Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/164066
Title: Seismic loss dynamics in three Asian megacities using a macro-level approach based on socioeconomic exposure indicators
Authors: Sarica, Gizem Mestav
Pan, Tso-Chien
Keywords: Science::Geology
Issue Date: 2022
Source: Sarica, G. M. & Pan, T. (2022). Seismic loss dynamics in three Asian megacities using a macro-level approach based on socioeconomic exposure indicators. Communications Earth & Environment, 3(1). https://dx.doi.org/10.1038/s43247-022-00430-9
Journal: Communications Earth & Environment
Abstract: Scrutinizing the evolving exposure and possible consequent forthcoming seismic losses in rapidly urbanizing megacities is essential for decision-makers. Here we present a framework for the evaluation of spatio-temporal seismic loss dynamics where we propose a probabilistic macro-level loss estimation approach that is based on socioeconomic exposure indicators. We follow this framework to model the urban growth, disaggregate population to urban cells, and estimate grid-level wealth in three Asian megacities, namely Jakarta, Metro Manila, and Istanbul. Then, we calculate present and future probabilistic risk metrics based on the combination of evolving exposure, probabilistic seismic hazard analysis and vulnerability curves. The results reveal that our approach can produce present loss estimates that are in the same order of magnitude as the conventional approaches. The predictions suggest that present average annual loss could increase almost twofold in Jakarta and in Metro Manila, and by almost 57% in Istanbul by 2030. Our framework can be used to trigger discussions between scientific community and decision-makers for better long-term risk reduction and risk awareness strategies.
URI: https://hdl.handle.net/10356/164066
ISSN: 2662-4435
DOI: 10.1038/s43247-022-00430-9
Schools: School of Civil and Environmental Engineering 
Interdisciplinary Graduate School (IGS) 
Research Centres: Institute of Catastrophe Risk Management 
Rights: © The Author(s) 2022. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:CEE Journal Articles
IGS Journal Articles

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