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Big Models: From Beijing to the Whole China

  • Ying Long
  • Zhenjiang Shen
Part of the GeoJournal Library book series (GEJL, volume 116)

Abstract

This chapter proposes the concept of big model as a novel research paradigm for regional analysis and urban studies. Big models are fine-scale regional/urban analysis/simulation models for a large geographical area. With the widespread use of big/open data, the increased computation capacity, as well as the advanced regional and urban analyzing/modeling methodologies, big models make it possible to overcome the trade-off between geographical scale and simulation resolution. In this chapter, the concept, characteristics, and potential applications of big models have been elaborated. We presented several case studies to illustrate the progress of our research and the application of big models. They include mapping urban areas for all Chinese cities, performing parcel-level urban simulation, and several ongoing research projects. Most of these applications can be adopted across the whole country, and all of them are focusing on a fine-scale level, such as a parcel, a block, or a township (sub-district). It is expected that big models will mark a promising new era for the urban analysis and regional studies in the era of big/open data.

Keywords

Big model Applied urban modeling Fine-scale Large area China 

Notes

Acknowledgement

We thank Ms Yichun Tu for her editing the language of this chapter.

References

  1. Batty, M. (2009). Urban modeling. International encyclopedia of human geography. Oxford: Elsevier.Google Scholar
  2. Batty, M. (2012). Building a science of cities. Cities, 29, S9–S16.CrossRefGoogle Scholar
  3. Batty, M., & Ferguson, P. (2011). Defining city size. Environment and Planning B: Planning & Design, 38(5), 753–56.CrossRefGoogle Scholar
  4. Berry, B. J. L., Goheen, P. G., & Goldstein, H. (1969). Metropolitan area definition: A re-evaluation of concept and statistical practice 28. Washington, DC: US Bureau of the Census.Google Scholar
  5. Han, H., Lai, S., Dang, A., Tan, Z., & Wu, C. (2009). Effectiveness of urban construction boundaries in Beijing: An assessment. Journal of Zhejiang University SCIENCE A, 10, 1285–1295.CrossRefGoogle Scholar
  6. He, C., Shi, P., Li, J., Chen, J., Pan, Y., Li, J., Li, Z., & Ichinose, T. (2006). Restoring urbanization process in China in the 1990s by using non-radiance calibrated DMSP/OLS nighttime light imagery and statistical data. Chinese Science Bulletin, 51(13), 1614–1620.CrossRefGoogle Scholar
  7. Hu, Y., Wu, Z., Xiong, W., & Pan, C. (2008). Study of identifying urban built-up area: Taking Wuhan as an example. City Planning Review, 32(4), 88–92.Google Scholar
  8. Hunt, J. D., Kriger, D. S., & Miller, E. J. (2005). Current operational urban land-use–transport modelling frameworks: A review. Transport Reviews, 25(3), 329–376.CrossRefGoogle Scholar
  9. Jiang, B., & Yin, J. (2014). Ht-index for quantifying the fractal or scaling structure of geographic features. Annals of the Association of American Geographers, 104(3), 530–540.Google Scholar
  10. Liu, Z., He, C., Zhang, Q., Huang, Q., & Yang, Y. (2012). Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008. Landscape and Urban Planning, 106(1), 62–72.Google Scholar
  11. Long, Y., & Liu, X. (2014). Automated identification and characterization of parcels (AICP) with OpenStreetMap and points of interest. arXiv preprint. arXiv:1311.6165.Google Scholar
  12. Long, Y., Shen, Z., & Mao, Q. (2011). An urban containment planning support system for Beijing. Computers, Environment and Urban Systems, 35(4), 297–307.CrossRefGoogle Scholar
  13. Long, Y., Gu, Y., & Han, H. (2012). Spatiotemporal heterogeneity of urban planning implementation effectiveness: Evidence from five master plans of Beijing. Landscape and Urban Planning, 108, 103–111.CrossRefGoogle Scholar
  14. Long, Y., Han, H., Lai, S.-K., & Mao, Q. (2013). Urban growth boundaries of the Beijing metropolitan area: Comparison of simulation and artwork. Cities, 31, 337–348.CrossRefGoogle Scholar
  15. Masucci, A. P, Stanilov, K., & Batty, M. (2012). Limited urban growth: London’s street network dynamics since the 18th century. arXiv preprint. arXiv:1206.5298.Google Scholar
  16. Montgomery, M. R. (2008). The urban transformation of the developing world. Science, 319(8), 761–764.CrossRefGoogle Scholar
  17. Morrill, R., Cromartie, J., & Hart, G. (1999). Metropolitan, urban, and rural commuting areas: Toward a better depiction of the United States settlement system. Urban Geography, 20(8), 727–748.CrossRefGoogle Scholar
  18. Nelson, A. C., & Duncan, J. B. (1995). Growth management principles and practices. Chicago/Washington, DC: Planners Press/American Planning Association.Google Scholar
  19. Pendall, R., Martin, J., & Fulton, W. (2002). Holding the line: Urban containment in the United States. Washington, DC: The Brookings Institution Center on Urban and Metropolitan Policy.Google Scholar
  20. Rozenfeld, H. D., Rybski, D., Gabaix, X., & Makse, H. A. (2009). The area and population of cities: New insights from a different perspective on cities (No. w15409). National Bureau of Economic Research.Google Scholar
  21. SGS Economics & Planning. (2011). Melbourne’s economy: A stunning success or captured by complacency?, presentation at State Library of Victoria by Terry Rawnsley.Google Scholar
  22. SGS Economics & Planning. (2012). Melbourne metro: Move to more productive jobs, draft version 2.0, 3 February 2012.Google Scholar
  23. Tian, L., & Shen, T. (2011). Evaluation of plan implementation in the transitional China: A case of Guangzhou city master plan. Cities, 28, 11–27.CrossRefGoogle Scholar
  24. United States Census Bureau. (2014). History: Metropolitan areas. U.S. Census Bureau. http://www.census.gov/history/www/programs/geography/metropolitan_areas.html. Accessed 31 March.
  25. Wegener, M. (2004). Overview of land-use transport models. Handbook of Transport Geography and Spatial Systems, 5, 127–146.Google Scholar
  26. Xu, Y., Shi, S., & Fan, Y. (2009). Methodology of Shanghai city master planning in new position. Urban Planning Forum, 2, 10–15.Google Scholar
  27. Zhang, Y. P., & Long, Y. (2013). Urban growth simulation using V-BUDEM: A vector-based Beijing urban development model. Beijing: The conference of Spatial Planning and Sustainable Development.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ying Long
    • 1
  • Zhenjiang Shen
    • 2
    • 3
    • 4
  1. 1.Beijing Key Lab of Capital Spatial Planning and StudiesBeijing Institute of City PlanningBeijingChina
  2. 2.2C718Kanazawa University Natural Science and Technology HallKanazawaJapan
  3. 3.Tsinghua UniversityBeijingChina
  4. 4.Fuzhou UniversityFuzhouChina

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