Analysis of the heterogeneity of urban expansion landscape patterns and driving factors based on a combined Multi-Order Adjacency Index and Geodetector model

Abstract

Under conditions of rapid urbanization, quantitative measurement of the expansion characteristics of urban landscapes and evaluation of their spatial and temporal differentiation properties is an important scientific problem. The Multi-order Adjacency Index (MAI) is an effective indicator of the quantitative characteristics of urban landscape expansion; however, it cannot directly reflect the spatial heterogeneity of this expansion. Therefore, it is necessary to combine the MAI with a spatial heterogeneity detection method to measure and evaluate the spatiotemporal divergence features of urban landscape expansion. In this study, taking Chenggong District, Kunming City, Yunnan Province, China as the study area, we apply MAI to analyze the changing process of urban landscape pattern expansion, and use the Geodetector to analyze the drivers affecting the spatial divergence of this expansion. We compare the results with the Landscape Extension Index and geographically-weighted regression models. The results show that MAI can reveal urban landscape expansion well at the micro-level, and analysis of the urban landscape expansion process reveals that it is mainly socio-economic factors that lead to the spatial heterogeneity of urban landscape expansion. Combining MAI and Geodetector can solve the problem that existing methods cannot directly reflect the heterogeneity of urban expansion landscape patterns and their causes.