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Adaptive modeling of the human-environment relationship applied to estimation of the population carrying capacity in an earthquake zone

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Abstract

Natural catastrophes such as earthquakes can, in addition to causing loss of life, disrupt the urbanization process through the need for forced population redistribution and the modification of resource and environmental carrying capacity. The population carrying capacity (PCC) of an altered environment following an earthquake is a crucial determinant in the relocation of displaced persons. We use data adaptive methods to model the correlation between the physical environment and human population density in estimating PCC in areas affected by the 2008 Wenchuan earthquake. Comparing actual population distributions with ideal population distributions allows for the identification of villages where population exceeds PCC, or conversely, areas where the environment can support a higher population. Such a comparison can provide the basis for a relocation plan, a critical element of post-catastrophe policy-making.

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References

  • Christakos, G. (2010). Integrative problem-solving in a time of decadence. New York: Springer.

    Google Scholar 

  • Fan, J. (2009). State planning for Wenchuan earthquake rebuilding—assessment of environmental and resource carrying capacity (in Chinese). Beijing: Science Press.

    Google Scholar 

  • Fischer, M. M., & Nijkamp, P. (1999). Spatial dynamics of European integration: Regional and policy issues at the turn of the century. Berlin: Springer.

    Google Scholar 

  • Gao, X. L., & Asami, Y. (2007). Influence of lot size and shape on redevelopment projects. Land Use Policy, 24, 212–222.

    Article  Google Scholar 

  • Haimes, Y. Y. (2008). Risk modeling, assessment, and management (3rd ed.). New York: Wiley.

    Book  Google Scholar 

  • Haining, R. (2003). Spatial data analysis: Theory and practice. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Leung, Y., & Leung, K. S. (1993). An intelligent expert system shell for knowledge-based geographical information systems: 1. The tools. International Journal of Geographical Information Science, 7, 189–199.

    Article  Google Scholar 

  • Li, X., & Liu, X. P. (2007). Case-based cellular automaton for simulating urban development in a large complex region (in Chinese). Acta Geographica Sinica, 62, 1097–1109.

    Google Scholar 

  • Li, L. F., Wang, J. F., Cao, Z. D., Feng, X. L., Zhang, L. L., & Zhong, E. S. (2008). An information-fusion method to regionalize spatial heterogeneity for improving the accuracy of spatial sampling estimation (in Chinese). Stochastic Environmental Research and Risk Assessment, 22, 689–704.

    Article  Google Scholar 

  • Liao, Y. L., Wang, J. F., Guo, Y. Q., & Zheng, X. Y. (2010b). Risk assessment of human neural tube defects using a Bayesian belief network. Stochastic Environmental Research and Risk Assessment, 24, 93–100.

    Article  Google Scholar 

  • Liao, Y. L., Wang, J. F., & Meng, B. (2010a). GP, GA and GIS for mapping population distribution. International Journal of Geographical Information Sciences, 24, 47–67.

    Article  Google Scholar 

  • Marston, R. A. (2008). Land, life, and environmental change in mountains. Annals of the Association of American Geographers, 98, 507–520.

    Article  Google Scholar 

  • Parsons, T., Chen, J., & Eric, K. (2008). Stress changes from the 2008 Wenchuan earthquake and increased hazard in the Sichuan basin. Nature. doi:10.1038/nature07177.

  • Puleston, C. O., & Tuljapurkar, S. (2008). Population and prehistory II: Space-limited human populations in constant environments. Theoretical Population Biology, 74, 147–160.

    Article  Google Scholar 

  • Wang, J. F. (1993). Methodology for assessing natural disaster risk in China (in Chinese). Beijing: China Science & Technology Press.

    Google Scholar 

  • Wang, J. F., Cheng, G. D., Gao, Y. G., Long, A. H., Li, X., & Xu, Z. M. (2008a). Optimal water allocation in arid and semi-arid areas. Water Resources Management, 22, 239–258.

    Article  Google Scholar 

  • Wang, J. F., Haining, R., & Cao, Z. D. (2010). Sample surveying to estimate the mean of a heterogeneous surface: Reducing the error variance through zoning. International Journal of Geographical Information Science, 24(4), 523–543.

    Article  Google Scholar 

  • Wang, J. F., & Li, L. F. (2008). Improving tsunami warning systems with remote sensing and geographical information system input. Risk Analysis, 28(6), 1653–1668.

    Article  Google Scholar 

  • Wang, J. F., Wise, S., & Haining, R. (1997). An integrated regionalization of earthquake, flood and drought hazards in China. Transactions in GIS, 2, 25–44.

    Article  Google Scholar 

  • Wang, K. Y., Chen, T., Wang, L. Y., & Yuan, X. (2008b). Harmonious development model of urban and rural integration in quasi-urbanization areas (in Chinese). Scientia Geographica Sinica, 28, 173–178.

    Google Scholar 

  • Zhang, W. Z., Liu, W., & Meng, B. (2005). On location advantage value of residential environment in the urban and suburban areas of Beijing (in Chinese). Acta Geographica Sinica, 60, 115–121.

    Google Scholar 

Download references

Acknowledgments

This study was supported by the NSFC (41023010), CAS (XDA05090102), the MOST (2009ZX10004-201, 2008BA156B02, 2006BAK01A13).

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Correspondence to Jin-Feng Wang or Xiao-Ying Zheng.

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Wang, JF., Liao, YL., Wang, JJ. et al. Adaptive modeling of the human-environment relationship applied to estimation of the population carrying capacity in an earthquake zone. Popul Environ 33, 233–242 (2012). https://doi.org/10.1007/s11111-011-0143-3

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  • DOI: https://doi.org/10.1007/s11111-011-0143-3

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