湖南省传统村落遗产的空间分布特征研究
A Study on the Spatial Distribution Characteristics of Traditional Village Architectural Heritage in Hunan Province
投稿时间:2023-06-09  修订日期:2023-08-14
DOI:
中文关键词:  传统村落  空间分布  湖南省
English Keywords:Traditional villages  SSpatial distribution  SHunan Province
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作者单位邮编
李涛南华大学 松霖建筑与设计艺术学院 421001
车轩 
王宽* 南华大学 421001
李晟 
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中文摘要:
      文章基于中国传统村落名录结合自然地理与经济社会数据,运用GIS空间分析法,选取最邻近距离、地理集中化指数、核密度等分析模型,揭示了湖南省传统村落遗产的空间分布特征及其影响因素。研究发现,湖南省传统村落遗产的最邻近点指数R=0.64<1,表明这些村落趋向于集聚分布,空间分布类型属于凝聚型。湖南省的传统村落在14个市州地理区域分布的空间基尼系数G =0.3,表明其在各市州分布不均衡。核密度分析发现传统村落在全省范围内形成了3个明显的集聚区,分别为怀化、湘西-张家界,以及永州-郴州地区,这3个集聚区拥有全省近80%的传统村落。经济与社会发展方面的差异是造成这种空间分异特征的主导因素;另外,人均GDP∩土地开发强度、人均GDP∩公路密度以及公路密度∩距水系距离对这种空间分异现象具有较强解释力,表明这种空间分异是各影响因素协同作用下的结果。
English Summary:
      Based on the list of Chinese traditional villages, combined with physical geography and economic and social data, this paper uses the GIS spatial analysis method to select the nearest distance, geographical concentration index, nuclear density and other analysis models, and reveals the spatial distribution characteristics and influencing factors of the architectural heritage of traditional villages in Hunan Province.?Research has found that the nearest point index of traditional village architectural heritage in Hunan Province, R=0.64<1, indicates that these villages tend to be clustered and have a spatial distribution type of agglomeration.?The spatial Gini coefficient G=0.3 for the distribution of traditional villages in 14 cities and states in Hunan Province indicates that their distribution is uneven and not clustered in each city and state.?Nuclear density analysis found that traditional villages have formed three distinct clusters throughout the province, namely Huaihua, Xiangxi Zhangjiajie, and Yongzhou Chenzhou regions. These three clusters account for nearly 80% of traditional villages in the province.?The differences in economic and social development are the dominant factors causing this spatial differentiation feature; In addition, the ratio of per capita GDP to land development intensity, per capita GDP to highway density, and highway density to distance from the water system have strong explanatory power for this spatial differentiation phenomenon, indicating that this spatial differentiation is the result of the synergistic effect of various influencing factors.
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