Seismic Vulnerability Assessment at Urban Scale Based on Different Building Stock Data Sources

P. Ricci, Carlo Del Gaudio, G.M. Verderame, G. Manfredi, M. Pollino, F. Borfecchia

Research output: Contribution to conferencePaper

2 Citations (Scopus)

Abstract

In this study, a seismic vulnerability assessment at urban scale is carried out in a high-seismic city in Southern Italy using building stock data from different sources: (1) data from an airborne Remote Sensing mission carried out over the municipality, providing a detailed estimate of 3D geometric parameters of buildings, and (2) data from a field survey, providing detailed information on geometrical and structural characteristics of each single building. Such data are used within a multilevel approach in order to evaluate the influence of the detail level of input data on seismic vulnerability assessment at urban scale. Data from the detailed field survey are assumed as a reference, and when using Remote Sensing data, due to the lack of information affecting such source, some of the input parameters to the seismic vulnerability assessment procedure are assumed as random variables, using aggregate information on buildings provided by census data. Hence, the error introduced by the use of less detailed (but easier, faster and less expensive to collect) data is analyzed and discussed in order to evaluate the reliability of alternative data sources within a cost/benefit approach to large scale seismic risk assessment.

Conference

Conference2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014
CountryUnited Kingdom
CityLiverpool
Period1/1/14 → …

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality

Cite this

Ricci, P., Del Gaudio, C., Verderame, G. M., Manfredi, G., Pollino, M., & Borfecchia, F. (2014). Seismic Vulnerability Assessment at Urban Scale Based on Different Building Stock Data Sources. Paper presented at 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014, Liverpool, United Kingdom. https://doi.org/10.1061/9780784413609.104