Skip to main content

Advertisement

Log in

Developing GIS-based earthquake loss model: a case study of Baqiao District, China

  • Original Article
  • Published:
Bulletin of Earthquake Engineering Aims and scope Submit manuscript

Abstract

Large earthquakes frequently occurred and caused substantial damage and losses in Chinese densely populated urban areas. It is worth clarifying that the existing earthquake loss assessment tools in China do not consider its special characteristics (e.g., tectonics, geology and building inventory). In this paper, an integrated framework for earthquake loss assessment in China is proposed and a geographic information system (GIS)-based system, referred to as China Earthquake Disaster Loss Assessment System, is developed. The individual building is considered as the basic geographical unit and described in three levels (i.e., basic attributes, structural performance parameters, and functional parameters. A three-step data collection method is proposed, and the mobile GIS-based field collection tool is developed. A broad, reasonable, and upgradeable building typology is then presented for the seismic fragility assessment of building blocks. A new economic loss model and casualty model are also presented by considering the characteristics of economics and population. The proposed methodology is implemented in Baqiao District, and the estimation of economic losses and casualties under a scenario earthquake is discussed, which can provide information for urban disaster risk assessment and mitigation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  • Ahmad N, Crowley H, Pinho R et al (2010) Displacement-based earthquake loss assessment of masonry buildings in Mansehra city. Pak J Earthq Eng 14(S1):1–37

    Google Scholar 

  • Ahmad N, Ali Q, Ashraf M et al (2012) Seismic vulnerability of the Himalayan half-dressed rubble stone masonry structures, experimental and analytical studies. Nat Hazards Earth Syst Sci 12(11):3441–3454

    Article  Google Scholar 

  • Ahmad N, Ali Q, Crowley H, Rui P (2014) Earthquake loss estimation of residential buildings in Pakistan. Nat Hazards 73(3):1889–1955

    Article  Google Scholar 

  • Ahmad N, Shahzad A, Ali Q et al (2018) Seismic fragility functions for code compliant and non-compliant RC SMRF structures in Pakistan. Bull Earthq Eng 16(10):4675–4703

    Article  Google Scholar 

  • Al Hanoun MH, Abrahamczyk L, Schwarz J (2019) Macromodeling of in-and out-of-plane behavior of unreinforced masonry infill walls. Bull Earthq Eng 17(1):519–535

    Article  Google Scholar 

  • Annunziato A, Gadenz S, Galliano DA et al (2010) Field tracking tool: a collaborative framework from the field to the decision makers. Geographic information and cartography for risk and crisis management. Springer, Berlin, pp 287–303

    Google Scholar 

  • ATC-13 (1985) Earthquake damage evaluation data for California. Applied Technology Council, Redwood City

    Google Scholar 

  • Baker JW (2008) An introduction to probabilistic seismic hazard analysis (PSHA). White Paper, Version 1.3. http://www.stanford.edu/~bakerjw/publications.html. Accessed 2 May 2013

  • Bal IE, Crowley H, Pinho R et al (2008) Detailed assessment of structural characteristics of Turkish RC building stock for loss assessment models. Soil Dyn Earthq Eng 28(10):914–932

    Article  Google Scholar 

  • Brzev S, Scawthorn C, Charleson AW et al (2013) GEM building taxonomy. GEM technical report, Version 1.0.0. https://pubs.er.usgs.gov/publication/70045104. Accessed 16 Mar 2017

  • Chen DM, Duan R (2013) Amplification effects of site conditions on ground peak acceleration. J Earthq Eng Eng Vib 33(1):24–30 (in Chinese)

    Google Scholar 

  • China Earthquake Networks Center, National Earthquake Data Center. http://data.earthquake.cn

  • Choun YS, Elnashai AS (2010) A simplified framework for probabilistic earthquake loss estimation. Probab Eng Mech 25(4):355–364

    Article  Google Scholar 

  • Coburn A, Spence R (2003) Earthquake protection. Wiley, Hoboken

    Google Scholar 

  • Cornell CA (1968) Engineering seismic risk analysis. Bull Seismol Soc Am 58(5):1583–1606

    Article  Google Scholar 

  • D’Ayala D, Meslem A, Vamvastikos D, Porter K, Rossetto T, Crowley H, Silva V (2014) Guidelines for analytical vulnerability assessment of low/mid-rise Buildings—Methodology. Vulnerability Global Component project. Available from: https://www.nexus.globalquakemodel.org/gem-vulnerability/posts/

  • Duzgun HSB, Yucemen MS, Kalaycioglu HS et al (2011) An integrated earthquake vulnerability assessment framework for urban areas. Nat Hazards 59(2):917–947

    Article  Google Scholar 

  • Ellingwood BR, Wen YK (2005) Risk-benefit-based design decisions for low-probability/high consequence earthquake events in mid-America. Prog Struct Mater Eng 7(2):56–70

    Article  Google Scholar 

  • ESRI (2010) ArcGIS. Version 10.1. Redlands, United States

  • Fan W, Du WH, Wang XJ et al (2011) Seismic motion attenuation relations in Shaanxi areas. Earthq Eng Eng Vib 31(2):47–54

    Google Scholar 

  • Federal Emergency Management Agency (2002) Rapid visual screening of buildings for potential seismic hazards: a handbook, 2nd edn. FEMA, Washington

    Google Scholar 

  • Federal Emergency Management Agency (FEMA) (2012a) Multi-hazard loss estimation methodology, earthquake model, HAZUS–MH 2.1 technical manual. Washington, DC

  • Federal Emergency Management Agency (FEMA) (2012b) Multi-hazard loss estimation methodology HAZUS–MH 2.1 advanced engineering building module (AEBM) technical and user’s manual. Washington, DC

  • Federal Emergency Management Agency-National Institute of Building Sciences (FEMA-NIBS) (1997) Earthquake loss estimation methodology–HAZUS99. Washington, DC

  • Gao X, Zhong Y, Chen D (1989) A method on prediction of seismic damage for reinforced concrete frames. Build Sci 01:16–23

    Google Scholar 

  • Global Earthquake Model (GEM) (2013). http://www.globalquakemodel.org

  • Gong M, Lin S, Sun J et al (2015) Seismic intensity map and typical structural damage of 2010 Ms 7.1 Yushu earthquake in China. Nat Hazards 77(2):847–866

    Article  Google Scholar 

  • Haldar P, Singh Y, Lang DH, Paul DK (2013) Comparison of seismic risk assessment based on macroseismic intensity and spectrum approaches using ‘SeisVARA.’ Soil Dyn Earthq Eng 48:267–281

    Article  Google Scholar 

  • Hu YX (1990) Comprehensive probability method for the seismic risk analysis. Earthquake Press, Beijing (in Chinese)

    Google Scholar 

  • IDCT (2011) http://www.globalquakemodel.org/resources/use-and-share/tools-apps/

  • Jaiswal K, Wald D, Porter K (2010) A global building inventory for earthquake loss estimation and risk management. Earthq Spectra 26(3):731–748

    Article  Google Scholar 

  • Jeon JS (2013) Aftershock vulnerability assessment of damaged reinforced concrete buildings in California. Georgia Institute of Technology, Atlanta

    Google Scholar 

  • Jiang HJ, Liu XJ, Hu L (2015) Seismic fragility assessment of RC frame-shear wall structures designed according to the current Chinese seismic design code. J Asian Archit Build Eng 14(2):459–466

    Article  Google Scholar 

  • Joint Research Centre (JRC) (2013) Development of inventory datasets through remote sensing and direct observation data for earthquake loss estimation. SYNER-G technical report

  • Ketner KB (2008) Creating a global building inventory for earthquake loss assessment and risk management. U.S. geological Survey.

  • Konakli K, Der Kiureghian A (2012) Simulation of spatially varying ground motions including incoherence, wave-passage and differential site-response effects. Earthq Eng Struct Dyn 41(3):495–513

    Article  Google Scholar 

  • Lin SL, Li J, Elnashai AS, Spencer BF Jr (2012) NEES integrated seismic risk assessment framework (NISRAF). Soil Dyn Earthq Eng 42:219–228

    Article  Google Scholar 

  • Liu JW, Wang ZM, Xie FR, Lv YJ (2013) Seismic hazard assessment for greater North China from historical intensity observations. Eng Geol 164:117–130

    Article  Google Scholar 

  • Long L, Zheng SS, Zhang YX et al (2020) CEDLES: a framework for plugin-based applications for earthquake risk prediction and loss assessment. Nat Hazards 103:531–556

    Article  Google Scholar 

  • Lv Y, Dong Y, Feng XJ et al (2014) Characteristics of geological relics due to 1556 Huaxian great earthquakes in Guanzhong area of Shaanxi province, China. J Eng Geol 22(2):300–308 (in Chinese)

    Google Scholar 

  • MAEviz (2018) http://rcp.ncsa.uiuc.edu/maeviz/about.html

  • Mansour AK, Romdhane NB, Boukadi N (2013) An inventory of buildings in the city of Tunis and an assessment of their vulnerability. Bull Earthq Eng 11(5):1563–1583

    Article  Google Scholar 

  • Mansouri B, Amini-Hosseini K (2014) Development of residential building stock and population databases and modeling the residential occupancy rate for Iran. Nat Hazards Rev 15(1):88–94

    Article  Google Scholar 

  • Mansouri B, Ghafory-Ashtiany M, Amini-Hosseini K et al (2010) Building seismic loss model for Tehran. Earthq Spectra 26(1):153–168

    Article  Google Scholar 

  • McGuire RK (2008) Probabilistic seismic hazard analysis: early history. Earthq Eng Struct Dyn 37:329–338

    Article  Google Scholar 

  • Molina S, Lang DH, Lindholm CD (2010) SELENA—an open-source tool for seismic risk and loss assessment using a logic tree computation procedure. Comput Geosci 36(3):257–269

    Article  Google Scholar 

  • National Bureau of Statistics of the People’s Republic of China (NBSPRC) (2015) The People's Republic of China national economic and social development statistical bulletin in 2014. http://www.stats.gov.cn/tjsj/zxfb/201502/t20150226_685799.html (in Chinese)

  • National Standard of People’s Republic of China (NSPRC) (1979) Chinese aseismic code of industrial and civil buildings (TJ11-78). Ministry of Construction of People’s Republic of China, Beijing (in Chinese)

    Google Scholar 

  • National Standard of People’s Republic of China (NSPRC) (1989) Chinese code for seismic design of buildings (GBJ11-89). Ministry of Construction of People’s Republic of China, Beijing (in Chinese)

    Google Scholar 

  • National Standard of People’s Republic of China (NSPRC) (2001) Chinese code for seismic design of buildings (GB50011-2001). Ministry of Construction of People’s Republic of China, Beijing (in Chinese)

    Google Scholar 

  • National Standard of People’s Republic of China (NSPRC) (2009) Classification of earthquake damage to buildings and special structures (GB/T24335-2009). Ministry of Construction of People’s Republic of China, Beijing (in Chinese)

    Google Scholar 

  • National Standard of People’s Republic of China (NSPRC) (2010) Chinese code for seismic design of buildings (GB50011-2010). Ministry of Construction of People’s Republic of China, Beijing (in Chinese)

    Google Scholar 

  • National Standard of People’s Republic of China (NSPRC) (2015) Seismic ground motion parameter zonation map of China, GB 18306–2015. China Standard Publishing House, Beijing (in Chinese)

    Google Scholar 

  • Norwegian Geotechnical Institute (NGI) (2013) SYNER-G fragility curves for all elements at risk. SYNER-G technical report

  • Pagani M, Monelli D, Weatherill G, Danciu L, Crowley H (2014) Openquake engine: an open hazard (and risk) software for the global earthquake model. Seismol Res Lett 85(3):692–702

    Article  Google Scholar 

  • Pan H, Gao MT, Xie FR (2013) The earthquake activity model and seismicity parameters in the new seismic hazard map of China. Technol Earthq Disaster Prev 8(1):11–23 (in Chinese)

    Google Scholar 

  • Pitilakis K, Argyroudis S (2014) Introduction to the applications of the SYNER-G methodology and tools. In: SYNER-G: systemic seismic vulnerability and risk assessment of complex urban, utility, lifeline systems and critical facilities. Springer, pp 185–198

  • Applied Technology Council (2009) Quantification of building seismic performance factors (FEMA P-695), Washington, DC

  • Sahar L, Muthukumar S, French SP (2010) Using aerial imagery and GIS in automated building footprint extraction and shape recognition for earthquake risk assessment of urban inventories. IEEE Trans Geosci Remote Sen 48(9):3511–3520

    Article  Google Scholar 

  • Seismic Vulnerability Assessment Project Group (SVAPG) (2013) Seismic vulnerability assessment of building types in India, Technical Document on Typology of Buildings in India

  • Silva V, Crowley H, Pagani M, Monelli D, Rui P (2014) Development of the openquake engine, the global earthquake model’s open-source software for seismic risk assessment. Nat Hazards 72(3):1–19

    Article  Google Scholar 

  • Spence KSR (2011) Mapping urban building stocks for vulnerability assessment-preliminary results. Int J Digit Earth 4(1):117–130

    Google Scholar 

  • Sun BT, Chen HF (2009) Urban building loss assessment method considering the decoration damage due to earthquake. J Earthq Eng Eng Vib 29(5):164–169

    Google Scholar 

  • Sun, BT, Chen HF, Zhong YZ (2012) Development of earthquake disaster loss estimation in China. In: Proceedings of the 15th world conference on earthquake engineering, 2012

  • Sun BT, Zhang GX (2012) Statistical analysis of the seismic vulnerability of various types of building structures in Wenchuan M8.0 earthquake. China Civ Eng J 45(5):26–30 (in Chinese)

    Google Scholar 

  • SYNER-G (2013) http://www.vce.at/SYNER-G/

  • Wang JP, Taheri H (2014) Seismic hazard assessment of the Tehran region. Nat Hazards Rev 15:121–127

    Article  Google Scholar 

  • Wang YY (2008) Lessons learnt from building damages in the Wenchuan earthquake: seismic concept design of buildings. J Build Struct 4(4):20–25 (in Chinese)

    Google Scholar 

  • Wieland M, Pittore M, Parolai S et al (2012) Estimating building inventory for rapid seismic vulnerability assessment: towards an integrated approach based on multi-source imaging. Soil Dyn Earthq Eng 36:70–83

    Article  Google Scholar 

  • Wu D, Tesfamariam S, Stiemer SF, Qin D (2012) Seismic fragility assessment of RC frame structure designed according to modern Chinese code for seismic design of buildings. Earthq Eng Eng Vib 11(3):331–342

    Article  Google Scholar 

  • Xi’an Geophysical Exploration Center, Xi’an Earthquake Administration (2011) Seismic ground motion parameters zonation map of Xi’an

  • Xiong C, Huang J, Lu X (2020) Framework for city-scale building seismic resilience simulation and repair scheduling with labor constraints driven by time–history analysis. Comput Aided Civ Infrastruct Eng 35(4):322–341

    Article  Google Scholar 

  • Xu Z, Lu X, Guan H, Han B, Ren A (2014) Seismic damage simulation in urban areas based on a high-fidelity structural model and a physics engine. Nat Hazards 71(3):1679–1693

    Article  Google Scholar 

  • Yin ZQ (1995) Method for earthquake disaster predicting and loss assessment. Earthquake Press, Beijing (in Chinese)

    Google Scholar 

  • Yu YX, Li SY, Xiao L (2013) Development of ground motion attenuation relations for the new seismic hazard map of China. Technol Earthq Disaster Prev 8(1):24–33 (in Chinese)

    Google Scholar 

  • Yu YX, Wang SY (2003) Attenuation relations for horizontal peak ground acceleration and response spectrum in Eastern and Western China. Technol Earthq Disaster Prev 1(3):206–217 (in Chinese)

    Google Scholar 

  • Zhang GX (2010) Two methods for earthquake damage prediction of building groups base on multi-parameters. Master dissertation, Institute of Engineering Mechanics, China Earthquake Administration (in Chinese)

Download references

Acknowledgements

The research described in this paper was financed by the National Natural Science Foundation of China with Grant No. 51678475 and the Research Fund of Shaanxi Province in China with Grant No. 2017ZDXM-SF-093. Part of the basic data was provided by the Earthquake Administration of Xi’an and the Government of Baqiao District. This support is greatly acknowledged.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Yixin Zhang or Li Long.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

See Table

Table 9 Comparisons of loss assessment in sub-districts of Baqiao

9.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Zheng, S., Sun, L. et al. Developing GIS-based earthquake loss model: a case study of Baqiao District, China. Bull Earthquake Eng 19, 2045–2079 (2021). https://doi.org/10.1007/s10518-020-01039-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10518-020-01039-z

Keywords

Navigation