Developing a damage assessment model for bridge surroundings: a study of the disaster caused by Typhoon Morakot in Taiwan

NCUIR > Engineering College > Department of Civil Engineering > journal & Dissertation > Item 987654321/99895

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/99895

Title:	Developing a damage assessment model for bridge surroundings: a study of the disaster caused by Typhoon Morakot in Taiwan
Authors:	陳介豪;Chen, Jieh-Haur;Su, Mu-Chun;Chen, Chang-Yi;Lin, Shih-Chieh
Contributors:	工學院土木工程學系
Keywords:	ANN;Applied sciences;bridge;Bridges;Building failures (cracks, physical changes, etc.);Buildings. Public works;Climatology and bioclimatics for buildings;Computation methods. Tables. Charts;damage assessment;Disasters;Durability. Pathology. Repairing. Maintenance;Exact sciences and technology;fuzzy;Fuzzy logic;optimisation;Optimization algorithms;remote sensing imagery;Rivers;SOM;Storm damage;Structural analysis. Stresses;typhoon disaster;Typhoons;Vegetation
Date:	2014-01-01
Issue Date:	2026-04-21 13:40:02 (UTC+8)
Publisher:	Taylor and Francis Ltd.;Colchester: Taylor & Francis
Abstract:	摘要： Typhoon Morakot has been the most severe typhoon disaster to strike Taiwan in recent decades causing tremendous damage to bridge surroundings in 2009. However, we still lack a means of assessing post-typhoon damage for follow-up rebuilding. This paper presents an integrated model that automatically measures changes in rivers, areas of damage to bridge surroundings, and changes in vegetation. The proposed model is based on a neurofuzzy mechanism enhanced by the self-organising map optimisation algorithm and also includes the particular functions of dilation, erosion, and skeletonisation to deal with river imagery. High resolution FORMOSAT-2 satellite imagery from before and after the invasion period is adopted. A bridge is randomly selected from the 129 destroyed due to the typhoon for applications of the model. The recognition results show that the river average width has increased 66% with a maximum increase of over 200%. The ruined segment of the bridge is located exactly in the most scoured region. There has also been a nearly 10% reduction in the vegetation coverage. The results yielded by the proposed model demonstrate a pinpoint accuracy rate of 99.94%. This study successfully develops a tool for large-scale damage assessment as well as for precise measurement after disasters. 出版者： Colchester: Taylor & Francis 出版日期： 2014-01-02 出處： Civil engineering and environmental systems, 2014-01, Vol.31 (1), p.24-35 資源來源： EBSCOhost Academic Search Premier 版權： 2013 Taylor & Francis 2013 版權： 2015 INIST-CNRS 版權： Copyright Taylor & Francis Ltd. 2014 識別號： ISSN: 1028-6608 識別號： EISSN: 1029-0249 識別號： DOI: 10.1080/10286608.2013.820278
Appears in Collections:	[Department of Civil Engineering] journal & Dissertation

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	12	View/Open

社群 sharing

Loading...