Utilizing Google Street View for Rapid Seismic Vulnerability Assessment: Case Study in the City of Manila, Philippines

2021 ◽  
Author(s):  
Marcus Karl Evangelista ◽  
Diocel Harold Aquino ◽  
Jamie Alea Ramos
Keyword(s):  
Vulnerability Assessment ◽  
Seismic Vulnerability ◽  
Seismic Vulnerability Assessment ◽  
Google Street View ◽  
Street View ◽  
The City

scholarly journals Performance of Logistic Regression and Support Vector Machines for Seismic Vulnerability Assessment and Mapping: A Case Study of the 12 September 2016 ML5.8 Gyeongju Earthquake, South Korea

2019 ◽  
Vol 11 (24) ◽  
pp. 7038 ◽  
Author(s):  
Jihye Han ◽  
Soyoung Park ◽  
Seongheon Kim ◽  
Sanghun Son ◽  
Seonghyeok Lee ◽  
...  
Keyword(s):  
Logistic Regression ◽  
South Korea ◽  
Vulnerability Assessment ◽  
Seismic Vulnerability ◽  
Spatial Databases ◽  
Support Vector ◽  
Seismic Vulnerability Assessment ◽  
The Common ◽  
Gyeongju Earthquake

In this study, we performed seismic vulnerability assessment and mapping of the ML5.8 Gyeongju Earthquake in Gyeongju, South Korea, as a case study. We applied logistic regression (LR) and four kernel models based on the support vector machine (SVM) learning method to derive suitable models for assessing seismic vulnerabilities; the results of each model were then mapped and evaluated. Dependent variables were quantified using buildings damaged in the 9.12 Gyeongju Earthquake, and independent variables were constructed and used as spatial databases by selecting 15 sub-indicators related to earthquakes. Success and prediction rates were calculated using receiver operating characteristic (ROC) curves. The success rates of the models (LR, SVM models based on linear, polynomial, radial basis function, and sigmoid kernels) were 0.652, 0.649, 0.842, 0.998, and 0.630, respectively, and the prediction rates were 0.714, 0.651, 0.804, 0.919, and 0.629, respectively. Among the five models, RBF-SVM showed the highest performance. Seismic vulnerability maps were created for each of the five models and were graded as safe, low, moderate, high, or very high. Finally, we examined the distribution of building classes among the 23 administrative districts of Gyeongju. The common vulnerable regions among all five maps were Jungbu-dong and Hwangnam-dong, and the common safe region among all five maps was Gangdong-myeon.

Large-Scale Seismic Vulnerability Assessment Method for Urban Centres. An Application to the City of Florence

2014 ◽  
Vol 628 ◽  
pp. 49-54 ◽  
Author(s):  
Maurizio Ripepe ◽  
Giorgio Lacanna ◽  
Pauline Deguy ◽  
Mario de Stefano ◽  
Valentina Mariani ◽  
...  
Keyword(s):  
Vulnerability Assessment ◽  
Large Scale ◽  
Seismic Vulnerability ◽  
Risk Mitigation ◽  
Structural Features ◽  
Assessment Method ◽  
Ground Acceleration ◽  
Seismic Vulnerability Assessment ◽  
Damage Scenarios ◽  
The City

The seismic vulnerability assessment of a building requires a comprehensive knowledge of both building structural features and soils geophysical parameters. To achieve a vulnerability assessment at the urban scale a large amount of data would be necessary, with a consequent involvement of time and economical resources. The aim of this paper is hence to propose a simplified procedure to evaluate the seismic vulnerability of urban centres and possible seismic damage scenarios in order to identify critical areas and/or building typologies to plan future actions of seismic risk mitigation and prevention. The procedure is applied to the outstanding case study of the city of Florence. The research is based on the definition of major building typologies related to construction periods and type of the structural system (masonry or reinforced concrete), the identification of a set of sample buildings, the analysis of the dynamic behaviour and the evaluation of a vulnerability index with an expeditious approach. The obtained results allow to define potential vulnerability and post-event damage scenarios related to the expected levels of peak ground acceleration.

Seismic vulnerability assessment of historical urban centres: case study of the old city centre in Seixal, Portugal

2013 ◽  
Vol 11 (5) ◽  
pp. 1753-1773 ◽  
Author(s):  
Tiago Miguel Ferreira ◽  
Romeu Vicente ◽  
J. A. R. Mendes da Silva ◽  
Humberto Varum ◽  
Aníbal Costa
Keyword(s):  
Vulnerability Assessment ◽  
Seismic Vulnerability ◽  
City Centre ◽  
Seismic Vulnerability Assessment ◽  
Old City
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