Urban Earthquake Vulnerability Assessment and Mapping at the Microscale Based on the Catastrophe Progression Method

Deniz Ger&#231;ek; &#304;smail Talih G&#252;ven

doi:10.1007/s13753-023-00512-y

Volume 14 Issue 5

Nov. 2023

Turn off MathJax

Article Contents

Article Navigation > International Journal of Disaster Risk Science > 2023 > 14(5): 768-781

Deniz Gerçek, İsmail Talih Güven. Urban Earthquake Vulnerability Assessment and Mapping at the Microscale Based on the Catastrophe Progression Method[J]. International Journal of Disaster Risk Science, 2023, 14(5): 768-781. doi: 10.1007/s13753-023-00512-y

Citation:

Deniz Gerçek, İsmail Talih Güven. Urban Earthquake Vulnerability Assessment and Mapping at the Microscale Based on the Catastrophe Progression Method[J]. International Journal of Disaster Risk Science, 2023, 14(5): 768-781. doi: 10.1007/s13753-023-00512-y

Citation:

PDF

Urban Earthquake Vulnerability Assessment and Mapping at the Microscale Based on the Catastrophe Progression Method

doi: 10.1007/s13753-023-00512-y

Deniz Gerçek¹,
İsmail Talih Güven²

1. Department of City and Regional Planning, Faculty of Architecture, İzmir Institute of Technology, 35430, Izmir, Turkey;
2. Department of Geophysics Engineering, Kocaeli University, 41001, Kocaeli, Turkey

Funds:

-19-06.

This study was supported by the Disaster and Emergency Management Presidency under Project No. AFAD-UDAP-Ç

Accepted Date: 2023-10-04

Available Online: 2023-11-23

Publish Date: 2023-11-06

Abstract

Abstract

Vulnerability assessment and mapping play a crucial role in disaster risk reduction and planning for adaptation to a future earthquake. Turkey is one of the most at-risk countries for earthquake disasters worldwide. Therefore, it is imperative to develop effective earthquake vulnerability assessment and mapping at practically relevant scales. In this study, a holistic earthquake vulnerability index that addresses the multidimensional nature of earthquake vulnerability was constructed. With the aim of representing the vulnerability as a continuum across space, buildings were set as the smallest unit of analysis. The study area is in İzmit City of Turkey, with the exposed human and structural elements falling inside the most hazardous zone of seismicity. The index was represented by the building vulnerability, socioeconomic vulnerability, and vulnerability of the built environment. To minimize the subjectivity and uncertainty that the vulnerability indices based on expert knowledge are suffering from, an extension of the catastrophe progression method for the objective weighing of indicators was proposed. Earthquake vulnerability index and components were mapped, a local spatial autocorrelation metric was employed where the hotspot maps demarcated the earthquake vulnerability, and the study quantitatively revealed an estimate of people at risk. With its objectivity and straightforward implementation, the method can aid decision support for disaster risk reduction and emergency management.
- Catastrophe progression method,
- Earthquake vulnerability index,
- Hotspots,
- Microscale,
- Turkey

FullText(HTML)

References(70)

References

[1]	AFAD (Afet ve Acil Durum Yönetimi Başkanlığı / Disaster and Emergency Management Presidency). 2023. Turkey earthquake hazard map (Türkiye Deprem Tehlike Haritası). https://tdth.afad.gov.tr/TDTH/main.xhtml. Accessed 10 Jul 2023 (in Turkish).
[2]	Ahmed, K., S. Shahid, S. Harun, T. Ismail, N. Nawaz, and S. Shamsudin. 2015. Assessment of groundwater potential zones in an arid region based on catastrophe theory. Earth Science Informatics 8(3): 539-549.
[3]	Aksha, S.K., L. Juran, L.M. Resler, and Y. Zhang. 2019. An analysis of social vulnerability to natural hazards in Nepal using a modified social vulnerability index. International Journal of Disaster Risk Science 10(1): 103-116.
[4]	Allan, P., and M. Bryant. 2011. Resilience as a framework for urbanism and recovery. Journal of Landscape Architecture 6: 34-45.
[5]	Ara, S. 2014. Impact of temporal population distribution on earthquake loss estimation: A case study on Sylhet, Bangladesh. International Journal of Disaster Risk Science 5(3): 296-312.
[6]	Armaş, I., D. Toma-Danila, R. Ionescu, and A. Gavriş. 2017. Vulnerability to earthquake hazard: Bucharest case study, Romania. International Journal of Disaster Risk Science 8(2): 182-195.
[7]	Aubrecht, C., S. Freire, C. Neuhold, A. Curtis, and K. Steinnocher. 2012. Introducing a temporal component in spatial vulnerability analysis. Disaster Advances 5(2): 48-53.
[8]	Bağcı, G., A. Yatman, S. Özdemir, and N. Altın. 2000. The earthquakes causing damage in Turkey (Türkiye’de Hasar Yapan Depremler). Earthquake Research Bulletin (Deprem Araştırma Bülteni) 69: 113-126.
[9]	Barbat, A.H., M.L. Carreño, L.G. Pujades, N. Lantada, O.D. Cardona, and M.C. Marulanda. 2009. Seismic vulnerability and risk evaluation methods for urban areas: A review with application to a pilot area. Structure and Infrastructure Engineering 6(1-2): 17-38.
[10]	Birkmann, J. 2006. Measuring vulnerability to promote disaster-resilient societies: Conceptual frameworks and definitions. In Measuring vulnerability to natural hazards: Towards disaster resilient societies, ed. J. Birkmann, 9-54. Tokyo: United Nations University Press.
[11]	Bohle, H. 2001. Vulnerability and criticality: Perspectives from social geography. IHDP Update 2(1): 3-5.
[12]	Brecht, H., U. Deichmann, and H.G. Wang. 2013. A global urban risk index. Policy research working papers 6506. Washington, DC: The World Bank.
[13]	Cardona, O.D. 2004. The need for rethinking the concepts of vulnerability and risk from a holistic perspective: A necessary review and criticism for effective risk management. In Mapping vulnerability: Disasters, development and people, ed. G. Bankoff, G. Frerks, and D. Hilhost, 37-51. London: Earthscan.
[14]	Carreño, M., O.D. Cardona, and A.H. Barbat. 2007. Urban seismic risk evaluation: A holistic approach. Natural Hazards 40(1): 137-172.
[15]	Carreño, M.L., O.D. Cardona, A.H. Barbat, D.C. Suarez, M.P. Perez, and L. Narvaez. 2017. Holistic disaster risk evaluation for the urban risk management plan of Manizales, Colombia. International Journal of Disaster Risk Science 8(2): 258-269.
[16]	Chen, Y., J. Yu, and S. Khan. 2010. Spatial sensitivity analysis of multi-criteria weights in GIS-based land suitability evaluation. Environmental Modelling & Software 25(12): 1582-1591.
[17]	Cheng, C.-H., Y. Liu, and Y. Lin. 1996. Evaluating a weapon system using catastrophe series based on fuzzy scales. Proceedings of the 1996 Asian Fuzzy Systems Symposium, 11-14 December 1996, Kenting, 212-217.
[18]	Cutter, S.L. 1996. Vulnerability to environmental hazards. Progress in Human Geography 20(4): 529-539.
[19]	Cutter, S.L., and C. Finch. 2008. Temporal and spatial changes in social vulnerability to natural hazards. Proceedings of the National Academy of Sciences 105(7): 2301-2306.
[20]	Cutter, S.L., B.J. Boruff, and W.L. Shirley. 2003. Social vulnerability to environmental hazards. Social Science Quarterly 84(2): 242-261.
[21]	Davidson, R. 1997. EERI annual student paper award a multidisciplinary urban earthquake disaster risk index. Earthquake Spectra 13(2): 211-223.
[22]	DBYBHY (Deprem Bölgelerinde Yapılacak Binalar Hakkında Yönetmelik / Regulation on buildings to be constructed in earthquake zones). 2007. https://www.resmigazete.gov.tr/eskiler/2007/03/20070306-3.htm. Accessed 10 Jul 2023.
[23]	Diaz-Sarachaga, J.M., and D. Jato-Espino. 2019. Analysis of vulnerability assessment frameworks and methodologies in urban areas. Natural Hazards 100(1): 437-457.
[24]	Du, X., X. Liu, and Y. Zihang. 2022. Risk assessment of agricultural drought based on catastrophe progression method: A China case study. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4034084.
[25]	Ebert, A., N. Kerle, and A. Stein. 2009. Urban social vulnerability assessment with physical proxies and spatial metrics derived from air and spaceborne imagery and GIS data. Natural Hazards 48(2): 275-294.
[26]	Fekete, A. 2019. Social vulnerability (re-)assessment in context to natural hazards: Review of the usefulness of the spatial indicator approach and investigations of validation demands. International Journal of Disaster Risk Science 10(2): 220-232.
[27]	FEMA (Federal Emergency Management Agency). 2015. Rapid visual screening of buildings for potential seismic hazards: A handbook, 3rd edn. https://www.fema.gov/sites/default/files/2020-07/fema_earthquakes_rapid-visual-screening-of-buildings-for-potential-seismic-hazards-a-handbook-third-edition-fema-p-154.pdf. Accessed 10 Jul 2023.
[28]	Fischer, E., A.E. Biondo, A. Greco, F. Martinico, A. Pluchino, and A. Rapisarda. 2022. Objective and perceived risk in seismic vulnerability assessment at an urban scale. Sustainability 14(15): Article 9380.
[29]	Gao, S., H. Sun, M. Ma, Y. Lu, Y. Yao, and W. Liu. 2020. Vulnerability assessment of marine economic system based on comprehensive index and catastrophe progression model. Ecosystem Health and Sustainability 6(1): Article 1834459.
[30]	Haque, C.E., and D. Etkin. 2006. People and community as constituent parts of hazards: The significance of societal dimensions in hazards analysis. Natural Hazards 41(2): 271-282.
[31]	Jaafari, A., A. Najafi, H.R. Pourghasemi, J. Rezaeian, and A. Sattarian. 2014. GIS-based frequency ratio and index of entropy models for landslide susceptibility assessment in the Caspian forest, northern Iran. International Journal of Environmental Science and Technology 11(4): 909-926.
[32]	Jaimes, D.L., C.R. Escudero, K.L. Flores, and A. Zamora-Camacho. 2022. Multicriteria seismic hazard and social vulnerability assessment in the Puerto Vallarta metropolitan area, Mexico: Toward a comprehensive seismic risk analysis. Natural Hazards 116(2): 2671-2692.
[33]	Jenifer, M.A., and M.K. Jha. 2017. Comparison of analytic hierarchy process, catastrophe and entropy techniques for evaluating groundwater prospect of hard-rock aquifer systems. Journal of Hydrology 548: 605-624.
[34]	Jin, X., and W. Zhang. 2020. The optimization of objective weighting method based on relative importance. In Proceedings of the 2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), 25-27 December 2020, Harbin, China, 1234-1237. https://doi.org/10.1109/ICMCCE51767.2020.00271.
[35]	Jones, B., and J. Andrey. 2007. Vulnerability index construction: Methodological choices and their influence on identifying vulnerable neighbourhoods. International Journal of Emergency Management 4(2): 269-295.
[36]	Lindlay, S., J. O’Neill, N. Lawson, R. Christian, and M. O’Neil. 2011. Climate change, justice and vulnerability. York: Joseph Rowntree Foundation.
[37]	Longley, P.A., M.F. Goodchild, D.J. Maguire, and D.W. Rhind. 2015. Geographic information science and systems. New York: Wiley.
[38]	McEntire, D. 2012. Understanding and reducing vulnerability: From the approach of liabilities and capabilities. Disaster Prevention and Management: An International Journal 21(2): 206-225.
[39]	Mostafa, M.M. 2022. Five decades of catastrophe theory research: Geographical atlas, knowledge structure and historical roots. Chaos, Solitons & Fractals 159: Article 112078.
[40]	Özalaybey, S., E. Zor, M.C. Tapırdamaz, A.R. Tarancıoğlu, B. Erkan, A. Karaaslan, E.M. Alpaslan, E.S. Ergintav, and E. Tan. 2008. Soil classification and seismic hazard assessment project for Kocaeli Province (Kocaeli İli için Zemin Sınıflaması ve Sismik Tehlike Değerlendirme Projesi). TÜBİTAK.
[41]	Pavić, G., M. Hadzima-Nyarko, and B. Bulajić. 2020. A contribution to a UHS-based seismic risk assessment in Croatia - A case study for the city of Osijek. Sustainability 12(5): Article 1796.
[42]	Peduzzi, P., H. Dao, C. Herold, and F. Mouton. 2009. Assessing global exposure and vulnerability towards natural hazards: The disaster risk index. Natural Hazards and Earth System Sciences 9(4): 1149-1159.
[43]	Pelling, M. 2003. The vulnerability of cities: Natural disasters and social resilience. London: Earthscan.
[44]	Rashed, T., and J. Weeks. 2003. Exploring the spatial association between measures from satellite imagery and patterns of urban vulnerability to earthquake hazards. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIV 7(W9): 144-152.
[45]	Rodcha, R., N.K. Tripathi, and R.P. Shrestha. 2019. Comparison of cash crop suitability assessment using parametric, AHP, and FAHP methods. Land 8(5): Article 79.
[46]	RYTEIE (Riskli Yapıların Tespit Edilmesine İlişkin Esaslar / Principles for identification of risky buildings). 2019. https://webdosya.csb.gov.tr/db/altyapi/icerikler/r-skl--yapilarin-tesp-t-ed-lmes-ne-il-sk-n-esaslar-20190218134628.pdf. Accessed 6 Oct 2023.
[47]	Sauti, N.S., M.E. Daud, M. Kaamin, and S. Sahat. 2021. GIS spatial modelling for seismic risk assessment based on exposure, resilience, and capacity indicators to seismic hazard: A case study of Pahang, Malaysia. Geomatics, Natural Hazards and Risk 12(1): 1948-1972.
[48]	Şengör, A.M.C., O. Tüysüz, C. İmren, M. Sakınç, H. Eyidoğan, N. Görür, X. Le Pichon, and C. Rangin. 2005. The North Anatolian Fault: A new look. Annual Reviews 33: 37-112.
[49]	Shakya, M., H. Varum, R. Vicente, and A. Costa. 2018. Seismic vulnerability assessment methodology for slender masonry structures. International Journal of Architectural Heritage 12(7-8): 1297-1326.
[50]	Shen, D., T. Qian, Y. Xia, Y. Zhang, and J. Wang. 2020. Micro-scale flood hazard assessment based on catastrophe theory and an integrated 2-D hydraulic model: A case study of Gongshuangcha detention basin in Dongting Lake area, China. ISPRS International Journal of Geo-Information 9(4): Article 206.
[51]	Silva, V., S. Brzev, C. Scawthorn, C. Yepes, J. Dabbeek, and H. Crowley. 2022. A building classification system for multi-hazard risk assessment. International Journal of Disaster Risk Science 13(2): 161-177.
[52]	Song, F., X. Yang, and F. Wu. 2020. Catastrophe progression method based on M-K test and correlation analysis for assessing water resources carrying capacity in Hubei Province. Journal of Water and Climate Change 11(2): 556-567.
[53]	Su, S., D. Li, X. Yu, Z. Zhang, Q. Zhang, R. Xiao, J. Zhi, and J. Wu. 2011. Assessing land ecological security in Shanghai (China) based on catastrophe theory. Stochastic Environmental Research and Risk Assessment 25: 737-746.
[54]	Thom, R. 1975. Structural stability and morphogenesis. Reading, MA: WA Benjamin.
[55]	TUIK (Türkiye İstatistik Kurumu / Turkish Statistical Institute). 2021. Labor force statistics, 2021. https://data.tuik.gov.tr/Bulten/Index?p=Isgucu-Istatistikleri-2021-45645. Accessed 10 Jul 2023.
[56]	Wamsler, C., E. Brink, and C. Rivera. 2013. Planning for climate change in urban areas: From theory to practice. Journal of Cleaner Production 50: 68-81.
[57]	Wei, B., G. Nie, G. Su, L. Sun, X. Bai, and W. Qi. 2017. Risk assessment of people trapped in earthquake based on km grid: A case study of the 2014 Ludian Earthquake, China. Geomatics, Natural Hazards and Risk 8(2): 1289-1305.
[58]	Wisner, B., P.M. Blaike, T. Cannon, and I. Davis. 2004. At risk: Natural hazards, people’s vulnerability and disasters. London: Routledge.
[59]	Wood, N.J., C.G. Burton, and S.L. Cutter. 2010. Community variations in social vulnerability to Cascadia-related tsunamis in the U.S. Pacific Northwest. Natural Hazards 52(2): Article 369389.
[60]	Woodcock, A. 2006. Stereographic reconstuctions of the catastrophe manifolds of the cuspoids: (4) the wigwam. In A geometrical study of the elementary catastrophes, ed. A.E.R. Woodcock, and T. Poston, 193-211. Berlin: Springer.
[61]	Wu, J., X. Chen, and J. Lu. 2022. Assessment of long and short-term flood risk using the multi-criteria analysis model with the AHP-entropy method in Poyang Lake basin. International Journal of Disaster Risk Reduction 75: Article 102968.
[62]	Xue, J., J. Yan, and C. Chen. 2022. Combining catastrophe technique and regression analysis to deduce leading landscape patterns for regional flood vulnerability: A case study of Nanjing, China. Frontiers in Ecology and Evolution 10: Article 1002231.
[63]	Yariyan, P., H. Zabihi, I.D. Wolf, M. Karami, and S. Amiriyan. 2020. Earthquake risk assessment using an integrated fuzzy analytic hierarchy process with artificial neural networks based on GIS: A case study of Sanandaj in Iran. International Journal of Disaster Risk Reduction 50: Article 101705.
[64]	Zhai, Y., S. Chen., and Q. Ouyang. 2019. GIS-based seismic hazard prediction system for urban earthquake disaster prevention planning. Sustainability 11(9): Article 2620.
[65]	Zhang, P., X. Li, and C. Liu. 2023. Impact of spatial scale and building exposure distribution on earthquake insurance rates: A case study in Tangshan, China. International Journal of Disaster Risk Science 14(1): 64-78.
[66]	Zhang, H., Y. Sun, W. Zhang, Z. Song, Z. Ding, and X. Zhang. 2021. Comprehensive evaluation of the eco-environmental vulnerability in the Yellow River Delta wetland. Ecological Indicators 125: Article 107514.
[67]	Zhang, W., X. Xu, and X. Chen. 2017. Social vulnerability assessment of earthquake disaster based on the catastrophe progression method: A Sichuan Province case study. International Journal of Disaster Risk Reduction 24: 361-372.
[68]	Zheng, J., and G. Huang. 2023. Towards flood risk reduction: Commonalities and differences between urban flood resilience and risk based on a case study in the Pearl River Delta. International Journal of Disaster Risk Reduction 86: Article 103568.
[69]	Zhu, Y., D. Tian, and F. Yan. 2020. Effectiveness of entropy weight method in decision-making. Mathematical Problems in Engineering 2020: Article 3564835.
[70]	Ziarh, G.F., M.D. Asaduzzaman, A. Dewan, M.S. Nashwan, and S. Shahid. 2021. Integration of catastrophe and entropy theories for flood risk mapping in peninsular Malaysia. Journal of Flood Risk Management 14(1): Article e12686.