The dataset contains the additional explanatory variables used in the paper "Leveraging data driven approaches for enhanced tsunami damage modelling: insights from the 2011 Great East Japan event" (doi: 10.1016/j.envsoft.2022.105604) for developing an empirical, multi-variable tsunami damage model for buildings, based on machine-learning algorithms which leverage about 250.000 ex-post data surveyed by the Japanese Ministry of Land, Infrastructure and Transportation (MLIT) after the 2011 Great East Japan event in the Tōhoku region. The present dataset includes only the new features computed in the mentioned study, while the original MLIT dataset is publicly available from the website of the Ministry of Land, Infrastructure, and Transportation of Japan http://www.mlit.go.jp/toshi/toshi-hukkou-arkaibu.html (and related webGIS (doi: 10.5638/thagis.21.87): http://fukkou.csis.u-tokyo.ac.jp/, for registered users).
Extended MLIT dataset for the 2011 Great East Japan tsunami (Tōhoku region)
Anna Rita Scorzini;Mario Di Bacco;
2022-01-01
Abstract
The dataset contains the additional explanatory variables used in the paper "Leveraging data driven approaches for enhanced tsunami damage modelling: insights from the 2011 Great East Japan event" (doi: 10.1016/j.envsoft.2022.105604) for developing an empirical, multi-variable tsunami damage model for buildings, based on machine-learning algorithms which leverage about 250.000 ex-post data surveyed by the Japanese Ministry of Land, Infrastructure and Transportation (MLIT) after the 2011 Great East Japan event in the Tōhoku region. The present dataset includes only the new features computed in the mentioned study, while the original MLIT dataset is publicly available from the website of the Ministry of Land, Infrastructure, and Transportation of Japan http://www.mlit.go.jp/toshi/toshi-hukkou-arkaibu.html (and related webGIS (doi: 10.5638/thagis.21.87): http://fukkou.csis.u-tokyo.ac.jp/, for registered users).Pubblicazioni consigliate
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