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Measurement and identification of relative poverty level of pastoral areas: an analysis based on spatial layout

Pastoral areas are the key difficulty in China’s pursuit of common prosperity and a key region for China to build the northern ecological safety barrier and to realize the Two Centenary Goals. It is of great significance to scientifically evaluate the quality of rural life (QRL), measure the relativ...

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Autores principales: Lin, Haiying, Gao, Youhan, Zhu, Tianqi, Wu, Huayuan, Hou, Pengshen, Li, Wenlong, Hou, Shuxia, Arshad, Muhammad Umer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9264307/
https://www.ncbi.nlm.nih.gov/pubmed/35802323
http://dx.doi.org/10.1007/s11356-022-21717-6
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author Lin, Haiying
Gao, Youhan
Zhu, Tianqi
Wu, Huayuan
Hou, Pengshen
Li, Wenlong
Hou, Shuxia
Arshad, Muhammad Umer
author_facet Lin, Haiying
Gao, Youhan
Zhu, Tianqi
Wu, Huayuan
Hou, Pengshen
Li, Wenlong
Hou, Shuxia
Arshad, Muhammad Umer
author_sort Lin, Haiying
collection PubMed
description Pastoral areas are the key difficulty in China’s pursuit of common prosperity and a key region for China to build the northern ecological safety barrier and to realize the Two Centenary Goals. It is of great significance to scientifically evaluate the quality of rural life (QRL), measure the relative poverty level (RPL), and identify the relatively poor areas, making it possible to dock poverty elimination with rural revitalization. Based on the socio-economic data of 18 pastoral areas in Inner Mongolia, this paper draws on spatial layout theory to evaluate QRL and measures RPL by the natural breakpoint method and then identifies the relatively poor areas in Inner Mongolia. The results show that (1) the QRLs of pastoral areas in Inner Mongolia were unbalanced and highly polarized. The mean score of QRLs was 0.2598. Eleven (61.11%) of the counties/banners had a QRL smaller than the mean score. On the spatial layout of QRLs, the western areas were stronger than the central areas. High QRL counties/banners are mainly concentrated in the western region. In the central region, the QRLs were very fragmented, falling onto all five levels. (2) The pastoral areas in Inner Mongolia differed significantly in RPL. The mean score of RPL stood at 0.3788. Nine counties/banners (50%) had an RPL greater than the mean. Contrary to the spatial layout features of QRLs, the central pastoral areas in Inner Mongolia had stronger RPLs than the eastern ones. High RPL counties/banners are mostly clustered in the central region. The spatial layout of RPLs is relatively reasonable in the central region: the RPLs decreased gradually from Dorbod Banner. (3) Nearly 45% of the pastoral areas in central and western Inner Mongolia face serious relative poverty and a high risk of returning to poverty. Eight counties/banners (45%) were identified as high composite relative poverty areas. From spatial layout, the composite relatively poor counties/banners clustered clearly, mainly in the western region. Finally, this paper establishes a warning mechanism against large-scale returning to poverty, aiming to lower composite RPL. The research results provide empirical reference and implementation path for consolidating the results of poverty eradication and facilitating rural revitalization.
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spelling pubmed-92643072022-07-08 Measurement and identification of relative poverty level of pastoral areas: an analysis based on spatial layout Lin, Haiying Gao, Youhan Zhu, Tianqi Wu, Huayuan Hou, Pengshen Li, Wenlong Hou, Shuxia Arshad, Muhammad Umer Environ Sci Pollut Res Int Research Article Pastoral areas are the key difficulty in China’s pursuit of common prosperity and a key region for China to build the northern ecological safety barrier and to realize the Two Centenary Goals. It is of great significance to scientifically evaluate the quality of rural life (QRL), measure the relative poverty level (RPL), and identify the relatively poor areas, making it possible to dock poverty elimination with rural revitalization. Based on the socio-economic data of 18 pastoral areas in Inner Mongolia, this paper draws on spatial layout theory to evaluate QRL and measures RPL by the natural breakpoint method and then identifies the relatively poor areas in Inner Mongolia. The results show that (1) the QRLs of pastoral areas in Inner Mongolia were unbalanced and highly polarized. The mean score of QRLs was 0.2598. Eleven (61.11%) of the counties/banners had a QRL smaller than the mean score. On the spatial layout of QRLs, the western areas were stronger than the central areas. High QRL counties/banners are mainly concentrated in the western region. In the central region, the QRLs were very fragmented, falling onto all five levels. (2) The pastoral areas in Inner Mongolia differed significantly in RPL. The mean score of RPL stood at 0.3788. Nine counties/banners (50%) had an RPL greater than the mean. Contrary to the spatial layout features of QRLs, the central pastoral areas in Inner Mongolia had stronger RPLs than the eastern ones. High RPL counties/banners are mostly clustered in the central region. The spatial layout of RPLs is relatively reasonable in the central region: the RPLs decreased gradually from Dorbod Banner. (3) Nearly 45% of the pastoral areas in central and western Inner Mongolia face serious relative poverty and a high risk of returning to poverty. Eight counties/banners (45%) were identified as high composite relative poverty areas. From spatial layout, the composite relatively poor counties/banners clustered clearly, mainly in the western region. Finally, this paper establishes a warning mechanism against large-scale returning to poverty, aiming to lower composite RPL. The research results provide empirical reference and implementation path for consolidating the results of poverty eradication and facilitating rural revitalization. Springer Berlin Heidelberg 2022-07-08 2022 /pmc/articles/PMC9264307/ /pubmed/35802323 http://dx.doi.org/10.1007/s11356-022-21717-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Research Article
Lin, Haiying
Gao, Youhan
Zhu, Tianqi
Wu, Huayuan
Hou, Pengshen
Li, Wenlong
Hou, Shuxia
Arshad, Muhammad Umer
Measurement and identification of relative poverty level of pastoral areas: an analysis based on spatial layout
title Measurement and identification of relative poverty level of pastoral areas: an analysis based on spatial layout
title_full Measurement and identification of relative poverty level of pastoral areas: an analysis based on spatial layout
title_fullStr Measurement and identification of relative poverty level of pastoral areas: an analysis based on spatial layout
title_full_unstemmed Measurement and identification of relative poverty level of pastoral areas: an analysis based on spatial layout
title_short Measurement and identification of relative poverty level of pastoral areas: an analysis based on spatial layout
title_sort measurement and identification of relative poverty level of pastoral areas: an analysis based on spatial layout
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9264307/
https://www.ncbi.nlm.nih.gov/pubmed/35802323
http://dx.doi.org/10.1007/s11356-022-21717-6
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