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An Analysis of Housing Structures’ Earthquake Vulnerability in Two Parts of Dhaka City

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  • Md Sohel Ahmed

    (Graduate School of Information Science and Technology, Osaka University, Osaka 565-0871, Japan)

  • Hiroshi Morita

    (Graduate School of Information Science and Technology, Osaka University, Osaka 565-0871, Japan)

Abstract

The damage done in earthquake disasters is correlated to the types of housing structures that are present. In the last two decades of urbanization in Dhaka, rapid growth without proper planning has been a major concern. This study evaluates the performance of the decision tree and random forest techniques to predict structures’ vulnerability factors for buildings as a step towards improving earthquake disaster preparedness. Applying the decision tree algorithm to locations (wards) in Dhaka North City Corporation (DNCC) and Dhaka South City Corporation (DSCC), we observed some important predictors of earthquake damage. Decision tree analysis reveals that the most important predictor for structures that fare well in earthquakes is the use of reinforced concrete, and a common factor among the most vulnerable structures is the soft story building style in the DNCC and DSCC areas. The random forest technique also showed reinforced concrete as being the most important factor for lowering the risk for housing structures, with the model having a 24.19% out-of-bag (OOB) error. As for vulnerability, soft story construction was a significant factor in estimating earthquake susceptibility (40.32% OOB error). The findings reveal that building materials in the DNCC are stronger than those in the DSCC but soft story buildings are more common in the DNCC, which make it one of the weakest parts of the area and point to the need to make plans to seismically retrofit soft story buildings.

Suggested Citation

  • Md Sohel Ahmed & Hiroshi Morita, 2018. "An Analysis of Housing Structures’ Earthquake Vulnerability in Two Parts of Dhaka City," Sustainability, MDPI, vol. 10(4), pages 1-18, April.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:1106-:d:139972
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    References listed on IDEAS

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    1. Yoshinori Nakagawa, 2017. "The lived experience of preparing for earthquakes in households: a phenomenological psychological study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(3), pages 1825-1844, September.
    2. Mustafa Erdik & Eser Durukal, 2008. "Earthquake risk and its mitigation in Istanbul," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 44(2), pages 181-197, February.
    3. Aftab Alam Khan, 2016. "Geophysical characterization and earthquake hazard vulnerability of Dhaka Mega City, Bangladesh, vis-à-vis impact of scenario earthquakes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(2), pages 1147-1166, June.
    4. Edris Alam & Dale Dominey-Howes, 2014. "An analysis of the AD1762 earthquake and tsunami in SE Bangladesh," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 70(1), pages 903-933, January.
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    Cited by:

    1. Jihye Han & Soyoung Park & Seongheon Kim & Sanghun Son & Seonghyeok Lee & Jinsoo Kim, 2019. "Performance of Logistic Regression and Support Vector Machines for Seismic Vulnerability Assessment and Mapping: A Case Study of the 12 September 2016 ML5.8 Gyeongju Earthquake, South Korea," Sustainability, MDPI, vol. 11(24), pages 1-19, December.
    2. Jihye Han & Jinsoo Kim & Soyoung Park & Sanghun Son & Minji Ryu, 2020. "Seismic Vulnerability Assessment and Mapping of Gyeongju, South Korea Using Frequency Ratio, Decision Tree, and Random Forest," Sustainability, MDPI, vol. 12(18), pages 1-22, September.

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