[1]Liu Daqian,Wang Dan,Xu Jun,et al.The Spatial Pattern of Rural Settlements and Its Influencing Factors in Changbai Mountain Region[J].Research of Soil and Water Conservation,2024,31(03):383-390,400.[doi:10.13869/j.cnki.rswc.2024.03.035]
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The Spatial Pattern of Rural Settlements and Its Influencing Factors in Changbai Mountain Region
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
31
Number of periods:
2024 03
Page number:
383-390,400
Column:
Public date:
2024-04-30
- Title:
- The Spatial Pattern of Rural Settlements and Its Influencing Factors in Changbai Mountain Region
- Keywords:
- rural settlements; spatial patterns; spatial regression model; Geodetector; Changbai Mountain Region
- CLC:
- K901.8
- DOI:
- 10.13869/j.cnki.rswc.2024.03.035
- Abstract:
- [Objective] This study aims to explore the spatial distribution characteristics and influencing factors of rural settlements in the Changbai Mountain region, and to understand the formation process and mechanisms of the spatial patterns of rural residential areas in the middle and high latitude mountainous areas under the background of the large-scale migration in modern times. [Methods] Analytical methods including Kernel Density analysis, spatial autocorrelation analysis, spatial regression analysis, and Geodetector were used to examine the spatial pattern of rural settlements in the Changbai Mountain region and identify its influencing factors. [Results] The rural settlements in the Changbai Mountain region exhibited an obvious clustering distribution, with two distinctive clusters in the northeast and southwest. Among various spatial regression methods, the Spatial Durbin Error Model showed the best fit. The arable land resources and elevation were the most important factors influencing the spatial patterns of rural settlements in the Changbai Mountain region. Furthermore, these two factors exhibited a ‘push-pull' effect on the layout of neighboring settlements. Potential unknown variables such as soil quality and cultural factors also contributed to the spatial autocorrelation of rural settlements. Geodetector analysis further confirmed the importance of arable land resources and elevation. Additionally, distance to urban areas at the county level or above, administrative towns, major transportation routes, and main rivers, as well as slope, significantly influenced the distribution of rural settlements, and these factors exhibited the mutual enhancement effect. [Conclusion] The spatial patterns of rural settlements in the middle and high latitude mountainous areas, primarily formed by migration, are the result of the combined effects of multiple factors, with arable land resources and elevation being more significant. The Spatial Durbin Error Model can simultaneously detect the spatial autocorrelation effects of both the dependent and independent variables, making it applicable to the study on spatial patterns of rural settlements.
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Last Update:
2024-04-30