Distribution of Chinese traditional villages and influencing factors for regionalization

Detalhes bibliográficos
Autor(a) principal: Wu,Yunong
Data de Publicação: 2021
Outros Autores: Wu,Mengqi, Wang,Zhexiao, Zhang,Beiming, Li,Changzuo, Zhang,Bin
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Ciência Rural
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021000700801
Resumo: ABSTRACT: Traditional Villages (TVs) are typical and representative of the agricultural civilization in millions of Chinese villages. The distribution of TVs shows spatial heterogeneity, based on the complexity and diversity of several influencing factors. In this study, 6,819 Chinese TVs were identified and the influencing factors that affect their distribution were screened in terms of three indicator groups: climatic, geographic, and humanity-related factors. Additionally, the K-means clustering algorithm clustered the TVs into different distribution regions. The quantitative relationships between the dominant influencing factors of different distribution regions were revealed to ensure a lucid understanding of the regional distribution of TVs. The results indicated that 1) climatic factors have the greatest impact on the spatial distribution of TVs, followed by geographic factors, particularly the elevation, and then by human factors, of which ethnic distribution played a relatively important role. 2) Twenty-one TV clustering distributions were obtained, which were classified into eight regions of TV distribution with different dominant influencing factors. Management and protective strategies were formulated based on the attribute analysis of influencing factors in each region. The obtained results delineated homogeneous TV distribution regions via the clustering method to achieve an accurate statistical analysis of the influencing factors. This study proposes a new perspective and reference for managing and protecting the diversity, continuity, and integrity of TVs across administrative regions.
id UFSM-2_9980e39d3865878a7011f288e81e146c
oai_identifier_str oai:scielo:S0103-84782021000700801
network_acronym_str UFSM-2
network_name_str Ciência rural (Online)
repository_id_str
spelling Distribution of Chinese traditional villages and influencing factors for regionalizationtraditional/ historical rural settlementsdominant factorscluster analysisdistribution regionsgeographic information system.ABSTRACT: Traditional Villages (TVs) are typical and representative of the agricultural civilization in millions of Chinese villages. The distribution of TVs shows spatial heterogeneity, based on the complexity and diversity of several influencing factors. In this study, 6,819 Chinese TVs were identified and the influencing factors that affect their distribution were screened in terms of three indicator groups: climatic, geographic, and humanity-related factors. Additionally, the K-means clustering algorithm clustered the TVs into different distribution regions. The quantitative relationships between the dominant influencing factors of different distribution regions were revealed to ensure a lucid understanding of the regional distribution of TVs. The results indicated that 1) climatic factors have the greatest impact on the spatial distribution of TVs, followed by geographic factors, particularly the elevation, and then by human factors, of which ethnic distribution played a relatively important role. 2) Twenty-one TV clustering distributions were obtained, which were classified into eight regions of TV distribution with different dominant influencing factors. Management and protective strategies were formulated based on the attribute analysis of influencing factors in each region. The obtained results delineated homogeneous TV distribution regions via the clustering method to achieve an accurate statistical analysis of the influencing factors. This study proposes a new perspective and reference for managing and protecting the diversity, continuity, and integrity of TVs across administrative regions.Universidade Federal de Santa Maria2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021000700801Ciência Rural v.51 n.7 2021reponame:Ciência Ruralinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM10.1590/0103-8478cr20200124info:eu-repo/semantics/openAccessWu,YunongWu,MengqiWang,ZhexiaoZhang,BeimingLi,ChangzuoZhang,Bineng2021-04-08T00:00:00ZRevista
dc.title.none.fl_str_mv Distribution of Chinese traditional villages and influencing factors for regionalization
title Distribution of Chinese traditional villages and influencing factors for regionalization
spellingShingle Distribution of Chinese traditional villages and influencing factors for regionalization
Wu,Yunong
traditional/ historical rural settlements
dominant factors
cluster analysis
distribution regions
geographic information system.
title_short Distribution of Chinese traditional villages and influencing factors for regionalization
title_full Distribution of Chinese traditional villages and influencing factors for regionalization
title_fullStr Distribution of Chinese traditional villages and influencing factors for regionalization
title_full_unstemmed Distribution of Chinese traditional villages and influencing factors for regionalization
title_sort Distribution of Chinese traditional villages and influencing factors for regionalization
author Wu,Yunong
author_facet Wu,Yunong
Wu,Mengqi
Wang,Zhexiao
Zhang,Beiming
Li,Changzuo
Zhang,Bin
author_role author
author2 Wu,Mengqi
Wang,Zhexiao
Zhang,Beiming
Li,Changzuo
Zhang,Bin
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Wu,Yunong
Wu,Mengqi
Wang,Zhexiao
Zhang,Beiming
Li,Changzuo
Zhang,Bin
dc.subject.por.fl_str_mv traditional/ historical rural settlements
dominant factors
cluster analysis
distribution regions
geographic information system.
topic traditional/ historical rural settlements
dominant factors
cluster analysis
distribution regions
geographic information system.
description ABSTRACT: Traditional Villages (TVs) are typical and representative of the agricultural civilization in millions of Chinese villages. The distribution of TVs shows spatial heterogeneity, based on the complexity and diversity of several influencing factors. In this study, 6,819 Chinese TVs were identified and the influencing factors that affect their distribution were screened in terms of three indicator groups: climatic, geographic, and humanity-related factors. Additionally, the K-means clustering algorithm clustered the TVs into different distribution regions. The quantitative relationships between the dominant influencing factors of different distribution regions were revealed to ensure a lucid understanding of the regional distribution of TVs. The results indicated that 1) climatic factors have the greatest impact on the spatial distribution of TVs, followed by geographic factors, particularly the elevation, and then by human factors, of which ethnic distribution played a relatively important role. 2) Twenty-one TV clustering distributions were obtained, which were classified into eight regions of TV distribution with different dominant influencing factors. Management and protective strategies were formulated based on the attribute analysis of influencing factors in each region. The obtained results delineated homogeneous TV distribution regions via the clustering method to achieve an accurate statistical analysis of the influencing factors. This study proposes a new perspective and reference for managing and protecting the diversity, continuity, and integrity of TVs across administrative regions.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021000700801
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021000700801
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0103-8478cr20200124
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência Rural v.51 n.7 2021
reponame:Ciência Rural
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Ciência Rural
collection Ciência Rural
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1749140556068421632