Centrality and Agglomeration Measurement Method Based on the Global Structure of Urban Expansion

Abstract

The invention discloses a method for measuring centrality and agglomeration based on the global structure of urban expansion. This method first proposes the location centrality index (LCI), which uses the "area-inverse distance" weighting algorithm to obtain the position weight of the new urban patches compared with the original urban overall spatial structure, and uses the geometric characteristics of the circle to capture the urban Expansion structure dynamic features. This method also proposes another indicator—the central agglomeration index (LCAI), which describes the evolutionary heterogeneity of urban form by combining the attributes of new patches themselves on the basis of considering the global spatial structure of urban expansion. The method of the present invention combines the above indicators, by clearly revealing the global structural characteristics, filling the gap in the dynamic evaluation of the centrality of urban expansion, improving the performance of identifying the heterogeneity of urban expansion and aggregation, and clarifying the types of expansion characteristics of urban new land use space , which meets the practical application needs of reflecting the characteristics of different urban sprawl from bottom to top.

Description

technical field [0001] The invention belongs to the technical field of spatial analysis, in particular to a method for measuring centrality and agglomeration based on the overall structure of urban expansion. Background technique [0002] Urbanization is accompanied by the spatial expansion of urban land, with serious impacts on resources, the environment and society [1–2] . There is a consensus that rational use of land resources requires a better understanding of the process of urban sprawl [3–5] . Therefore, quantitative evaluation indicators of urban sprawl processes have been considered as powerful means to understand urban sprawl, which has attracted increasing attention from the urban science community in recent years. [6–7] . [0003] The landscape index is one of the most widely used methods to describe the spatial pattern of urban sprawl [8–10] , most of the landscape indices are developed based on information theory, fractal geometry, and spatial statistics, ...

AI Technical Summary

Problems solved by technology

However, landscape indices have an inherent flaw: these indices can only characterize static patterns at a single point in time, but cannot capture dynamic process information [14]

Since urban sprawl is a multidimensional process, a vague and simple division of urban sprawl into compactness or sprawl based on one-dimensional neighborhood characteristics will lead to inaccurate evaluations and prevent a better understanding of the spatial characteristics of the urban sprawl process

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