Journal of Forestry Research

, Volume 12, Issue 1, pp 67–70 | Cite as

Type, quantity and layout of urban peripheral green space

  • Wang Xiao-jun
Article

Abstract

Urban peripheral green space (UPGS) plays more and more important role in sustaining urban physical and ecological environments. In this paper, a preliminary classification of UPGS was presented for seven types and quantity index of UPGS was discussed tentatively. The quantity and layout problems in urban peripheral green space, and the several principles were mainly discussed in urban ventilation and sanitation, recreational opportunity and landscape ecological structure.

Key words

Peripheral Green space Quantity Layout 

CLC number

S731 

Document code

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Chapin, F.S. and Kaiser, E.J., 1979. Urban Land use Planning [M]. Champagne-urbane, III: Press of University of Illinois, p 375–377.Google Scholar
  2. Dong Yawen. 1991. Urban landscape and regional connection [C]. In: Landscape ecology: theory, method and applications (Edited by Xiao Duning). Beijing: China Forestry Press, p 75–82.Google Scholar
  3. Li Jingwen. 1981. Forest Ecology [M]. Beijing: China Forestry Press, p 163–164.Google Scholar
  4. Men Dezheng (translator). 1986. Urban Ecology [M]. Beijing: Science Press, p 50–51.Google Scholar
  5. Shi Zuomin and Chen Tao. 1996. Research advance of urbanization and its effect on urban eco-environment [J]. Chinese Journal of Ecology,15(1): 35–41.Google Scholar
  6. Wang Rusong. 1990. Urban ecology [C]. In: Perspectives in modern ecology, edited by Ma Shijun Beijing: Science Press, p 183–193.Google Scholar
  7. Wang Xingrong. 1992. Layout of Air Pollution Sources [M]. Beijing: China Environment Press, p 87–97.Google Scholar

Copyright information

© Northeast Forestry University 2001

Authors and Affiliations

  • Wang Xiao-jun
    • 1
  1. 1.Department of Landscape ArchitectureNanjing Forestry UniversityNanjingP.R. China

Personalised recommendations