Evidence map›Paper›PMID 38001125›Full record

ArticleScientific reports2023

Analysis on the geographical pattern and driving force of traditional villages based on GIS and Geodetector: a case study of Guizhou, China.

Kehua Wu, Weici Su, Shi'an Ye, Wei Li, Yang Cao, Zhenzhen Jia

Abstract read
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Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Kehua WuInstitute of Mountain Resources, Guizhou Academy of Sciences, Guiyang, 550001, China. kehuakarst@163.com.
Weici SuSchool of Geography and Tourism, Chongqing Normal University, Chongqing, 401331, China. suweici@sina.com.
Shi'an YeInstitute of Mountain Resources, Guizhou Academy of Sciences, Guiyang, 550001, China.
Wei LiInstitute of Mountain Resources, Guizhou Academy of Sciences, Guiyang, 550001, China.
Yang CaoInstitute of Mountain Resources, Guizhou Academy of Sciences, Guiyang, 550001, China.
Zhenzhen JiaInstitute of Mountain Resources, Guizhou Academy of Sciences, Guiyang, 550001, China.

Funding

2016 High-Level Innovative Talents Project in Guizhou Province [2016]21Innovation Talent Team Capability Improvement Project of Guizhou Academy of Sciences [2019]08National Natural Science Foundation of China 42161052The National Key Research and Development Program of the Thirteenth in China 2016YFC0502606
6 · The paper itself

Abstract

Traditional villages have received widespread attention from all walks of life based on important carriers of Chinese rural culture. The mutual superposition of natural and cultural factors may exacerbate the evolution of traditional village geographical patterns. To understand such relationships and effects, factors and degrees influencing traditional villages need to be determined. Here, we analysed the data of 724 traditional villages in Guizhou recognised by relevant national ministries and commissions in China using average nearest neighbour analysis, Tyson polygon analysis, nuclear density analysis and Geodector. The geographic pattern feature revealed that traditional villages, in general, are highly clustered regionally and have significant edge effects on administrative units. Different substrate environments result in significant spatial heterogeneity in village spatial density, clustering, surface undulation, sun exposure, and waterfront. The geographic pattern of traditional villages is mostly affected by the closest distance to river valleys, the types and number of intangible cultural heritage resources in the county, river gorge density, edge effect index, degree of county ethnic language use, and proportion of paddy fields to the regional area; and their combined effects influence and control the community structure. The results highlight the impact of nature and culture on the distribution of traditional villages, which helps traditional village conservation and scientific exploration of human-land relationship issues in the mountainous areas of Southwest China.

Indexed as

Geographic Information SystemsRural PopulationChinaCluster AnalysisHumansRivers

Identifiers

PMID38001125
PMCPMC10673962

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.