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A Model for the Spatio-temporal Distribution of Population using Country-Wide Statistical Data and Its Application to the Estimation of Human Exposure to Disasters

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Improving Disaster Resilience and Mitigation - IT Means and Tools

Abstract

Extent of fatality due to natural disaster depends largely on spatial distribution of population at the moment disaster occurs. In this study, a computational model for estimating day-long spatio-temporal distribution of commuters (workers and students) was developed using a number of country-wide statistical data of Japan such as “population census”, “survey on time use and leisure activities”, and “economic census”. The model estimates behavior of individual commuters by considering their attributes including gender, occupation, place of work (or school), and place of residence. As a case study, the proposed model was applied to the Keihanshin (Kyoto-Osaka-Kobe) metropolitan area, one of the largest metropolitan areas in Japan. Estimated maximum number of commuters unable to return home in an expecting earthquake scenario was between 1.1 and 1.9 million depending on the assumptions on traffic disruption following disaster and the maximum walkable distance of each commuter.

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References

  1. Fire and Disaster Management Agency (FDMA) (2006) Final report of 1995 Hyogo-ken Nanbu Earthquake, 2 pages

    Google Scholar 

  2. Fire and Disaster Management Agency (FDMA) (2013) 148th report of 2011 off the pacific coast of Tohoku Earthquake, 40 pages

    Google Scholar 

  3. Nojima N, Kuse M, Sugito M, Suzuki Y (2004) Population exposure to seismic intensity for assessment of seismic disaster potential. J Jpn Soc Nat Disaster Sci 23(3):363–380 (in Japanese)

    Google Scholar 

  4. Dilley M, Chen RS, Deichmann U, Lerner-Lam AL, Arnold M, Agwe J, Buys P, Kjekstad O, Lyon B, Yetman G (2005) Natural disaster hotspots: a global risk analysis. The World Bank, Washington, DC

    Book  Google Scholar 

  5. Peduzzi P, Dao H, Herold C, Mouton F (2009) Assessing global exposure and vulnerability towards natural hazards: the disaster risk index. Nat Hazards Earth Syst Sci 9:1149–1159

    Article  Google Scholar 

  6. Aubrecht C, Ozceylan D, Steinnocher K, Freire S (2012) Multi-level geospatial modeling of human exposure patterns and vulnerability indicators. Nat Hazards

    Google Scholar 

  7. Balk D, Yetman G, de Sherbinin A (2010) Construction of gridded population and poverty data sets from different data sources. In: Proceeding of the European forum for geostatistics conference, Talin, 5–7 October 2010, pp 12–20

    Google Scholar 

  8. Dobson JE, Bright EA, Coleman PR, Durfee RC, Worley BA (2000) LandScan: a global population database for estimating populations at risk. Photogramm Eng Remote Sens 66(7):849–857

    Google Scholar 

  9. Bhaduri B, Bright E, Coleman P, Urban ML (2007) LandScan USA: a high-resolution geospatial and temporal modeling approach for population distribution and dynamics. GeoJournal 69:103–117. Springer, http://link.springer.com/journal/10708

  10. Freire S (2010) Modeling of spatiotemporal distribution of urban population at high resolution – value for risk assessment and emergency management. In: Konecny M et al (eds) Geographic information and cartography for risk and crisis management, Lecture notes in geoinformation and cartography, Berlin, pp 53–67

    Google Scholar 

  11. Osaragi T (2012) Modeling a spatiotemporal distribution of stranded people returning home on foot in the aftermath of a large-scale Earthquake. Nat Hazards

    Google Scholar 

  12. Ministry of Internal Affairs and Communications (MIC) (2007) Report of the 2005 population census, http://www.stat.go.jp/english/data/kokusei/index.htm. Last date accessed: Dec 2013

  13. Ministry of Internal Affairs and Communications (MIC) (2007) Report of the 2006 economic census, Tokyo. http://www.stat.go.jp/english/data/jigyou/index.htm. Last date accessed: Dec 2013

  14. Ministry of Internal Affairs and Communications (MIC) (2007) Report of the 2006 survey on time use and leisure activities, Tokyo. http://www.stat.go.jp/english/data/shakai/index.htm. Last date accessed: Dec 2013

  15. Ministry of Land, Infrastructure, Transport and Tourism (MLIT) (2000) Report of the 4th Keihanshin Metropolitan Area Person Trip Survey, 35 pages

    Google Scholar 

  16. Ministry of Land, Infrastructure, Transport and Tourism (MLIT) (2010) Report of the 2010 Census on Traffic in Major Metropolitan Areas, 157 pages

    Google Scholar 

  17. Cabinet Office (2012) Second report of the WG on the countermeasures against the gigantic Nankai trough earthquake, http://www.bousai.go.jp/jishin/nan.kai/nankaitrough_info.html. Last date accessed: Dec 2013

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Acknowledgement

This ongoing work is supported by Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number 21360291.

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Correspondence to Keisuke Himoto .

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Himoto, K., Kimata, J. (2014). A Model for the Spatio-temporal Distribution of Population using Country-Wide Statistical Data and Its Application to the Estimation of Human Exposure to Disasters. In: Teodorescu, HN., Kirschenbaum, A., Cojocaru, S., Bruderlein, C. (eds) Improving Disaster Resilience and Mitigation - IT Means and Tools. NATO Science for Peace and Security Series C: Environmental Security. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9136-6_5

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  • DOI: https://doi.org/10.1007/978-94-017-9136-6_5

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-017-9135-9

  • Online ISBN: 978-94-017-9136-6

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