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1. Tachaudomdach, S. (2017). The Strategies to Prevent Flooding for Human Health: A Case Study of Wiang Kum Kam Ancient City, Tambon Tha Wang Tan, Chiang Mai, Thailand. The 5th Asian Symposium on Healthcare Without Borders was held. (Japan) 2. Tachaudomdach, S. (2017). Factors Affecting traffic accidents in Thailand. Paper presented at the Proceedings of ITS Asia- Pacific Form & Exhibition 2017. (Hong Kong) 3. Tachaudomdach, S., Arunotayanun, K., & Upayokin, A. (2018, December). A systematic review of the resilience of transportation infrastructures affected by flooding. In Proceedings of the Asia-Pacific Conference on Intelligent Medical 2018 & International Conference on Transportation and Traffic Engineering 2018 (pp. 176-182). (China) 4. Tachaudomdach, S., Arunotayanun, K., & Upayokin, A. (2019). Comparative Analysis of Modeling Approaches for Evaluating Transportation Network Resilience against Disasters. In Proceedings of the 14th International Conference of Logistics and SCM System. (Taiwan)
Amidst sudden and unprecedented increases in the severity and frequency of climate-change-induced natural disasters, building critical infrastructure resilience has become a prominent policy issue globally for reducing disaster risks. Sustainable measures and procedures to strengthen preparedness, response, and recovery of infrastructures are urgently needed, but the standard for measuring such resilient elements has yet to be consensually developed. This study was undertaken with an aim to quantitatively measure transportation infrastructure robustness, a proactive dimension of resilience capacities and capabilities to withstand disasters; in this case, floods. A four-stage analytical framework was empirically implemented: (1) specifying the system and disturbance (i.e., road network and flood risks in Chiang Mai, Thailand), (2) illustrating the system response using the damaged area as a function of floodwater levels and protection measures, (3) determining recovery thresholds based on land use and system functionality, and (4) quantifying robustness through the application of edge- and node-betweenness centrality models. Various quantifiable indicators of transportation robustness can be revealed; not only flood-damaged areas commonly considered in flood-risk management and spatial planning, but also the numbers of affected traffic links, nodes, and cars are highly valuable for transportation planning in achieving sustainable flood-resilient transportation systems.
Suchat Tachaudomdach; Auttawit Upayokin; Nopadon Kronprasert; Kriangkrai Arunotayanun. Quantifying Road-Network Robustness toward Flood-Resilient Transportation Systems. Sustainability 2021, 13, 3172 .
AMA StyleSuchat Tachaudomdach, Auttawit Upayokin, Nopadon Kronprasert, Kriangkrai Arunotayanun. Quantifying Road-Network Robustness toward Flood-Resilient Transportation Systems. Sustainability. 2021; 13 (6):3172.
Chicago/Turabian StyleSuchat Tachaudomdach; Auttawit Upayokin; Nopadon Kronprasert; Kriangkrai Arunotayanun. 2021. "Quantifying Road-Network Robustness toward Flood-Resilient Transportation Systems." Sustainability 13, no. 6: 3172.