Evidence map›Paper›PMID 42260085›Full record

ArticleScientific reports2026

Cultural landscape clustering and zoning of traditional rural settlements.

Deyi Kong, Xinhui Fei, Ziyi Li

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Deyi KongCollege of Architecture and Urban Planning, Qingdao University of Technology, Qingdao City, China. kongdeyizi@qq.com.
Xinhui FeiCollege of Resources and Environment, Anqing Normal University, Anqing City, China.
Ziyi LiDepartment of Architectural Engineering, Dong-eui University, Seoul, Korea.

Funding

Construction and Application of Traditional Residential Color Palette in the Minjiang River Basin Based on the Color Preferences of the Original Residents 2023Y4003
6 · The paper itself

Abstract

Settlement cultural landscape serves as a prominent indicator reflecting regional disparities in cultural landscapes, among which the cultural landscape of traditional villages is the most direct and representative manifestation. From the cultural landscape perspective, this study deconstructs landscape characteristics and constructs a traditional village landscape classification system comprising 13 indicators across four dimensions: geographical environment, morphological layout, traditional building, and social culture. Using the K‑modes clustering method, 520 traditional village samples in the Min River Basin are classified into distinct cultural landscape types. By integrating these clustering results with city‑ and county‑level administrative divisions, dominant regional cultures, and river basin systems, the study further delineates eight traditional village cultural landscape zones: Jian River Northern Fujian Cultural Landscape Zone, Futun River Min-Gan Cultural Landscape Zone, Min River Middle Stream Eastern Min Cultural Landscape Zone, Min River Downstream Eastern Min Cultural Landscape Zone, Dazhang River Eastern Min Cultural Landscape Zone, You River Central Min Transitional Cultural Landscape Zone, Sha River Central Min Cultural Landscape Zone, and Jiulong River Min-Hakka Cultural Landscape Zone. This zoning provides a scientific reference for identifying village tourism characteristics, sustaining the inheritance of village cultural contexts, and advancing the concentrated and contiguous protection and utilization of traditional villages.

Indexed as

CultureRural PopulationChinaCluster AnalysisGeographyHumansRiversCultural landscapeK-modes clusteringMin River BasinRegionalizationTraditional village

Identifiers

PMID42260085
PMCPMC13451424

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.