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Chinese Journal of Applied Ecology ›› 2010, Vol. 21 ›› Issue (10): 2621-2626.

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Characteristics and changes of landscape pattern in Wuhan City based on Ripley’s K function.

GAO Kai1, ZHOU Zhi-xiang1, YANG Yu-ping1,2, LI Hua1   

  1. 1College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China;2Three Gorges Vocational and Technical College, Yichang 443003, Hubei, China
  • Online:2010-10-18 Published:2010-10-18

Abstract: By using Ripley’s K function, an important method of point pattern analysis, and taking the TM remote sensing images of 1987, 1996 and 2007 as data source, this paper studied the characteristics and changes of landscape pattern in Wuhan City. The results showed that in 1987-2007, farmland was the landscape matrix in Wuhan, while water body, forestland, grassland, urban and rural built up land, and unutilized land types were the patches or corridors, which spatially clumped significantly in all scales. The landscape aggregation of water bodies was inferior to that of forestland, grassland, and urban and rural built-up land. The farmland clumped spatially in fine scales, but became random or uniform in coarse scales. Meantime, the areas of forestland and urban and rural built-up land increased largely, while water body, grassland, and farmland decreased greatly. In addition, the landscape spatial characteristics of all landscape types changed variously. On the whole, the landscape aggregation of forestland and urban and rural built-up land decreased, and became more uniform. Meanwhile, the water body, grassland, and farmland took on a more uneven and clumped landscape pattern. To analyze the landscape pattern through sample points had the advantages of conciseness, accuracy, and easiness-to-use, in comparison with the methods of  quadrat and sample line (or transect).  Ripley’s K function was proved to be an efficient means for analyzing landscape pattern in different scales, and fit for the supplement and support of landscape metrics.

Key words: landscape heterogeneity, landscape pattern, point pattern analysis, Ripley’s K function, landscape metrics, rhizosphere fungi, Aspergillus terreus, soil-borne disease, cucumber, biological control.