yuan; Kuai Peng Ip. A Typhoon Shelter Selection and Evacuee Allocation Model: A Case Study of Macao (SAR), China. Sustainability 2020, 12, 3308 .

AMA Style

Xiujuan Zhao, Peng Du, Jianguo Chen, Dapeng Yu, Wei Xu, Shiyan Lou, Hongyong Yuan, Kuai Peng Ip. A Typhoon Shelter Selection and Evacuee Allocation Model: A Case Study of Macao (SAR), China. Sustainability. 2020; 12 (8):3308.

Chicago/Turabian Style

Xiujuan Zhao; Peng Du; Jianguo Chen; Dapeng Yu; Wei Xu; Shiyan Lou; Hongyong Yuan; Kuai Peng Ip. 2020. "A Typhoon Shelter Selection and Evacuee Allocation Model: A Case Study of Macao (SAR), China." Sustainability 12, no. 8: 3308.

Journal article
Published: 22 August 2019 in Sustainability
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Earthquakes are one type of natural disaster that causes serious economic loss, deaths, and homelessness, and providing shelters is vital to evacuees who have been affected by an earthquake. Constructing shelters with reasonable capacity in the right locations and allocating evacuees to them in a reasonable time period is one disaster management method. This study proposes a multi-objective hierarchical model with three stages, i.e., an immediate shelter (IS) stage, a short-term shelter (STS) stage, and a long-term shelter (LTS) stage. According to the requirements of evacuees of IS, STS, and LTS, the objective of both the IS and STS stages is to minimize total evacuation time and the objectives of the LTS are to minimize total evacuation time and to minimize total shelter area. A modified particle swarm optimization (MPSO) algorithm is used to solve the IS and STS stages and an interleaved modified particle swarm optimization algorithm and genetic algorithm (MPSO-GA) is applied to solve the LTS stage. Taking Chaoyang District, Beijing, China as a case study, the results generated using the model present the government with a set of options. Thus, according to the preferences of the government, the determination can be made regarding where to construct ISs, STSs, and LTSs, and how to allocate the evacuees to them.

ACS Style

Xiujuan Zhao; Jianguo Chen; Wei Xu; Shiyan Lou; Peng Du; Hongyong Yuan; Kuai Peng Ip. A Three-Stage Hierarchical Model for An Earthquake Shelter Location-Allocation Problem: Case Study of Chaoyang District, Beijing, China. Sustainability 2019, 11, 4561 .

AMA Style

Xiujuan Zhao, Jianguo Chen, Wei Xu, Shiyan Lou, Peng Du, Hongyong Yuan, Kuai Peng Ip. A Three-Stage Hierarchical Model for An Earthquake Shelter Location-Allocation Problem: Case Study of Chaoyang District, Beijing, China. Sustainability. 2019; 11 (17):4561.

Chicago/Turabian Style

Xiujuan Zhao; Jianguo Chen; Wei Xu; Shiyan Lou; Peng Du; Hongyong Yuan; Kuai Peng Ip. 2019. "A Three-Stage Hierarchical Model for An Earthquake Shelter Location-Allocation Problem: Case Study of Chaoyang District, Beijing, China." Sustainability 11, no. 17: 4561.

Original article
Published: 11 April 2019 in Injury Prevention
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BackgroundDetermining the locations of disaster emergency shelters and the allocation of impacted residents are key components in shelter planning and emergency management. Various models have been developed to solve this location–allocation problem, but gaps remain regarding the processes of hazards. This study attempts to develop a model based on the change of typhoon track that addresses the location–allocation problem for typhoon emergency shelters.PurposeTo consider the changes in candidate shelters and number of evacuees due to the change in impact area with the progression of a typhoon.MethodsThe proposed model is composed of several static processes and solved by a modified particle swarm optimisation algorithm with a restart strategy.ResultsThe model is illustrated with the case of the evacuation process for Wenchang in Hainan province during Typhoon Rammasun in 2014 and Typhoon Mirinae in 2016. For the case of Typhoon Rammasun in 2014, the residents from east to west need to evacuate in three phases. For the case of Typhoon Mirinae in 2016, residents in the northern communities need not to evacuate to candidate shelters because they are not affected by the typhoon.ConclusionThe proposed model has advantages compared with non-typhoon track change–based model in saving time spent in shelters for residents and saving public resources for the local governments. With the proposed model, a manager could efficiently evacuate residents by considering the typhoon conditions.

ACS Style

Lianjie Qin; Wei Xu; Xiujuan Zhao; Yunjia Ma. Typhoon track change–based emergency shelter location–allocation model: a case study of Wenchang in Hainan province, China. Injury Prevention 2019, 26, 196 -203.

AMA Style

Lianjie Qin, Wei Xu, Xiujuan Zhao, Yunjia Ma. Typhoon track change–based emergency shelter location–allocation model: a case study of Wenchang in Hainan province, China. Injury Prevention. 2019; 26 (3):196-203.

Chicago/Turabian Style

Lianjie Qin; Wei Xu; Xiujuan Zhao; Yunjia Ma. 2019. "Typhoon track change–based emergency shelter location–allocation model: a case study of Wenchang in Hainan province, China." Injury Prevention 26, no. 3: 196-203.

Journal article
Published: 12 February 2019 in Sustainability
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Due to their complexity, hazard interactions are often neglected in current studies of multi-hazard risk assessment. As a result, the assessment results are qualitative or semi-quantitative and are difficult to use in regional risk management. In this paper, the crop loss risk due to heavy rain and strong wind in the Yangtze River Delta (YRD) region of China was quantitatively assessed, based on the joint return periods of these hazards and a vulnerability surface. The joint return period is obtained with a copula function based on the marginal distribution of each hazard. The vulnerability is fitted by considering the joint hazard intensity, the sown area of crops, elevation, and GDP per capita. The results show that counties with a high value of joint hazard probability are clustered in the southeast coastal area and that the value gradually decreases from south to north and from east to west. The multi-hazard risk has a similar pattern, with a large value in the southeast coastal area and a low value in the northwest. The proposed method can be used for quantitative assessment of multi-hazard risk, and the results can be used for regional disaster risk management and planning.

ACS Style

Wei Xu; Xiaodong Ming; Yunjia Ma; Xinhang Zhang; Peijun Shi; Li Zhuo; Bingqiang Lu. Quantitative Multi-Hazard Risk Assessment of Crop Loss in the Yangtze River Delta Region of China. Sustainability 2019, 11, 922 .

AMA Style

Wei Xu, Xiaodong Ming, Yunjia Ma, Xinhang Zhang, Peijun Shi, Li Zhuo, Bingqiang Lu. Quantitative Multi-Hazard Risk Assessment of Crop Loss in the Yangtze River Delta Region of China. Sustainability. 2019; 11 (3):922.

Chicago/Turabian Style

Wei Xu; Xiaodong Ming; Yunjia Ma; Xinhang Zhang; Peijun Shi; Li Zhuo; Bingqiang Lu. 2019. "Quantitative Multi-Hazard Risk Assessment of Crop Loss in the Yangtze River Delta Region of China." Sustainability 11, no. 3: 922.

Journal article
Published: 25 January 2019 in Science of The Total Environment
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Quantifying global population exposure to rainstorms is a key component of population risk assessments for rainstorms and induced floods. Based on daily precipitation data from the NEX-GDDP dataset, rainfall from rainstorms is first calculated by a multi-model ensemble method for four periods from 1986 to 2100. Combined with population data from the SSP2 scenario, the global population exposure to rainstorms is then calculated and analyzed. Finally, the contribution rates of climate change effect, population change effect, and joint change effect on exposure change are quantitatively assessed. The results showed that (1) Population exposure to rainstorms shows a linear upward trend from base period to the late 21st century period in most regions, and the mid-21st century period compared with base period has the fastest rate of increase. (2) The spatial patterns of population exposure to rainstorms are very similar for the four periods and the areas with high exposure are mainly distributed in Asia, population exposure of Africa is gradually increasing. The countries with high exposure show little volatility, especially the top eight countries. (3) The change in total exposure is mainly due to population change. Based on the composition of the total exposure change for each country, the number of countries whose climate change effect is greater than that of population change is gradually increasing, and this number reaches more than a quarter of the total when the late 21st century period is compared with the mid-21st century period.

ACS Style

Xinli Liao; Wei Xu; Junlin Zhang; Ying Li; Yugang Tian. Global exposure to rainstorms and the contribution rates of climate change and population change. Science of The Total Environment 2019, 663, 644 -653.

AMA Style

Xinli Liao, Wei Xu, Junlin Zhang, Ying Li, Yugang Tian. Global exposure to rainstorms and the contribution rates of climate change and population change. Science of The Total Environment. 2019; 663 ():644-653.

Chicago/Turabian Style

Xinli Liao; Wei Xu; Junlin Zhang; Ying Li; Yugang Tian. 2019. "Global exposure to rainstorms and the contribution rates of climate change and population change." Science of The Total Environment 663, no. : 644-653.

Review
Published: 14 January 2019 in Sustainability
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Constructing natural disaster shelters is important for disaster emergency management, and site selection models provide a feasible technique and method. This paper presents site selection models for natural disaster shelters. A synthesis of the types, objectives, constraints, methods of solutions, targeted disasters and applications of different site selection models for natural disaster shelters is investigated. Shelter location models can be classified as single-objective models, multiobjective models and hierarchical models, according to the objective and hierarchy type. Minimizing the evacuation distance or time, shelter construction cost or number, and the total risk are the general objectives of the models. Intelligent optimization algorithms are widely used to solve the models, instead of the Geographic Information System (GIS) method, due to the complexity of the problem. The results indicate that the following should be the main focuses of future works: How to set a model that can be applied for determining the shelter locations of multiple disasters; how to consider the uncertainty in the models; how to improve the existing algorithms or models to solve large-scale location-allocation problems; and how to develop a new resource-saving model that is consistent with the concept of sustainable development, as advocated by shelter planners and policy makers, which can be applied in real situations. This study allows those undertaking shelter location research to situate their work within the context of shelter planning.

ACS Style

Yunjia Ma; Wei Xu; Lianjie Qin; Xiujuan Zhao. Site Selection Models in Natural Disaster Shelters: A Review. Sustainability 2019, 11, 399 .

AMA Style

Yunjia Ma, Wei Xu, Lianjie Qin, Xiujuan Zhao. Site Selection Models in Natural Disaster Shelters: A Review. Sustainability. 2019; 11 (2):399.

Chicago/Turabian Style

Yunjia Ma; Wei Xu; Lianjie Qin; Xiujuan Zhao. 2019. "Site Selection Models in Natural Disaster Shelters: A Review." Sustainability 11, no. 2: 399.

Article
Published: 01 January 2019 in Geomatics, Natural Hazards and Risk
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Earthquake disaster management involves determining locations in which to construct shelters and how to allocate the affected population to them. A multi-objective, hierarchical mathematical model, allied with an interleaved modified particle swarm optimization algorithm and genetic algorithm (MPSO–GA), have been developed to solve the earthquake shelter location-allocation problem. From a set of candidate shelter locations, the model first determines which of these should act as emergency shelters and then which should be used as long-term shelters, while simultaneously optimizing the allocation of a population to them. Damage caused to evacuation routes is considered in addition to the number of evacuees and shelter capacity. In terms of the model’s emergency and long-term shelter stages, the objectives are to minimize (i) total weighted evacuation time, and (ii) total shelter area used. An interleaved MPSO–GA applied to the model yielded better results than achieved using MPSO or GA in isolation. For a case study with an earthquake affecting the area of Jinzhan within Beijing’s Chaoyang district in China, results generated present government with a range of solution options. Thus, based on government preferences, choices can be made regarding the locations in which to construct shelters and how to allocate the population to them.

ACS Style

Xiujuan Zhao; Graham Coates; Wei Xu. A hierarchical mathematical model of the earthquake shelter location-allocation problem solved using an interleaved MPSO–GA. Geomatics, Natural Hazards and Risk 2019, 10, 1712 -1737.

AMA Style

Xiujuan Zhao, Graham Coates, Wei Xu. A hierarchical mathematical model of the earthquake shelter location-allocation problem solved using an interleaved MPSO–GA. Geomatics, Natural Hazards and Risk. 2019; 10 (1):1712-1737.

Chicago/Turabian Style

Xiujuan Zhao; Graham Coates; Wei Xu. 2019. "A hierarchical mathematical model of the earthquake shelter location-allocation problem solved using an interleaved MPSO–GA." Geomatics, Natural Hazards and Risk 10, no. 1: 1712-1737.

Articles
Published: 01 January 2019 in Geomatics, Natural Hazards and Risk
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The special planning for shelters is an integral part of overall city planning and is a key issue in solving the urban security problem. During the planning of earthquake emergency shelters, it is usually necessary to prioritize the designated shelters to avoid wasting resources. However, in previous research initiatives, special attention has been given to the general location-allocation model without prior consideration of the designated shelters. This article presents a multi-objective supplemental location-allocation optimization model for earthquake emergency shelters that addresses the concerns related to the designated shelters. This model is believed to remain more consistent with the knowledge of shelter planners and policy makers by incorporating the uncertainties of the temporal dynamics of population distribution and the spatially heterogeneous distribution of evacuees under various earthquake damage scenarios by using the elliptical attenuation model for seismic intensity into the location-allocation problem. A case study of the central area of Beijing, China is presented. A modified particle swarm optimization algorithm is applied to solve the supplemental location-allocation model and the general location-allocation model, and the solutions obtained from the two models are then compared. The results show that the solutions of the supplemental location-allocation model significantly minimized the shelter area by prioritizing the designated shelters. By contrast, without prior consideration of the designated shelters, the shelter areas significantly increased, which slightly decreased the evacuation distance in the general location-allocation model. The policy makers could select solutions from the obtained minimal-area scheme using the supplemental location-allocation model that ensures acceptable evacuation distances and minimal budgets by prioritizing the designated shelters during the phased planning of shelters in Beijing.

ACS Style

Yunjia Ma; Wei Xu; Lianjie Qin; Xiujuan Zhao; Juan Du. Emergency shelters location-allocation problem concerning uncertainty and limited resources: a multi-objective optimization with a case study in the Central area of Beijing, China. Geomatics, Natural Hazards and Risk 2019, 10, 1242 -1266.

AMA Style

Yunjia Ma, Wei Xu, Lianjie Qin, Xiujuan Zhao, Juan Du. Emergency shelters location-allocation problem concerning uncertainty and limited resources: a multi-objective optimization with a case study in the Central area of Beijing, China. Geomatics, Natural Hazards and Risk. 2019; 10 (1):1242-1266.

Chicago/Turabian Style

Yunjia Ma; Wei Xu; Lianjie Qin; Xiujuan Zhao; Juan Du. 2019. "Emergency shelters location-allocation problem concerning uncertainty and limited resources: a multi-objective optimization with a case study in the Central area of Beijing, China." Geomatics, Natural Hazards and Risk 10, no. 1: 1242-1266.

Articles
Published: 26 December 2018 in Geomatics, Natural Hazards and Risk
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Research on the emergency facility location-allocation problem has important theoretical and practical significance for responses to large-scale emergencies. During the actual planning of disaster supply warehouses (DSWs), reconstruction and expansion projects usually need to fully exploit different levels of designated facilities to achieve resource integration. This article presents a hierarchical supplement location-allocation (HSLA) optimization model for DSWs in both the preparedness and response phases to address the above concerns. The model minimizes the total number and cost of DSWs for the facility location problem and the total distance for delivering supplies at all levels for the supply allocation problem. A modified particle swarm optimization algorithm is applied to derive solutions to the HSLA model. The model is demonstrated for the Beijing–Tianjin–Hebei (BTH) region in China. The results show that twelve of the 180 counties, which account for 6.03% of the total area of the BTH region are not covered by county-, prefectural- and provincial-level DSWs. In addition, three sets of optimization schemes for the location-allocation problem for DSWs at the three levels and one final mixed optimal scheme (one county-level DSW, two prefectural-level DSWs, and one provincial-level DSW should be newly built or upgraded in four counties) are suggested based on the supplemental optimization site selection. This model is believed to remain more consistent with the knowledge of DSW planners and policy makers by incorporating the multi-level coverage and supplemental site selection concept into the location-allocation problem. The method can be easily duplicated to expand or build new emergency facilities at different levels in addition to DSWs. The results provide a scientific reference for DSW location-allocation planning in the BTH region.

ACS Style

Yunjia Ma; Wei Xu; Lianjie Qin; Xiujuan Zhao; Juan Du. Hierarchical supplement location-allocation optimization for disaster supply warehouses in the Beijing–Tianjin–Hebei region of China. Geomatics, Natural Hazards and Risk 2018, 10, 102 -117.

AMA Style

Yunjia Ma, Wei Xu, Lianjie Qin, Xiujuan Zhao, Juan Du. Hierarchical supplement location-allocation optimization for disaster supply warehouses in the Beijing–Tianjin–Hebei region of China. Geomatics, Natural Hazards and Risk. 2018; 10 (1):102-117.

Chicago/Turabian Style

Yunjia Ma; Wei Xu; Lianjie Qin; Xiujuan Zhao; Juan Du. 2018. "Hierarchical supplement location-allocation optimization for disaster supply warehouses in the Beijing–Tianjin–Hebei region of China." Geomatics, Natural Hazards and Risk 10, no. 1: 102-117.

Journal article
Published: 07 November 2018 in ISPRS International Journal of Geo-Information
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Spatial distribution and population density are important parameters in studies on urban development, resource allocation, emergency management, and risk analysis. High-resolution height data can be used to estimate the total or spatial pattern of the urban population for small study areas, e.g., the downtown area of a city or a community. However, there has been no case of population estimation for large areas. This paper tries to estimate the urban population of prefectural cities in China using building height data. Building height in urban population settlement (Mdiffs) was first extracted using the digital surface model (DSM), digital elevation model (DEM), and land use data. Then, the relationships between the census-based urban population density (CPD) and the Mdiffs density (MDD) for different regions were regressed. Using these results, the urban population for prefectural cities of China was finally estimated. The results showed that a good linear correlation was found between Mdiffs and the census data in each type of region, as all the adjusted R2 values were above 0.9 and all the models passed the significance test (95% confidence level). The ratio of the estimated population to the census population (PER) was between 0.7 and 1.3 for 76% of the cities in China. This is the first attempt to estimate the urban population using building height data for prefectural cities in China. This method produced reasonable results and can be effectively used for spatial distribution estimates of the urban population in large scale areas.

ACS Style

Junlin Zhang; Wei Xu; Lianjie Qin; Yugang Tian. Spatial Distribution Estimates of the Urban Population Using DSM and DEM Data in China. ISPRS International Journal of Geo-Information 2018, 7, 435 .

AMA Style

Junlin Zhang, Wei Xu, Lianjie Qin, Yugang Tian. Spatial Distribution Estimates of the Urban Population Using DSM and DEM Data in China. ISPRS International Journal of Geo-Information. 2018; 7 (11):435.

Chicago/Turabian Style

Junlin Zhang; Wei Xu; Lianjie Qin; Yugang Tian. 2018. "Spatial Distribution Estimates of the Urban Population Using DSM and DEM Data in China." ISPRS International Journal of Geo-Information 7, no. 11: 435.

Journal article
Published: 21 July 2018 in Water Resources Research
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A river channel network is an important geomorphological feature in a catchment. A method to extract river channels in urban environments from a high‐resolution digital elevation model (DEM) is introduced in this paper. The method utilizes terrain transition lines to delineate channel networks. First, terrain transition lines are extracted from the DEM. Then, shallow road ditches are removed based on elevation from the terrain transition lines, and then, noise is removed using the region growing method. Subsequently, most of the road ditches are removed by pixel block expansion, and then, the non‐channel pixels are removed by fitting a quadratic surface. The computational efficiency and accurate localization of river channel extraction using the proposed method is demonstrated using light detection and ranging (LiDAR) data for an urban environment in Johnson County, Iowa. The proposed method is effective for extracting channels and removing road ditches in this urban environment. A potential application of this method is to provide the river channels required for riverine flood modeling and geomorphological studies.

ACS Style

Lianjie Qin; Wei Xu; Yugang Tian; Bo Chen; Siyue Wang. A River Channel Extraction Method for Urban Environments Based on Terrain Transition Lines. Water Resources Research 2018, 54, 4887 -4900.

AMA Style

Lianjie Qin, Wei Xu, Yugang Tian, Bo Chen, Siyue Wang. A River Channel Extraction Method for Urban Environments Based on Terrain Transition Lines. Water Resources Research. 2018; 54 (7):4887-4900.

Chicago/Turabian Style

Lianjie Qin; Wei Xu; Yugang Tian; Bo Chen; Siyue Wang. 2018. "A River Channel Extraction Method for Urban Environments Based on Terrain Transition Lines." Water Resources Research 54, no. 7: 4887-4900.

Original articles
Published: 01 January 2018 in Geomatics, Natural Hazards and Risk
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Constructing shelters is an important part of earthquake disaster management which involves selecting the location of them and assigning the evacuees to them. For this work, selecting suitable objectives and solution is important. Thus, in this paper, a multi-objective mathematical model with four groups of the objectives, allied with a modified particle swarm optimization algorithm, has been developed to solve the location–allocation problem for earthquake shelter. The four objective groups are: total shelter number (TSN) and total evacuation distance (TED), TSN and total weighted evaluation time (TWET), total shelter area (TSA) and TED, and TSA and TWET. The solutions of the model include the determination of the shelters from the candidates and how to allocate population to them. Then the solutions of the model with four objective groups are given and compared using safety, capacity and investment evaluation index with the case of Chaoyang district of Beijing, China. Related to government's preferences and future city planning, the most suitable model solutions can be chosen to help decide where it is suitable to construct shelters and how to allocate the population.

ACS Style

Wei Xu; Xiujuan Zhao; Yunjia Ma; Ying Li; Lianjie Qin; Ying Wang; Juan Du. A multi-objective optimization based method for evaluating earthquake shelter location–allocation. Geomatics, Natural Hazards and Risk 2018, 9, 662 -677.

AMA Style

Wei Xu, Xiujuan Zhao, Yunjia Ma, Ying Li, Lianjie Qin, Ying Wang, Juan Du. A multi-objective optimization based method for evaluating earthquake shelter location–allocation. Geomatics, Natural Hazards and Risk. 2018; 9 (1):662-677.

Chicago/Turabian Style

Wei Xu; Xiujuan Zhao; Yunjia Ma; Ying Li; Lianjie Qin; Ying Wang; Juan Du. 2018. "A multi-objective optimization based method for evaluating earthquake shelter location–allocation." Geomatics, Natural Hazards and Risk 9, no. 1: 662-677.

Article
Published: 13 December 2017 in International Journal of Disaster Risk Science
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Determining the location of earthquake emergency shelters and the allocation of affected population to them are key issues that face shelter planning and emergency management. To solve this emergency shelter location–allocation problem, evacuation time and the construction cost of shelters—both influenced by the evacuation population size and its spatial distribution—are two important considerations. In this article, a mathematical model with two objectives—to minimize total weighted evacuation time (TWET) and total shelter area (TSA)—is allied with a modified particle swarm optimization algorithm to address the problem. The relationships between evacuation population size, evacuation time, and total shelter area are examined using Jinzhan Town in Chaoyang District of Beijing, China, as a case study. The results show that TWET has a power function relationship with TSA under different population size scenarios, and a linear function applies between evacuation population and TWET under different TSAs. The joint relationships of TSA, TWET, and population size show that TWET increases with population increase and TSA decrease, and compared with TSA, population influences TWET more strongly. Given a reliable projection of population change and spatial planning of a study area, this method can be useful for government decision making on the location of earthquake emergency shelters and on the allocation of evacuees to those shelters.

ACS Style

Xiujuan Zhao; Wei Xu; Yunjia Ma; Lianije Qin; Junlin Zhang; Ying Wang. Relationships Between Evacuation Population Size, Earthquake Emergency Shelter Capacity, and Evacuation Time. International Journal of Disaster Risk Science 2017, 8, 457 -470.

AMA Style

Xiujuan Zhao, Wei Xu, Yunjia Ma, Lianije Qin, Junlin Zhang, Ying Wang. Relationships Between Evacuation Population Size, Earthquake Emergency Shelter Capacity, and Evacuation Time. International Journal of Disaster Risk Science. 2017; 8 (4):457-470.

Chicago/Turabian Style

Xiujuan Zhao; Wei Xu; Yunjia Ma; Lianije Qin; Junlin Zhang; Ying Wang. 2017. "Relationships Between Evacuation Population Size, Earthquake Emergency Shelter Capacity, and Evacuation Time." International Journal of Disaster Risk Science 8, no. 4: 457-470.

Article
Published: 31 October 2017 in International Journal of Geographical Information Science
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The accurate location and allocation of disaster emergency shelters are key components of effective urban planning and emergency management. Various models have been developed to solve the location-allocation problem, but gaps remain with regard to model realism and associated applicability. For the available location and allocation models of earthquake emergency shelters, uncertainty with respect to earthquake hazard, population exposure, rate of damage to buildings and the effects of evacuee behavior are often neglected or oversimplified. Moreover, modifying the models can be an alternative means of improving the solution quality when the optimization algorithm has difficulty coping with a complex, high-dimensional problem. This article develops a scenario-based hybrid bilevel model that addresses the concerns related to high-dimensional complexity and provides a higher degree of realism by incorporating the uncertainties of population dynamics and earthquake damage scenarios into location-allocation problems for earthquake emergency shelters. A modified particle swarm optimization algorithm combined with a simulated annealing algorithm was applied to derive solutions using the hybrid bilevel model and a conventional multi-objective model, and the solutions obtained using the two models were then compared. The novel features of the study include the hybrid bilevel model that considers the dynamic number of evacuees and its implementation for earthquake emergency shelter location and allocation. The results show that the solutions significantly differ between daytime and nighttime. When applied to the multi-objective model, the optimization algorithm is time consuming and may only find the local optima and provide suboptimal solutions in the considered scenarios with more evacuees. By contrast, the hybrid bilevel model shows more desirable performance because it significantly reduces the dimensionality of the location-allocation problem based on a two-step-to-reach approach. The proposed hybrid bilevel model is proven to be useful for optimal shelter allocation, and the presented results can be used as a reference for balancing the interests of the government and residents during the planning of shelters in Beijing.

ACS Style

Wei Xu; Yunjia Ma; Xiujuan Zhao; Ying Li; Lianjie Qin; Juan Du. A comparison of scenario-based hybrid bilevel and multi-objective location-allocation models for earthquake emergency shelters: a case study in the central area of Beijing, China. International Journal of Geographical Information Science 2017, 32, 236 -256.

AMA Style

Wei Xu, Yunjia Ma, Xiujuan Zhao, Ying Li, Lianjie Qin, Juan Du. A comparison of scenario-based hybrid bilevel and multi-objective location-allocation models for earthquake emergency shelters: a case study in the central area of Beijing, China. International Journal of Geographical Information Science. 2017; 32 (2):236-256.

Chicago/Turabian Style

Wei Xu; Yunjia Ma; Xiujuan Zhao; Ying Li; Lianjie Qin; Juan Du. 2017. "A comparison of scenario-based hybrid bilevel and multi-objective location-allocation models for earthquake emergency shelters: a case study in the central area of Beijing, China." International Journal of Geographical Information Science 32, no. 2: 236-256.

Journal article
Published: 26 August 2017 in International Journal of Environmental Research and Public Health
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In light of global warming, increased extreme precipitation events have enlarged the population exposed to floods to some extent. Extreme precipitation risk assessments are of great significance in China and allow for the response to climate change and mitigation of risks to the population. China is one of the countries most influenced by climate change and has unique national population conditions. The influence of extreme precipitation depends on the degree of exposure and vulnerability of the population. Accurate assessments of the population exposed to rising rainstorm trends are crucial to mapping extreme precipitation risks. Studying the population exposed to rainstorm hazard areas (RSHA) at the microscale is extremely urgent, due to the local characteristics of extreme precipitation events and regional diversity of the population. The spatial distribution of population density was mapped based on the national population census data from China in 1990, 2000 and 2010. RSHA were also identified using precipitation data from 1975–2015 in China, and the rainstorm tendency values were mapped using GIS in this paper. The spatial characteristics of the rainstorm tendencies were then analyzed. Finally, changes in the population in the RSHA are discussed. The results show that the extreme precipitation trends are increasing in southeastern China. From 1990 to 2010, the population in RSHA increased by 110 million, at a rate of 14.6%. The elderly in the region increased by 38 million at a rate of 86.4%. Studying the size of the population exposed to rainstorm hazards at the county scale can provide scientific evidence for developing disaster prevention and mitigation strategies from the bottom up.

ACS Style

PuJun Liang; Wei Xu; Yunjia Ma; Xiujuan Zhao; Lianjie Qin. Increase of Elderly Population in the Rainstorm Hazard Areas of China. International Journal of Environmental Research and Public Health 2017, 14, 963 .

AMA Style

PuJun Liang, Wei Xu, Yunjia Ma, Xiujuan Zhao, Lianjie Qin. Increase of Elderly Population in the Rainstorm Hazard Areas of China. International Journal of Environmental Research and Public Health. 2017; 14 (9):963.

Chicago/Turabian Style

PuJun Liang; Wei Xu; Yunjia Ma; Xiujuan Zhao; Lianjie Qin. 2017. "Increase of Elderly Population in the Rainstorm Hazard Areas of China." International Journal of Environmental Research and Public Health 14, no. 9: 963.

Journal article
Published: 26 April 2017 in ISPRS International Journal of Geo-Information
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The accurate estimation of the dynamic changes in population is a key component in effective urban planning and emergency management. We developed a model to estimate hourly dynamic changes in population at the community level based on subway smart card data. The hourly population of each community in six central districts of Beijing was calculated, followed by a study of the spatiotemporal patterns and diurnal dynamic changes of population and an exploration of the main sources and sinks of the observed human mobility. The maximum daytime population of the six central districts of Beijing was approximately 0.7 million larger than the night-time population. The administrative and commercial districts of Dongcheng and Xicheng had high values of population ratio of day to night of 1.35 and 1.22, respectively, whereas Shijingshan, a residential district, had the lowest value of 0.84. Areas with a high population ratio were mainly concentrated in Dongcheng, Xicheng, West Chaoyang, and Southeast Haidian. The daytime population distribution showed a hierarchical spatial pattern of planar centers and second scattered centers as opposed to multiple scattered centers during the night-time. This was because most people moved inward from the areas with a low–high to high–low population ratio of day to night from night-time to daytime, which can be explained by the process of commuting between residential areas and workplaces. Several distinctive phenomena (e.g., the distribution of new industrial parks, the so-called old residential areas, and colleges and universities) in the development of China are reflected by the spatiotemporal pattern of the distribution of population. The general consistency of the population ratios of day to night, population distribution, population variation of typical communities, and population mobility pattern with previous research suggests that the subway smart card data has potential in analyzing dynamic diurnal variations of urban population. This method can be easily duplicated to calculate hourly dynamic changes in population at the community level. These results can be used to estimate the potential hourly number of evacuees under different temporal scenarios of disasters and to support future urban planning in Beijing.

ACS Style

Yunjia Ma; Wei Xu; Xiujuan Zhao; Ying Li. Modeling the Hourly Distribution of Population at a High Spatiotemporal Resolution Using Subway Smart Card Data: A Case Study in the Central Area of Beijing. ISPRS International Journal of Geo-Information 2017, 6, 128 .

AMA Style

Yunjia Ma, Wei Xu, Xiujuan Zhao, Ying Li. Modeling the Hourly Distribution of Population at a High Spatiotemporal Resolution Using Subway Smart Card Data: A Case Study in the Central Area of Beijing. ISPRS International Journal of Geo-Information. 2017; 6 (5):128.

Chicago/Turabian Style

Yunjia Ma; Wei Xu; Xiujuan Zhao; Ying Li. 2017. "Modeling the Hourly Distribution of Population at a High Spatiotemporal Resolution Using Subway Smart Card Data: A Case Study in the Central Area of Beijing." ISPRS International Journal of Geo-Information 6, no. 5: 128.

Journal article
Published: 17 February 2016 in International Journal of Environmental Research and Public Health
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A study of the frequency, intensity, and risk of extreme climatic events or natural hazards is important for assessing the impacts of climate change. Many models have been developed to assess the risk of multiple hazards, however, most of the existing approaches can only model the relative levels of risk. This paper reports the development of a method for the quantitative assessment of the risk of multiple hazards based on information diffusion. This method was used to assess the risks of loss of human lives from 11 types of meteorological hazards in China at the prefectural and provincial levels. Risk curves of multiple hazards were obtained for each province and the risks of 10-year, 20-year, 50-year, and 100-year return periods were mapped. The results show that the provinces (municipalities, autonomous regions) in southeastern China are at higher risk of multiple meteorological hazards as a result of their geographical location and topography. The results of this study can be used as references for the management of meteorological disasters in China. The model can be used to quantitatively calculate the risks of casualty, direct economic losses, building collapse, and agricultural losses for any hazards at different spatial scales.

ACS Style

Wei Xu; Li Zhuo; Jing Zheng; Yi Ge; Zhihui Gu; Yugang Tian. Assessment of the Casualty Risk of Multiple Meteorological Hazards in China. International Journal of Environmental Research and Public Health 2016, 13, 222 .

AMA Style

Wei Xu, Li Zhuo, Jing Zheng, Yi Ge, Zhihui Gu, Yugang Tian. Assessment of the Casualty Risk of Multiple Meteorological Hazards in China. International Journal of Environmental Research and Public Health. 2016; 13 (2):222.

Chicago/Turabian Style

Wei Xu; Li Zhuo; Jing Zheng; Yi Ge; Zhihui Gu; Yugang Tian. 2016. "Assessment of the Casualty Risk of Multiple Meteorological Hazards in China." International Journal of Environmental Research and Public Health 13, no. 2: 222.

Research article
Published: 07 December 2015 in PLOS ONE
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The correct location of earthquake emergency shelters and their allocation to residents can effectively reduce the number of casualties by providing safe havens and efficient evacuation routes during the chaotic period of the unfolding disaster. However, diverse and strict constraints and the discrete feasible domain of the required models make the problem of shelter location and allocation more difficult. A number of models have been developed to solve this problem, but there are still large differences between the models and the actual situation because the characteristics of the evacuees and the construction costs of the shelters have been excessively simplified. We report here the development of a multi-objective model for the allocation of residents to earthquake shelters by considering these factors using the Chaoyang district, Beijing, China as a case study. The two objectives of this model were to minimize the total weighted evacuation time from residential areas to a specified shelter and to minimize the total area of all the shelters. The two constraints were the shelter capacity and the service radius. Three scenarios were considered to estimate the number of people who would need to be evacuated. The particle swarm optimization algorithm was first modified by applying the von Neumann structure in former loops and global structure in later loops, and then used to solve this problem. The results show that increasing the shelter area can result in a large decrease in the total weighted evacuation time from scheme 1 to scheme 9 in scenario A, from scheme 1 to scheme 9 in scenario B, from scheme 1 to scheme 19 in scenario C. If the funding were not a limitation, then the final schemes of each scenario are the best solutions, otherwise the earlier schemes are more reasonable. The modified model proved to be useful for the optimization of shelter allocation, and the result can be used as a scientific reference for planning shelters in the Chaoyang district, Beijing.

ACS Style

Xiujuan Zhao; Wei Xu; Yunjia Ma; Fuyu Hu. Scenario-Based Multi-Objective Optimum Allocation Model for Earthquake Emergency Shelters Using a Modified Particle Swarm Optimization Algorithm: A Case Study in Chaoyang District, Beijing, China. PLOS ONE 2015, 10, e0144455 .

AMA Style

Xiujuan Zhao, Wei Xu, Yunjia Ma, Fuyu Hu. Scenario-Based Multi-Objective Optimum Allocation Model for Earthquake Emergency Shelters Using a Modified Particle Swarm Optimization Algorithm: A Case Study in Chaoyang District, Beijing, China. PLOS ONE. 2015; 10 (12):e0144455.

Chicago/Turabian Style

Xiujuan Zhao; Wei Xu; Yunjia Ma; Fuyu Hu. 2015. "Scenario-Based Multi-Objective Optimum Allocation Model for Earthquake Emergency Shelters Using a Modified Particle Swarm Optimization Algorithm: A Case Study in Chaoyang District, Beijing, China." PLOS ONE 10, no. 12: e0144455.

Journal article
Published: 06 August 2014 in Stochastic Environmental Research and Risk Assessment
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Risk assessment plays an important role in disaster risk management. Existing multi-hazard risk assessment models are often qualitative or semi-quantitative in nature and used for comparative study of regional risk levels. They cannot estimate directly probability of disaster losses from the joint impact of several hazards. In this paper, a quantitative approach of multi-hazard risk assessment based on vulnerability surface and joint return period of hazards is put forward to assess the risk of crop losses in the Yangtze River Delta region of China. The impact of strong wind and flood, the two most prominent agricultural hazards in the area, is analyzed. The multi-hazard risk assessment process consists of three steps. First, a vulnerability surface, which denotes the functional relationship between the intensity of the hazards and disaster losses, was built using the crop losses data for losses caused by strong wind and flood in the recent 30 years. Second, the joint probability distribution of strong wind and flood was established using the copula functions. Finally, risk curves that show the probability of crop losses in this multi-hazard context at four case study sites were calculated according to the joint return period of hazards and the vulnerability surface. The risk assessment result of crop losses provides a useful reference for governments and insurance companies to formulate agricultural development plans and analyze the market of agricultural insurance. The multi-hazard risk assessment method developed in this paper can also be used to quantitatively assess multi-hazard risk in other regions.

ACS Style

Xiaodong Ming; Wei Xu; Ying Li; Juan Du; Baoyin Liu; Peijun Shi. Quantitative multi-hazard risk assessment with vulnerability surface and hazard joint return period. Stochastic Environmental Research and Risk Assessment 2014, 29, 35 -44.

AMA Style

Xiaodong Ming, Wei Xu, Ying Li, Juan Du, Baoyin Liu, Peijun Shi. Quantitative multi-hazard risk assessment with vulnerability surface and hazard joint return period. Stochastic Environmental Research and Risk Assessment. 2014; 29 (1):35-44.

Chicago/Turabian Style

Xiaodong Ming; Wei Xu; Ying Li; Juan Du; Baoyin Liu; Peijun Shi. 2014. "Quantitative multi-hazard risk assessment with vulnerability surface and hazard joint return period." Stochastic Environmental Research and Risk Assessment 29, no. 1: 35-44.