Centrality and aggregation measurement method based on city expansion global structure

Abstract

The invention discloses a centrality and aggregation measurement method based on a city expansion global structure. The method comprises the steps: providing a position centrality index (LCI), whereinthe index adopts an 'area inverse distance' weighting algorithm to obtain the position weight of a newly added urban patch relative to an original urban overall space structure, and capturing the dynamic characteristics of an urban expansion structure by utilizing the geometrical characteristics of a circle. The method further provides another index, namely a central aggregation index (LCAI), andthe index describes the evolution heterogeneity of the urban form by combining the attributes of the new plaques on the basis of considering the urban expansion global space structure. According to the method, the indexes are combined, the dynamic evaluation blank of the urban expansion centrality is filled up by clearly revealing the global structure characteristics, the performance of identifying the urban expansion aggregation heterogeneity is improved, the expansion characteristic type of the urban newly-added land space is clarified, and the urban expansion aggregation heterogeneity is improved. The practical application requirements of reflecting different city expansion characteristics from bottom to top are met.

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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