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Spatial heterogeneity of urban–rural integration and its influencing factors in Shandong province of China

Based on nighttime light data and statistical data, this study calculated the level of urban–rural integration (URI) of Shandong province, researched spatial heterogeneity of URI levels by local spatial autocorrelation analysis, Geodetector, and geographically weighted regression, and analyzed its i...

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Autores principales: Shan, Baoyan, Zhang, Qiao, Ren, Qixin, Yu, Xinwei, Chen, Yanqiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9395521/
https://www.ncbi.nlm.nih.gov/pubmed/35995949
http://dx.doi.org/10.1038/s41598-022-18424-0
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author Shan, Baoyan
Zhang, Qiao
Ren, Qixin
Yu, Xinwei
Chen, Yanqiu
author_facet Shan, Baoyan
Zhang, Qiao
Ren, Qixin
Yu, Xinwei
Chen, Yanqiu
author_sort Shan, Baoyan
collection PubMed
description Based on nighttime light data and statistical data, this study calculated the level of urban–rural integration (URI) of Shandong province, researched spatial heterogeneity of URI levels by local spatial autocorrelation analysis, Geodetector, and geographically weighted regression, and analyzed its influencing factors and spatial heterogeneity. The results concluded that: (1) The spatial pattern of urban–rural integrated level is consistent with the level of regional economic development in Shandong province. The level of URI is higher along the Qingdao–Jinan railway and along the coast, whereas the level is lower in southwest Shandong and northwest Shandong. (2) The cities of Yantai and Weifang are High–High cluster areas of urban integration, and Jining is a Low–Low cluster area. The spatial agglomeration characteristics are not significant in other cities. (3) Among the main factors affecting URI, the explanatory power of the rural population with high school or technical secondary school education or above, the area of urban construction land, and the secondary and tertiary industry GDP to the spatial pattern of URI in Shandong province are 73.58%, 62.08%, and 58.66%, respectively. As the key factors, spatial heterogeneity, such as north–south differences, southwest-to-northeast differences, and east–west differences, is evident.
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spelling pubmed-93955212022-08-24 Spatial heterogeneity of urban–rural integration and its influencing factors in Shandong province of China Shan, Baoyan Zhang, Qiao Ren, Qixin Yu, Xinwei Chen, Yanqiu Sci Rep Article Based on nighttime light data and statistical data, this study calculated the level of urban–rural integration (URI) of Shandong province, researched spatial heterogeneity of URI levels by local spatial autocorrelation analysis, Geodetector, and geographically weighted regression, and analyzed its influencing factors and spatial heterogeneity. The results concluded that: (1) The spatial pattern of urban–rural integrated level is consistent with the level of regional economic development in Shandong province. The level of URI is higher along the Qingdao–Jinan railway and along the coast, whereas the level is lower in southwest Shandong and northwest Shandong. (2) The cities of Yantai and Weifang are High–High cluster areas of urban integration, and Jining is a Low–Low cluster area. The spatial agglomeration characteristics are not significant in other cities. (3) Among the main factors affecting URI, the explanatory power of the rural population with high school or technical secondary school education or above, the area of urban construction land, and the secondary and tertiary industry GDP to the spatial pattern of URI in Shandong province are 73.58%, 62.08%, and 58.66%, respectively. As the key factors, spatial heterogeneity, such as north–south differences, southwest-to-northeast differences, and east–west differences, is evident. Nature Publishing Group UK 2022-08-22 /pmc/articles/PMC9395521/ /pubmed/35995949 http://dx.doi.org/10.1038/s41598-022-18424-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Shan, Baoyan
Zhang, Qiao
Ren, Qixin
Yu, Xinwei
Chen, Yanqiu
Spatial heterogeneity of urban–rural integration and its influencing factors in Shandong province of China
title Spatial heterogeneity of urban–rural integration and its influencing factors in Shandong province of China
title_full Spatial heterogeneity of urban–rural integration and its influencing factors in Shandong province of China
title_fullStr Spatial heterogeneity of urban–rural integration and its influencing factors in Shandong province of China
title_full_unstemmed Spatial heterogeneity of urban–rural integration and its influencing factors in Shandong province of China
title_short Spatial heterogeneity of urban–rural integration and its influencing factors in Shandong province of China
title_sort spatial heterogeneity of urban–rural integration and its influencing factors in shandong province of china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9395521/
https://www.ncbi.nlm.nih.gov/pubmed/35995949
http://dx.doi.org/10.1038/s41598-022-18424-0
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