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

Abstract

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.

Keywords:

• remote sensing imagery
• damage assessment
• typhoon disaster
• bridge
• ANN
• fuzzy
• SOM
• optimisation

Acknowledgements

This work was partly supported by the National Science Council (NSC) under the grant number of NSC-99-2621-M-008-005.