Journal of East China Normal University(Natural Sc ›› 2008, Vol. 2008 ›› Issue (6): 40-50,7.

• Article • Previous Articles     Next Articles

Patterns of urban green spaces based on linear spectral mixture model: an empirical study in Urumqi(Chinese)

WANG Zhan-yong1,XU Jian-hua1,LÜ Guang-hui2,ZHANG Zhi-hua1,HU Qing1   

  1. 1. Key Laboratory of Geographic Information Science of Ministry of Education, East China Normal University, Shanghai 200062, China; 2. Key Laboratory of Oasis Ecology of Ministry of Education, Xinjiang University, Urumqi 830046, China
  • Received:2008-06-12 Revised:2008-08-05 Online:2008-11-25 Published:2008-11-25
  • Contact: XU Jian-hua

Abstract: The pattern of urban green spaces and its variation characteristic in Urumqi were analyzed under a linear spectral mixture model as well as vegetation landscape index, to provide a more accurate method in quantitative evaluation for ecological environment of oasis cities in arid areas. The results indicate that, (1) In terms of the region as a whole, the relevance of vegetation fraction and vegetation index is closer, but vegetation fraction is better able to reflect urban vegetation landscape with weak vegetation information at pixel scale. (2) In the past 13 years, the vegetation abundance has declined obviously overall in the study area and the serious problems of urban ecological development in Urumqi are remarkable, just like green coverage falling sharply in outskirts, greenbelt fragmentation intensifying in built-up area, spatial distribution of greenbelt being incompatible and others. (3) Viewed from vegetation types in built-up area, the vegetation with medium and high abundance has shrunk largest in area and the area of low abundance vegetation hasn’t changed much, but the fragmentation of low abundance vegetation is most serious. Moreover, the structure of urban greenbelt based on the principle of low abundance vegetation trends single obviously, which will result in instability in urban green ecosystems.

Key words: endmember, green space, spatiotemporal variation, Urumqi, linear spectral mixture model, endmember, green space, spatiotemporal variation, Urumqi

CLC Number: