Gao Kai, Zhou Zhi-xiang, Yang Yu-ping, Li Hua
College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan 430070, China.
Ying Yong Sheng Tai Xue Bao. 2010 Oct;21(10):2621-6.
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.
利用点格局分析的重要方法——Ripley's K函数，以1987年、1996年和2007年的TM遥感影像为数据源，研究了武汉市景观格局的特征与变化。结果表明，1987—2007年，农田是武汉市的景观基质，水体、林地、草地、城乡建设用地和未利用地等类型为斑块或廊道，在各尺度上均呈现出明显的空间集聚。水体的景观集聚性不如林地、草地和城乡建设用地。农田在小尺度上呈现空间集聚，但在大尺度上变得随机或均匀分布。同时，林地和城乡建设用地面积大幅增加，而水体、草地和农田面积大幅减少。此外，各景观类型的景观空间特征也发生了不同程度的变化。总体而言，林地和城乡建设用地的景观集聚性降低，分布更加均匀。同时，水体、草地和农田呈现出更加不均匀和集聚的景观格局。与样方和样线（或样带）方法相比，通过样点分析景观格局具有简洁、准确、易用等优点。Ripley's K函数被证明是分析不同尺度景观格局的有效手段，适用于景观指数的补充和支持。
