A study on the spatial distribution and driving factors of traditional villages–a case study of the Beijing-Tianjin-Hebei region in China

Traditional villages encompass abundant cultural resources, possessing significant humanistic and socio-economic value. This study used ArcGIS 10.8 and GeoDa software, took "Chinese Traditional Villages" as the research object, and analyzed their spatial autocorrelation and spatial heterogeneity through methods such as nearest neighbor analysis, Moran's Index, and kernel density estimation. Additionally, by combining techniques like Geodetector, ordinary least squares (OLS), and geographically weighted regression (GWR), the study selected the 10 most correlated driving factors and examined the drivers of their spatial distribution characteristics. The results are as follows: (1) The spatial distribution of villages exhibits significant clustering characteristics. (2) Rainfall and GDP per capita are the two important explanatory variables influencing the spatial distribution of villages. (3)The clustering phenomenon of villages is positively correlated with temperature, rainfall, and tourism resources, while negatively correlated with population density and overall economic level.

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Publication Details

Journal
Scientific Reports
Published
2025-08-05
DOI
https://doi.org/10.1038/s41598-025-14127-4
Citations
5
Primary Topic
Regional Economic and Spatial Analysis
Type
article
Field-Weighted Citation Impact
15.66
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article

A study on the spatial distribution and driving factors of traditional villages–a case study of the Beijing-Tianjin-Hebei region in China

Peng Peng, Limin Zhao, Y. L. Zhang, Yan Rong et al.
5 citations
Scientific Reports
Regional Economic and Spatial Analysis
15.66
article

A study on the spatial distribution and driving factors of traditional villages–a case study of the Beijing-Tianjin-Hebei region in China

Peng Peng, Limin Zhao, Y. L. Zhang, Yan Rong, Jinyu Wu, Jiajie Zhao
article en
5 citations

Abstract

Traditional villages encompass abundant cultural resources, possessing significant humanistic and socio-economic value. This study used ArcGIS 10.8 and GeoDa software, took "Chinese Traditional Villages" as the research object, and analyzed their spatial autocorrelation and spatial heterogeneity through methods such as nearest neighbor analysis, Moran's Index, and kernel density estimation. Additionally, by combining techniques like Geodetector, ordinary least squares (OLS), and geographically weighted regression (GWR), the study selected the 10 most correlated driving factors and examined the drivers of their spatial distribution characteristics. The results are as follows: (1) The spatial distribution of villages exhibits significant clustering characteristics. (2) Rainfall and GDP per capita are the two important explanatory variables influencing the spatial distribution of villages. (3)The clustering phenomenon of villages is positively correlated with temperature, rainfall, and tourism resources, while negatively correlated with population density and overall economic level.

Scientific ReportsVol. 15(1)
Shijiazhuang Tiedao University (CN)
Reduced inequalities
Openalex Percentile: Top 1%
Regional Economic and Spatial Analysis
15.66
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