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中国传统村落的空间分布特征及影响因素

Spatial Distribution Characteristics and Influencing Factors of Traditional Villages in China.

机构信息

Department of Geography, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China.

出版信息

Int J Environ Res Public Health. 2022 Apr 12;19(8):4627. doi: 10.3390/ijerph19084627.

DOI:10.3390/ijerph19084627
PMID:35457495
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9029868/
Abstract

Traditional villages carry the essence of traditional culture, which is necessary for rural revitalisation. However, continuous urban expansion has resulted in the rapid decline and even disappearance of these villages in recent decades. It is necessary to analyse the spatial pattern and influencing factors for the protection and development of traditional villages. Previous studies focused on the value and theoretical protection mechanism of traditional villages in China, disregarding their spatial distribution characteristics and influencing factors. Thus, we employed a Geographic Information System and spatial analysis with mathematical statistics to analyse the characteristics of these villages. Moreover, we analysed the associated influencing factors both qualitatively and quantitatively. The results show that traditional villages were mainly distributed in the southeast of the Hu Line in China, with an unbalanced spatial distribution pattern and an agglomeration distribution tendency. In general, four major agglomeration areas of traditional villages formed at the junction of Hebei, Shandong, and Henan provinces; the border between the Guizhou, Guangxi, and Hunan provinces; the border between the Anhui, Zhejiang, and Jiangxi provinces; and northwestern and southeastern Yunnan provinces. Traditional villages also existed in areas with relief lower than 300 m, altitudes of less than 1000 m, and slopes of less than 10°. They were mostly distributed in subtropical and temperate zones. A positive correlation was found between traditional villages and the level of economic development, population, and human history; conversely, the transportation network was negatively correlated. This study reveals the complex and diverse characteristics of traditional villages and provides scientific suggestions for their future protection, development, and utilisation.

摘要

传统村落承载着传统文化的精髓,是乡村振兴的必要条件。然而,近几十年来,城市的不断扩张导致这些村落迅速减少甚至消失。有必要分析传统村落的保护与发展的空间格局和影响因素。以往的研究主要集中在中国传统村落的价值和理论保护机制上,而忽略了它们的空间分布特征和影响因素。因此,我们采用地理信息系统和空间分析与数理统计相结合的方法,分析了这些村落的特征。此外,我们还定性和定量地分析了相关影响因素。结果表明,传统村落主要分布在中国胡焕庸线东南部,空间分布格局不均衡,呈集聚分布趋势。总体上,传统村落形成了四大集聚区,分别位于河北、山东和河南三省交界处;贵州、广西和湖南三省交界处;安徽、浙江和江西三省交界处;以及云南西北部和东南部。传统村落还分布在海拔低于 300 米、海拔低于 1000 米、坡度小于 10°的地区。它们主要分布在亚热带和温带地区。传统村落与经济发展水平、人口和人类历史呈正相关,而与交通网络呈负相关。本研究揭示了传统村落的复杂多样特征,为其未来的保护、发展和利用提供了科学建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/51ed40a8ff5a/ijerph-19-04627-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/6871950b57a9/ijerph-19-04627-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/df1674eead7f/ijerph-19-04627-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/04863c43e255/ijerph-19-04627-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/99c86abca19d/ijerph-19-04627-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/89b62c194b12/ijerph-19-04627-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/c8c355e1861b/ijerph-19-04627-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/296df47c96a3/ijerph-19-04627-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/f7b8a1c09925/ijerph-19-04627-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/757b9b71b3e2/ijerph-19-04627-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/58a48047e9a7/ijerph-19-04627-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/51ed40a8ff5a/ijerph-19-04627-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/6871950b57a9/ijerph-19-04627-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/df1674eead7f/ijerph-19-04627-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/04863c43e255/ijerph-19-04627-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/99c86abca19d/ijerph-19-04627-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/89b62c194b12/ijerph-19-04627-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/c8c355e1861b/ijerph-19-04627-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/296df47c96a3/ijerph-19-04627-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/f7b8a1c09925/ijerph-19-04627-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/757b9b71b3e2/ijerph-19-04627-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/58a48047e9a7/ijerph-19-04627-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5de/9029868/51ed40a8ff5a/ijerph-19-04627-g011.jpg

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