GIS-based seismic hazard prediction system for urban earthquake disaster prevention planning

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1 Tongji University, Shanghai Institute of Disaster Prevention and Relief, Shanghai, P.R China
2 Tongji University, Department of Civil Engineering, Shanghai, P.R China
3 Longfor Properties Company Limited, Suzhou Longfor Properties Company Limited, Suzhou, Jiangsu Province, P. R. China
DOI
10.7287/peerj.preprints.3165v1
Published
Accepted
Subject Areas
Spatial and Geographic Information Systems
Keywords
GIS, Urban Earthquake Disaster Prevention Planning, Seismic hazard Prediction, Aid Decision Making
Copyright
© 2017 Zhai et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Zhai Y, Chen S, OuYang Q. 2017. GIS-based seismic hazard prediction system for urban earthquake disaster prevention planning. PeerJ Preprints 5:e3165v1

Abstract

A basic framework of a GIS-based seismic hazard prediction system for urban earthquake disaster prevention planning is developed in this study, incorporating structural vulnerability analysis, program development, and GIS. The system is integrated with proven building vulnerability analysis models, data search function, spatial analysis function, and plotting function, realizing the batching and automation of seismic hazard prediction and the interactive visualization of predicted results. The system is applied to a test area and the results are compared with results from previous studies to verify that the system can provide data support and aid decisionmaking for the establishment and implementation of urban earthquake disaster prevention planning. Results from this study are essentially the same as the results of 2003 and slightly better than the results of 1993, which highlights the reliability of the fragility analysis method applied in this system.

Author Comment

This is a submission to PeerJ Computer Science for review.