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Mapping Seismic Vulnerability and Risk of Cities: The MASSIVE Project
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作者 Charalampos Kontoes Themistoklis Herekakis +8 位作者 Emmanouela Ieronymidi Iphigenia Keramitsoglou Anna Fokaefs Gerasimos A. Papadopoulos Sideris Paralikidis Dorothea Aifantopoulou Anna Maria Deflorio Daniela Iasillo Chris T. Kiranoudis 《Journal of Earth Science and Engineering》 2012年第8期496-513,共18页
MASSIVE (mapping seismic vulnerability and risk of cities) is a GIS-based earthquake preparedness system that was developed under the European Union Civil Protection Mechanism project (GA No. 070401/2009/540429/SUB... MASSIVE (mapping seismic vulnerability and risk of cities) is a GIS-based earthquake preparedness system that was developed under the European Union Civil Protection Mechanism project (GA No. 070401/2009/540429/SUB/A4), in order to provide civil protection authorities with accurate, and easily transferable tools for generating up-to-date maps of seismic hazard, seismic vulnerability and seismic risk of buildings, at the scale of the single building block. In addition, MASSIVE developed and ran state-of-the-art models to assess the risk for population evacuation in dense urban agglomerations given an earthquake event. The MASSIVE methodology was designed, implemented and validated considering two European pilot sites, heavily struck by recent earthquakes, which are the western part of the Larger Metropolitan Area of Athens (GR), and the city of L' Aquila in the Abruzzo Region (IT). The validation of the results using past earthquake records shows that the performance of MASSIVE is prosperous, achieving a correlation between the modeled and the on-site measured PGAs (peak ground accelerations) higher than 0.75, while the correlation between the on-site reported building damages and the ones predicted by the MASSIVE system has been of the order of 0.80. 展开更多
关键词 MASSIVE seismic risk damage assessment building vulnerability evacuation risk.
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Simulation-Based and Risk-Informed Assessment of the Effectiveness of Tsunami Evacuation Routes Using Agent-Based Modeling:A Case Study of Seaside,Oregon
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作者 Zhenqiang Wang Gaofeng Jia 《International Journal of Disaster Risk Science》 SCIE CSCD 2022年第1期66-86,共21页
Typically,tsunami evacuation routes are marked using signs in the transportation network and the evacuation map is made to educate people on how to follow the evacuation route.However,tsunami evacuation routes are usu... Typically,tsunami evacuation routes are marked using signs in the transportation network and the evacuation map is made to educate people on how to follow the evacuation route.However,tsunami evacuation routes are usually identified without the support of evacuation simulation,and the route effectiveness in the reduction of evacuation risk is typically unknown quantitatively.This study proposes a simulation-based and risk-informed framework for quantitative evaluation of the effectiveness of evacuation routes in reducing evacuation risk.An agentbased model is used to simulate the tsunami evacuation,which is then used in a simulation-based risk assessment framework to evaluate the evacuation risk.The route effectiveness in reducing the evacuation risk is evaluated by investigating how the evacuation risk varies with the proportion of the evacuees that use the evacuation route.The impacts of critical risk factors such as evacuation mode(for example,on foot or by car)and population size and distribution on the route effectiveness are also investigated.The evacuation risks under different cases are efficiently calculated using the augmented sample-based approach.The proposed approach is applied to the riskinformed evaluation of the route effectiveness for tsunami evacuation in Seaside,Oregon.The evaluation results show that the route usage is overall effective in reducing the evacuation risk in the study area.The results can be used for evacuation preparedness education and hence effective evacuation. 展开更多
关键词 Agent-based model risk-informed evaluation Route effectiveness Simulation-based framework Tsunami evacuation risk Tsunami preparedness education
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