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Estimate of population density and diagnosis of main factors of spatial heterogeneity in the metropolitan scale, western China
We estimated the population density and quantified its characteristics using remote sensing, census data, and Geographic Information System (GIS). The interactive influence of these factors on population density was quantified based on geographic detectors to identify the differentiation mechanisms...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246348/ https://www.ncbi.nlm.nih.gov/pubmed/37292294 http://dx.doi.org/10.1016/j.heliyon.2023.e16285 |
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author | Wang, Guangjie Peng, Wenfu Zhang, Lindan |
author_facet | Wang, Guangjie Peng, Wenfu Zhang, Lindan |
author_sort | Wang, Guangjie |
collection | PubMed |
description | We estimated the population density and quantified its characteristics using remote sensing, census data, and Geographic Information System (GIS). The interactive influence of these factors on population density was quantified based on geographic detectors to identify the differentiation mechanisms in the Chengdu metropolitan area of China. We identified the key factors that contribute to population density growth. The models used to simulate population density had the highest R(2) values (>0.899). Population density tended to increase with time, with a multicentre spatial agglomeration pattern; the centre of gravity of the spatial distribution tended to move from the southeast to the northwest. Industry proportions, Normalised Difference Vegetation Index (NDVI), land use, distance to urban centers or construction land, and GDP per capita can satisfactorily explain population density changes. The combined impact of these elements on population density variation exhibited mutual and non-linear strengthening, with the mutual effect of the two elements intensifying the impact of each individual element. Our study identified the key driving forces that contribute to the differentiation of population density, which can provide valuable support for the development of effective regional and targeted population planning guidelines. |
format | Online Article Text |
id | pubmed-10246348 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-102463482023-06-08 Estimate of population density and diagnosis of main factors of spatial heterogeneity in the metropolitan scale, western China Wang, Guangjie Peng, Wenfu Zhang, Lindan Heliyon Research Article We estimated the population density and quantified its characteristics using remote sensing, census data, and Geographic Information System (GIS). The interactive influence of these factors on population density was quantified based on geographic detectors to identify the differentiation mechanisms in the Chengdu metropolitan area of China. We identified the key factors that contribute to population density growth. The models used to simulate population density had the highest R(2) values (>0.899). Population density tended to increase with time, with a multicentre spatial agglomeration pattern; the centre of gravity of the spatial distribution tended to move from the southeast to the northwest. Industry proportions, Normalised Difference Vegetation Index (NDVI), land use, distance to urban centers or construction land, and GDP per capita can satisfactorily explain population density changes. The combined impact of these elements on population density variation exhibited mutual and non-linear strengthening, with the mutual effect of the two elements intensifying the impact of each individual element. Our study identified the key driving forces that contribute to the differentiation of population density, which can provide valuable support for the development of effective regional and targeted population planning guidelines. Elsevier 2023-05-27 /pmc/articles/PMC10246348/ /pubmed/37292294 http://dx.doi.org/10.1016/j.heliyon.2023.e16285 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Wang, Guangjie Peng, Wenfu Zhang, Lindan Estimate of population density and diagnosis of main factors of spatial heterogeneity in the metropolitan scale, western China |
title | Estimate of population density and diagnosis of main factors of spatial heterogeneity in the metropolitan scale, western China |
title_full | Estimate of population density and diagnosis of main factors of spatial heterogeneity in the metropolitan scale, western China |
title_fullStr | Estimate of population density and diagnosis of main factors of spatial heterogeneity in the metropolitan scale, western China |
title_full_unstemmed | Estimate of population density and diagnosis of main factors of spatial heterogeneity in the metropolitan scale, western China |
title_short | Estimate of population density and diagnosis of main factors of spatial heterogeneity in the metropolitan scale, western China |
title_sort | estimate of population density and diagnosis of main factors of spatial heterogeneity in the metropolitan scale, western china |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246348/ https://www.ncbi.nlm.nih.gov/pubmed/37292294 http://dx.doi.org/10.1016/j.heliyon.2023.e16285 |
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