Seismic loss dynamics in three Asian megacities using a macro-level approach based on socioeconomic exposure indicators
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 estimatio...
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sg-ntu-dr.10356-1640662023-01-04T01:53:45Z Seismic loss dynamics in three Asian megacities using a macro-level approach based on socioeconomic exposure indicators Sarica, Gizem Mestav Pan, Tso-Chien School of Civil and Environmental Engineering Interdisciplinary Graduate School (IGS) Institute of Catastrophe Risk Management Science::Geology Hazard Assessment Megacity 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. Monetary Authority of Singapore Nanyang Technological University Published version The authors would like to acknowledge the partial financial support for this work provided by the Institute of Catastrophe Risk Management, Nanyang Technological University, Singapore and the Monetary Authority of Singapore (MAS). 2023-01-04T01:53:45Z 2023-01-04T01:53:45Z 2022 Journal Article 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 2662-4435 https://hdl.handle.net/10356/164066 10.1038/s43247-022-00430-9 2-s2.0-85130471374 1 3 en Communications Earth & Environment © 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/. application/pdf |
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Science::Geology Hazard Assessment Megacity Sarica, Gizem Mestav Pan, Tso-Chien Seismic loss dynamics in three Asian megacities using a macro-level approach based on socioeconomic exposure indicators |
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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. |
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School of Civil and Environmental Engineering |
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School of Civil and Environmental Engineering Sarica, Gizem Mestav Pan, Tso-Chien |
format |
Article |
author |
Sarica, Gizem Mestav Pan, Tso-Chien |
author_sort |
Sarica, Gizem Mestav |
title |
Seismic loss dynamics in three Asian megacities using a macro-level approach based on socioeconomic exposure indicators |
title_short |
Seismic loss dynamics in three Asian megacities using a macro-level approach based on socioeconomic exposure indicators |
title_full |
Seismic loss dynamics in three Asian megacities using a macro-level approach based on socioeconomic exposure indicators |
title_fullStr |
Seismic loss dynamics in three Asian megacities using a macro-level approach based on socioeconomic exposure indicators |
title_full_unstemmed |
Seismic loss dynamics in three Asian megacities using a macro-level approach based on socioeconomic exposure indicators |
title_sort |
seismic loss dynamics in three asian megacities using a macro-level approach based on socioeconomic exposure indicators |
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2023 |
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https://hdl.handle.net/10356/164066 |
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1754611297242054656 |