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DC Field | Value | Language |
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dc.contributor.author | Suchat Tachaudomdach | en_US |
dc.contributor.author | Auttawit Upayokin | en_US |
dc.contributor.author | Nopadon Kronprasert | en_US |
dc.contributor.author | Kriangkrai Arunotayanun | en_US |
dc.date.accessioned | 2022-10-16T07:10:41Z | - |
dc.date.available | 2022-10-16T07:10:41Z | - |
dc.date.issued | 2021-03-02 | en_US |
dc.identifier.issn | 20711050 | en_US |
dc.identifier.other | 2-s2.0-85103120459 | en_US |
dc.identifier.other | 10.3390/su13063172 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85103120459&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/76481 | - |
dc.description.abstract | Amidst sudden and unprecedented increases in the severity and frequency of cli-mate-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. | en_US |
dc.subject | Energy | en_US |
dc.subject | Environmental Science | en_US |
dc.subject | Social Sciences | en_US |
dc.title | Quantifying road-network robustness toward flood-resilient transportation systems | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | Sustainability (Switzerland) | en_US |
article.volume | 13 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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