Spatial characteristics and evolution of rural settlement landscape based on fractal theory: A case study of Xiamen, China

doi:10.13287/j.1001-9332.201708.037

Abstract

Abstract: The characteristics of rural settlement landscape are composed of spatial structure and morphology, which are also the basis for optimizing rural land use patterns. Using the fractal theory, this paper quantitatively analyzed the characteristics and evolution of spatial structure rural settlement landscape in Xiamen from the city and town scales, and proposed corresponding optimization counter measures. The results showed that the fractal of spatial structure and pattern of rural settlement landscape was significant in Xiamen. At the city level, aggregation dimension, accessibility of traffic network and spatial dimension increased overtime, while the spatial correlation dimension showed an opposite trend. Overall, the spatial structure of rural settlement landscape showed a multi-center-aggregation distribution, and the accessibility of traffic network got better. Meanwhile, the self-organization of spatial structure constantly optimized, and the spatial form of rural settlement landscape tended to more complicated in terms of extension trend. At the town level, there were significant differences in spatial characteristics of rural settlement landscapes. In some towns, several problems such as loosing spatial structure, poor accessibility of traffic network were still unsolved. In the foreseeable future, the construction of transportation infrastructure and central villages needed to be actively pushed. Besides, the correlation between various elements within the rural settlements also need to be enhanced. The results could provide theoretical and technical support for the optimization of rural settlement space and scientific complication of land use planning.

LIANG Fa-chao, LIU Shi-yuan, LIU Li-ming. Spatial characteristics and evolution of rural settlement landscape based on fractal theory: A case study of Xiamen, China[J]. Chinese Journal of Applied Ecology, 2017, 28(8): 2640-2648.

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