• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

黄河流域传统村落的时空分布特征及驱动因素。

Spatio-Temporal distribution characteristics and driving factors of traditional villages in the Yellow River Basin.

机构信息

School of Architecture and Urban Planning, Lanzhou Jiaotong University, Lanzhou, China.

出版信息

PLoS One. 2024 May 21;19(5):e0303396. doi: 10.1371/journal.pone.0303396. eCollection 2024.

DOI:10.1371/journal.pone.0303396
PMID:38771883
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11108216/
Abstract

Currently, research on traditional villages mainly focuses on the current development status and evolutionary trends in specific regions, with relatively limited studies from a macroscopic and holistic perspective on the spatiotemporal evolution of traditional villages. Therefore, this study selects traditional villages in the Yellow River Basin (YRB) as the research object. By analyzing the spatiotemporal distribution characteristics and driving factors of traditional villages (TVs) in the basin, it aims to further promote high-quality development in the YRB and protect traditional cultural resources. Based on data from 892 village points of the first to sixth batches of TVs in the YRB, ArcGIS 10.8 spatial analysis techniques were employed to analyze the overall spatial pattern of TVs in the YRB. The results indicate: (1) In the basin, TVs are more numerous in the east than the west and more in the south than the north, forming clusters and contiguous distributions, with dense areas primarily in the upstream regions dominated by Qinghai Province and the midstream areas along the Shanxi-Shaanxi coast. (2) The number and scale of TVs in the basin generally exhibit an increasing trend, with imbalanced provincial distribution. More recent years show a more balanced distribution of villages and proportions, with a higher number of villages in the mountainous and plateau regions of the basin. (3) The layout center of TVs within the basin evolves with each batch, showing a migration pattern from north to south, back to north, and finally east to west. (4) The interaction of natural and social factors plays a synergistic role in driving the spatiotemporal distribution pattern of TVs. Among these, natural geographical factors are the primary factors. TVs are more commonly found in regions with low altitude sunny slopes, mild climate, abundant precipitation, proximity to ancient roads and rivers, gentle slopes, and soil predominantly comprising loess, brown earth, and alluvial soils. The cultural environment is a secondary factor, with TVs often located in areas with larger populations, developed economies, and rich cultural heritage.

摘要

目前,传统村落的研究主要集中在特定区域的现状发展和演变趋势上,从宏观和整体的角度对传统村落的时空演变研究相对较少。因此,本研究选择黄河流域(YRB)的传统村落作为研究对象。通过分析流域内传统村落的时空分布特征和驱动因素,旨在进一步促进黄河流域的高质量发展,保护传统的文化资源。基于黄河流域一至六批传统村落 892 个村点的数据,利用 ArcGIS 10.8 空间分析技术,分析了黄河流域传统村落的整体空间格局。结果表明:(1)黄河流域东部传统村落多于西部,南部多于北部,呈集聚分布,密集区主要集中在以青海省为主的上游地区和沿山西-陕西海岸的中游地区。(2)流域内传统村落的数量和规模总体呈增长趋势,分布不均。近几年,村落数量和比例分布更加均衡,流域内山区和高原地区的村落数量较多。(3)流域内传统村落的布局中心随批次而变化,呈现从北到南、再到北、最后到西的迁移模式。(4)自然和社会因素的相互作用对传统村落的时空分布模式起着协同作用。在这些因素中,自然地理因素是主要因素。传统村落更常见于海拔较低、阳光充足的山坡、气候温和、降水丰富、靠近古道和河流、坡度较缓、土壤主要为黄土、褐土和冲积土的地区。文化环境是次要因素,传统村落通常位于人口较多、经济发达、文化遗产丰富的地区。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/96bc916cf677/pone.0303396.g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/3ca0fff53f79/pone.0303396.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/807b23f3d5df/pone.0303396.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/8503140112e0/pone.0303396.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/5be82c4b463d/pone.0303396.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/f6a1865a630f/pone.0303396.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/0b0361993d53/pone.0303396.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/af9b1439a91a/pone.0303396.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/4098f81ab9a5/pone.0303396.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/f3279b61fd3e/pone.0303396.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/2e571aa8b83f/pone.0303396.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/96bc916cf677/pone.0303396.g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/3ca0fff53f79/pone.0303396.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/807b23f3d5df/pone.0303396.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/8503140112e0/pone.0303396.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/5be82c4b463d/pone.0303396.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/f6a1865a630f/pone.0303396.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/0b0361993d53/pone.0303396.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/af9b1439a91a/pone.0303396.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/4098f81ab9a5/pone.0303396.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/f3279b61fd3e/pone.0303396.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/2e571aa8b83f/pone.0303396.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7e8/11108216/96bc916cf677/pone.0303396.g011.jpg

相似文献

1
Spatio-Temporal distribution characteristics and driving factors of traditional villages in the Yellow River Basin.黄河流域传统村落的时空分布特征及驱动因素。
PLoS One. 2024 May 21;19(5):e0303396. doi: 10.1371/journal.pone.0303396. eCollection 2024.
2
A study on the spatial distribution characteristics and driving factors of traditional villages in the southeast coast of China: A case study of Puxian, Fujian.中国东南沿海传统村落空间分布特征及驱动因素研究——以福建浦为例
PLoS One. 2024 Jun 7;19(6):e0303746. doi: 10.1371/journal.pone.0303746. eCollection 2024.
3
The dynamic patterns and driving factors of land use conflict in the Yellow River basin of China.中国黄河流域土地利用冲突的动态格局和驱动因素。
Environ Sci Pollut Res Int. 2023 Oct;30(50):108649-108666. doi: 10.1007/s11356-023-29996-3. Epub 2023 Sep 26.
4
Spatial and temporal characteristic of PM2.5 and influence factors in the Yellow River Basin.黄河流域 PM2.5 的时空特征及影响因素。
Front Public Health. 2024 Jul 31;12:1403414. doi: 10.3389/fpubh.2024.1403414. eCollection 2024.
5
Spatial differentiation and geographical similarity of traditional villages--Take the Yellow River Basin and the Yangtze River Basin as examples.传统村落的空间分异与地域相似性——以黄河流域和长江流域为例。
PLoS One. 2024 Feb 2;19(2):e0295854. doi: 10.1371/journal.pone.0295854. eCollection 2024.
6
Spatiotemporal evolution and driving factors of ecosystem services' transformation in the Yellow River basin, China.中国黄河流域生态系统服务功能转化的时空演变及驱动因素
Environ Monit Assess. 2024 Feb 10;196(3):252. doi: 10.1007/s10661-024-12397-5.
7
[Driving Mechanism of the Spatiotemporal Evolution of Vegetation in the Yellow River Basin from 2000 to 2020].[2000—2020年黄河流域植被时空演变驱动机制]
Huan Jing Ke Xue. 2022 Feb 8;43(2):743-751. doi: 10.13227/j.hjkx.202105213.
8
Spatiotemporal pattern and obstacle factors of coupling relationship between habitat quality and urbanization level in the Yellow River Basin, China.中国黄河流域生境质量与城市化水平耦合关系的时空格局及障碍因子。
Environ Monit Assess. 2024 Aug 16;196(9):818. doi: 10.1007/s10661-024-12948-w.
9
Spatiotemporal Evolution and Spatial Network Analysis of the Urban Ecological Carrying Capacity in the Yellow River Basin.黄河流域城市生态承载力的时空演变与空间网络分析。
Int J Environ Res Public Health. 2021 Dec 26;19(1):229. doi: 10.3390/ijerph19010229.
10
Spatiotemporal Variations of Carbon Emissions and Their Driving Factors in the Yellow River Basin.黄河流域碳排放的时空变化及其驱动因素。
Int J Environ Res Public Health. 2022 Oct 8;19(19):12884. doi: 10.3390/ijerph191912884.

引用本文的文献

1
Cultural heritage of the Qin-Shu Ancient Road in Shaanxi: Spatial distribution characteristics and influencing factors.陕西秦蜀古道文化遗产:空间分布特征及影响因素
PLoS One. 2025 Sep 9;20(9):e0331676. doi: 10.1371/journal.pone.0331676. eCollection 2025.
2
The spatial distribution characteristics and influencing factors of key villages in rural tourism in China.中国乡村旅游重点村的空间分布特征及影响因素
PLoS One. 2025 Aug 19;20(8):e0330486. doi: 10.1371/journal.pone.0330486. eCollection 2025.
3
Spatial structure and influencing factors of agricultural civilization heritage in the Yellow River Basin.

本文引用的文献

1
Revitalize the world's countryside.振兴世界农村地区。
Nature. 2017 Aug 16;548(7667):275-277. doi: 10.1038/548275a.
黄河流域农业文明遗产的空间结构及影响因素
Sci Rep. 2025 Aug 14;15(1):29836. doi: 10.1038/s41598-025-15024-6.
4
A study on the spatial distribution and driving factors of traditional villages-a case study of the Beijing-Tianjin-Hebei region in China.传统村落的空间分布及驱动因素研究——以中国京津冀地区为例
Sci Rep. 2025 Aug 5;15(1):28516. doi: 10.1038/s41598-025-14127-4.
5
Spatial patterns and influencing factors of traditional villages in the Pearl River-Xijiang River Economic Belt (PRXREB).珠江—西江经济带传统村落的空间格局及影响因素
PLoS One. 2025 Apr 18;20(4):e0321646. doi: 10.1371/journal.pone.0321646. eCollection 2025.
6
Spatial and temporal distribution characteristics and evolution of traditional villages in the Qihe River Basin of China.中国漆河流域传统村落的时空分布特征及演变
Sci Rep. 2025 Mar 24;15(1):10077. doi: 10.1038/s41598-025-94872-8.
7
Adoption of K-means clustering algorithm in smart city security analysis and mythical experience analysis of urban image.K均值聚类算法在智慧城市安全分析及城市形象的虚拟体验分析中的应用。
PLoS One. 2025 Mar 10;20(3):e0319620. doi: 10.1371/journal.pone.0319620. eCollection 2025.
8
Study on the spatial distribution characteristics of traditional villages and their response to the water network system in the lower yangtze river basin.长江下游流域传统村落空间分布特征及其对水网系统响应的研究
Sci Rep. 2024 Sep 29;14(1):22586. doi: 10.1038/s41598-024-74363-y.