Study on Spatial Distribution Dispersion Evaluation and Driving Forces of Rural Settlements in the Yellow River Basin

Heying Li, Jianchen Zhang (), Yamin Shan, Guangxia Wang, Qin Tian, Jiayao Wang and Huiling Ma
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Heying Li: Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, China
Jianchen Zhang: Henan Industrial Technology Academy of Spatio-Temporal Big Data, Henan University, Zhengzhou 450046, China
Yamin Shan: Henan Industrial Technology Academy of Spatio-Temporal Big Data, Henan University, Zhengzhou 450046, China
Guangxia Wang: Henan Industrial Technology Academy of Spatio-Temporal Big Data, Henan University, Zhengzhou 450046, China
Qin Tian: Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, China
Jiayao Wang: Henan Industrial Technology Academy of Spatio-Temporal Big Data, Henan University, Zhengzhou 450046, China
Huiling Ma: Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, China

Land, 2024, vol. 13, issue 8, 1-21

Abstract: The spatial distribution pattern of rural settlements in the Yellow River Basin is scattered and numerous. It is of great significance to study the discrete distribution of rural settlements for achieving high-quality development and promoting rural revitalization strategy. In this paper, we propose an enhanced evaluation model for assessing the spatial distribution dispersion of rural settlements, incorporating the weight of road grade (the road grade refers to the ranking of traffic capacity and importance of a particular type of road, indicating varying levels of time accessibility). We investigate the dispersion characteristics of rural settlements in the Yellow River Basin in 2020, focusing on both county and city scales. Furthermore, we conduct a comprehensive analysis of the spatial differentiation and scale effects of dispersion evaluation outcomes and their driving forces. Our findings reveal the following insights: (1) The road grade significantly influences the dispersion evaluation. When considering road grade in the dispersion calculation, the results align more closely with the actual situation. (2) The dispersion of rural settlements in the Yellow River Basin exhibits a decreasing trend from west to east. Specifically, the dispersion is higher in the upper reaches compared to the middle and lower reaches. Both city and county scales show spatial autocorrelation in dispersion, with a positive spatial correlation observed. High dispersion values cluster in the west, while low values concentrate in the east. Notably, the agglomeration degree is more pronounced at the county scale than at the city scale, highlighting more localized patterns of agglomeration and dispersion. (3) The multiscale geographically weighted regression model emerges as the optimal model for analyzing the driving forces of dispersion. At the city scale, factors such as river density, road density, and rural economy negatively impact dispersion. However, at the county scale, average elevation and rural economy positively affect dispersion, whereas river density, road density, and rural population density have a negative influence. By incorporating the weight of road grade into our evaluation model, we provide a more nuanced understanding of the spatial distribution dispersion of rural settlements in the Yellow River Basin. Our findings offer valuable insights for policymakers and planners seeking to optimize rural settlement patterns and promote sustainable rural development.

Keywords: Yellow River Basin; rural settlements; dispersion; driving force (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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