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Multidimensional Evaluation of the Quality of Rural Life Using Big Data from the Perspective of Common Prosperity

Evaluating and revealing the spatial differentiations of quality of rural life (QRL) is the basis for formulating rural revitalization planning to promote rural transformation and achieve common prosperity. Taking the Lin’an District of Hangzhou city in China, an economically developed mountainous a...

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Autores principales: Zhang, Jing, Huang, Bingbing, Chen, Xinming, Zhu, Congmou, Gan, Muye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9657861/
https://www.ncbi.nlm.nih.gov/pubmed/36361053
http://dx.doi.org/10.3390/ijerph192114166
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author Zhang, Jing
Huang, Bingbing
Chen, Xinming
Zhu, Congmou
Gan, Muye
author_facet Zhang, Jing
Huang, Bingbing
Chen, Xinming
Zhu, Congmou
Gan, Muye
author_sort Zhang, Jing
collection PubMed
description Evaluating and revealing the spatial differentiations of quality of rural life (QRL) is the basis for formulating rural revitalization planning to promote rural transformation and achieve common prosperity. Taking the Lin’an District of Hangzhou city in China, an economically developed mountainous area, as an example, this study explored the connotation of QRL from the perspective of common prosperity and constructed a QRL evaluation framework involving living, employment, consumption, and leisure aspects. Then, based on multi-sourced data of 270 administrative villages as the assessment unit, we revealed the spatial patterns of QRL and proposed optimization paths to improving QRL. The results showed that (1) differences in the spatial distribution of quality of rural living, employment, consumption, and leisure of Lin’an District were significant, presenting stepped, block clustering, irregularity, and scattered patterns, respectively. (2) The overall QRL was mainly at a low level, clustered spatially, distributed in a strip pattern, and with obvious road directionality. (3) Based on the evaluation results of QRL, we divided the 270 administrative villages into six types of improvement: livability, employment, consumption, leisure, and balanced and lagged development types. This study could provide a scientific cognitive basis for the improvement of QRL and a useful reference for rural revitalization in China.
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spelling pubmed-96578612022-11-15 Multidimensional Evaluation of the Quality of Rural Life Using Big Data from the Perspective of Common Prosperity Zhang, Jing Huang, Bingbing Chen, Xinming Zhu, Congmou Gan, Muye Int J Environ Res Public Health Article Evaluating and revealing the spatial differentiations of quality of rural life (QRL) is the basis for formulating rural revitalization planning to promote rural transformation and achieve common prosperity. Taking the Lin’an District of Hangzhou city in China, an economically developed mountainous area, as an example, this study explored the connotation of QRL from the perspective of common prosperity and constructed a QRL evaluation framework involving living, employment, consumption, and leisure aspects. Then, based on multi-sourced data of 270 administrative villages as the assessment unit, we revealed the spatial patterns of QRL and proposed optimization paths to improving QRL. The results showed that (1) differences in the spatial distribution of quality of rural living, employment, consumption, and leisure of Lin’an District were significant, presenting stepped, block clustering, irregularity, and scattered patterns, respectively. (2) The overall QRL was mainly at a low level, clustered spatially, distributed in a strip pattern, and with obvious road directionality. (3) Based on the evaluation results of QRL, we divided the 270 administrative villages into six types of improvement: livability, employment, consumption, leisure, and balanced and lagged development types. This study could provide a scientific cognitive basis for the improvement of QRL and a useful reference for rural revitalization in China. MDPI 2022-10-29 /pmc/articles/PMC9657861/ /pubmed/36361053 http://dx.doi.org/10.3390/ijerph192114166 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Jing
Huang, Bingbing
Chen, Xinming
Zhu, Congmou
Gan, Muye
Multidimensional Evaluation of the Quality of Rural Life Using Big Data from the Perspective of Common Prosperity
title Multidimensional Evaluation of the Quality of Rural Life Using Big Data from the Perspective of Common Prosperity
title_full Multidimensional Evaluation of the Quality of Rural Life Using Big Data from the Perspective of Common Prosperity
title_fullStr Multidimensional Evaluation of the Quality of Rural Life Using Big Data from the Perspective of Common Prosperity
title_full_unstemmed Multidimensional Evaluation of the Quality of Rural Life Using Big Data from the Perspective of Common Prosperity
title_short Multidimensional Evaluation of the Quality of Rural Life Using Big Data from the Perspective of Common Prosperity
title_sort multidimensional evaluation of the quality of rural life using big data from the perspective of common prosperity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9657861/
https://www.ncbi.nlm.nih.gov/pubmed/36361053
http://dx.doi.org/10.3390/ijerph192114166
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