Spatiotemporal Evolution and Driving Factors of Land Economic Density at Township Scale: A Case Study of Anyang City, China

Zechen Wang, Xin Shen, Jiayuan Mao (), Zhangyanyang Yao and Shiliang Liu ()
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Zechen Wang: State Key Laboratory of Regional Environment and Sustainability, School of Environment, Beijing Normal University, Beijing 100875, China
Xin Shen: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China
Jiayuan Mao: School of Geographic Sciences, East China Normal University, Shanghai 200241, China
Zhangyanyang Yao: School of Energy and Environment, City University of Hong Kong, Hong Kong SAR 999077, China
Shiliang Liu: State Key Laboratory of Regional Environment and Sustainability, School of Environment, Beijing Normal University, Beijing 100875, China

Land, 2025, vol. 14, issue 11, 1-18

Abstract: Land economic density (LED) is vital for optimizing industrial structure and promoting intensive resource utilization. However, most existing studies have focused on city or county scales, with limited attention to township-level patterns. To address this research gap, we take 86 townships in Anyang City as research units and develop a four-dimensional evaluation system for LED. The study aims to reveal the spatial patterns and driving mechanisms of township-level LED evolution. This study is based on township-level land use, statistical, and socioeconomic data from 2005 to 2023. Using ArcGIS 10.5 for spatial analysis, spatial autocorrelation, standard deviation ellipse, and geographically weighted regression methods were applied to explore the spatiotemporal evolution and driving mechanisms of LED in Anyang City. The results indicate that (1) high-LED areas form a ring around the central city with dual cores in western Linzhou county and southeastern Huaxian county, while low-LED areas are concentrated at the northwestern and northeastern margins; (2) global spatial autocorrelation is weak, with low–low clusters shrinking from contiguous patches to only three townships by 2023, while high–high clusters expand from isolated points to multi-centered diffusion; (3) the ellipse consistently shows a northwest–southeast orientation, with the rotation angle increasing from 128.24° to 130.35°, the flatness ratio rising from 0.432 to 0.445, and the centroid shifting northwest then southeast; (4) The geographically weighted regression (GWR) results highlight economic foundation, industrial upgrading, and government support as the dominant drivers. Based on these findings, we propose a “One Core–Four Poles, Three Axes–Five Zones” spatial optimization framework to promote coordinated urban–rural development. This study provides a practical and multidimensional evaluation approach at the township level, offering methodological support for regional territorial spatial planning and sustainable development.

Keywords: land economic density; multidimensional index system; driving factor; spatial optimization; Anyang (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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