1,720,995 research outputs found
Machine learning and hydrodynamic proxies for enhanced rapid tsunami vulnerability assessment
Full text linkCoastal communities in various regions of the world are exposed to risk from tsunami inundation, requiring reliable modeling tools for implementing effective disaster preparedness and management strategies. This study advocates for comprehensive multi-variable models and emphasizes the limitations of traditional univariate fragility functions by leveraging a large, detailed dataset of ex-post damage surveys for the 2011 Great East Japan tsunami, hydrodynamic modeling of the event, and advanced machine learning techniques. It investigates the complex interplay of factors influencing building vulnerability to tsunami, with a specific focus on the hydrodynamic effects associated to tsunami propagation on land. Novel synthetic variables representing shielding and debris impact mechanisms prove to be suitable proxies for water velocity, offering a practical solution for rapid damage assessments, especially in post-event scenarios or large-scale analyses. Machine learning then emerges as a promising approach to tackle the complexities of vulnerability assessment, while providing valuable and interpretable insights.Hydrodynamic modelling and machine learning-based methods can effectively model tsunami damage mechanisms and represent an improvement over traditional univariate fragility functions for vulnerability assessments
Leveraging data driven approaches for enhanced tsunami damage modelling: Insights from the 2011 Great East Japan event
No full textThis study aims at 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 after the 2011 Great East Japan event in the Tōhoku region. By implementing simple geospatial tools, the dataset is integrated with additional explanatory variables, including, among others, factors accounting for the mutual interaction between the inundated structures. Tests on models’ sensitivity to the number and type of input features used for model development reveal the importance, on the predictive performance, of considering usually neglected mechanisms like the shielding effect and the debris impact generation. The analysis for the potential spatial transferability indicates a reduction in the accuracy, thus suggesting a better suitability of empirical models for descriptive purposes, limiting their predictive ability only to region-specific cases
Consideration of submarine landslide induced by 2018 Sulawesi earthquake and tsunami within Palu Bay
No full textOn September 28 2018, an Mw 7.5 strike-slip earthquake occurred to the north of Palu Bay on the Sulawesi Island, Indonesia. This triggered a destructive tsunami within the bay, which reached Palu city. Simulation have been conducted to investigate the landslide source. However, the tsunami should be investigated considering a physical model in the area where detailed bathymetric survey had not been conducted. In this study, we investigated the impact of coastal landslides on the southern part of the bay using a two-layer model. Owing to the increasing collapse volume, the southern west coastal landslide could approximately explain the observations in Palu city. However, the calculated mass volume of the source largely overestimated the bathymetric survey data. Hence, we considered the possibility of submarine landslide in the southern part of the bay and the simulation results could approximately explain the maximum tsunami heights in the southern part of the bay. These results suggest that more detailed multibeam data will be required to investigate the possible submarine landslide in the southern area which could induce a destructive tsunami reaching Palu city within a few minutes after the collapse.</p
Tsunami Risk Assessment to Coastal Population and Building in Thailand
Full text link博士学位論文の要旨及び審査結果の要旨 (Summary of Thesis(DR))othe
Extended MLIT dataset for the 2011 Great East Japan tsunami (Tōhoku region)
No full textThe 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)
マッピングによる災害レジリエンス構築：社会的脆弱性の高い人々へ着目した研究
No full text本研究では、災害に対する脆弱性が高い層の中でも、LGBTQ+の人々を対象に、彼らの持つ社会的脆弱性の特徴とそれに基づく人権に配慮した災害時支援の在り方について明らかにすることを目的として行った。平時から社会的排除の対象となっている彼らが、現状の災害対応方策において災害時に十分な支援を受けられるのか、当事者のニーズと現在の災害対応のギャップを明らかにするために、当事者への可能な限りの配慮を行いながら、当事者および関係者へのインタビュー調査およびWEB調査を実施した。その結果、現状の災害対応、特に要配慮者支援方策は、当事者および家族からの「支援が必要である」という意思表示と、支援のための個人情報の開示が前提条件となっており、個人情報の開示そのものが社会的、経済的、精神的、身体的ハイリスクにつながる状況に置かれているLGBTQ+の方々に対する支援が難しいことが確認され、この発見から、これまでの要配慮者対策とは全く違う、アセットマッピングのような支援方策の新設が急務であることが明らかになった
Empirical multi-variable tsunami damage models based on the 2011 Great East Japan dataset: analysis of the performances at different spatial scales
No full textBy implementing data-driven models for the 2011 Great East Japan earthquake and tsunami, the present study aims at investigating the effect of the level of spatial aggregation of the data on model’s predictive ability and at identifying the possible existence of regional-dependent patterns affecting model's accuracy and feature importance. An extended version of the dataset compiled by the Japanese Ministry of Land, Infrastructure and Transportation (MLIT) after the 2011 event in the Tōhoku region was used to generate sub datasets at different spatial scales, ranging from individual cities of different sizes to clusters at regional and multiregional levels. The results indicate a high variance in the accuracy for the models trained on the different subsets, with relative hit rates ranging from 0.68 to 0.89 and exhibiting a positive correlation with the cardinality of the sets, as well as some regional patterns in the prediction errors. The cluster-averaged feature importance is observed to be stable for all selections and reflects the results obtained from the models trained on the whole dataset, thus allowing a more informed identification of the most significant influencing factors for tsunami damage modelling
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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