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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-9657861 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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