Probability of Road Interruption due to Landslides under Different Rainfall-Return Periods Using Remote Sensing Techniques
Publication: Journal of Performance of Constructed Facilities
Volume 30, Issue 1
Abstract
Heavy rainfall-induced landslides along mountain routes in Taiwan easily cause road interruption, especially under extreme rainfall conditions. Road interruption due to rainfall-induced landslides is a major problem for Taiwanese authorities. In this study, remote sensing data, including satellite images and aerial photos, were employed to interpret landslides, which were mapped using geographical information systems (GISs). The goal was an event-based landslide inventory. Causative and triggering factors for landslides were adopted in a logistic model to predict landslide occurrence. These factors included lithology, normalized difference vegetation index, slope gradient, slope roughness, maximum elevation, total curvature, total slope height, maximum hourly rainfall, and total accumulated rainfall. With the proposed landslide prediction model, the probability of road interruption due to rainfall-induced landslides was evaluated under different rainfall-return periods. The model was confirmed by careful validation of reported historical events involving road interruption caused by subsequent typhoons. Validation results indicated that the landslide prediction model can be used in predicting road interruption due to rainfall-induced landslides.
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Acknowledgments
This study was supported under a project carried out by the Taiwan Soil and Water Conservation Bureau. In addition, thanks are due to the Taiwan Central Geologic Survey for providing the landslide susceptibility map. Special thanks go to SinoTech Engineering Consultants, Inc., for its assistance and cooperation and for the personnel and employees who participated in the study.
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Published In
Journal of Performance of Constructed Facilities
Volume 30 • Issue 1 • February 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Mar 4, 2014
Accepted: Dec 9, 2014
Published online: Feb 11, 2015
Discussion open until: Jul 11, 2015
Published in print: Feb 1, 2016
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