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Spatio-Temporal Evolution and Driving Factors of Rural Settlements in Low Hilly Region—A Case Study of 17 Cities in Hubei Province, China
With the rapid development of the social economy, factors of social and economic development in China’s rural areas have been continuously reorganized, and the pattern and distribution of rural residential areas have undergone significant changes. In rural areas, there have been many peculiar phenom...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7967727/ https://www.ncbi.nlm.nih.gov/pubmed/33804475 http://dx.doi.org/10.3390/ijerph18052387 |
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author | Tan, Shukui Zhang, Maomao Wang, Ao Ni, Qianlin |
author_facet | Tan, Shukui Zhang, Maomao Wang, Ao Ni, Qianlin |
author_sort | Tan, Shukui |
collection | PubMed |
description | With the rapid development of the social economy, factors of social and economic development in China’s rural areas have been continuously reorganized, and the pattern and distribution of rural residential areas have undergone significant changes. In rural areas, there have been many peculiar phenomena of “reducing people but not reducing land in rural areas, which has caused tremendous pressure on land resource protection. We used geographic detectors and a geographically temporally weighted regression model (GTWR) to explore the rural settlements’ evolution and driving mechanism in Hubei Province from 1990 to 2015. The results show that the kernel density of rural settlements decreased from 1.62 villages/km(2) in 1990 to 1.60 villages/km(2) in 2015. The scale of rural residential patches has obvious regional differentiation characteristics. From southeast to northwest, there is a wave-like distribution structure of “high-low-high-low-high”, and the clustering characteristics of “cold and hot spots” are strengthened with time. Based on GTWR analysis, the total rural population, total power of agricultural machinery, and rural electricity consumption have promoted the expansion of rural settlements, with the regression coefficients 0.096, 0.484, and 0.878, respectively. Cultivated land, agricultural output value, and rural labor force have negative impacts on the expansion, the regression coefficients of the village were −0.584, −0.510, and −0.109, respectively. |
format | Online Article Text |
id | pubmed-7967727 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79677272021-03-18 Spatio-Temporal Evolution and Driving Factors of Rural Settlements in Low Hilly Region—A Case Study of 17 Cities in Hubei Province, China Tan, Shukui Zhang, Maomao Wang, Ao Ni, Qianlin Int J Environ Res Public Health Article With the rapid development of the social economy, factors of social and economic development in China’s rural areas have been continuously reorganized, and the pattern and distribution of rural residential areas have undergone significant changes. In rural areas, there have been many peculiar phenomena of “reducing people but not reducing land in rural areas, which has caused tremendous pressure on land resource protection. We used geographic detectors and a geographically temporally weighted regression model (GTWR) to explore the rural settlements’ evolution and driving mechanism in Hubei Province from 1990 to 2015. The results show that the kernel density of rural settlements decreased from 1.62 villages/km(2) in 1990 to 1.60 villages/km(2) in 2015. The scale of rural residential patches has obvious regional differentiation characteristics. From southeast to northwest, there is a wave-like distribution structure of “high-low-high-low-high”, and the clustering characteristics of “cold and hot spots” are strengthened with time. Based on GTWR analysis, the total rural population, total power of agricultural machinery, and rural electricity consumption have promoted the expansion of rural settlements, with the regression coefficients 0.096, 0.484, and 0.878, respectively. Cultivated land, agricultural output value, and rural labor force have negative impacts on the expansion, the regression coefficients of the village were −0.584, −0.510, and −0.109, respectively. MDPI 2021-03-01 /pmc/articles/PMC7967727/ /pubmed/33804475 http://dx.doi.org/10.3390/ijerph18052387 Text en © 2021 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tan, Shukui Zhang, Maomao Wang, Ao Ni, Qianlin Spatio-Temporal Evolution and Driving Factors of Rural Settlements in Low Hilly Region—A Case Study of 17 Cities in Hubei Province, China |
title | Spatio-Temporal Evolution and Driving Factors of Rural Settlements in Low Hilly Region—A Case Study of 17 Cities in Hubei Province, China |
title_full | Spatio-Temporal Evolution and Driving Factors of Rural Settlements in Low Hilly Region—A Case Study of 17 Cities in Hubei Province, China |
title_fullStr | Spatio-Temporal Evolution and Driving Factors of Rural Settlements in Low Hilly Region—A Case Study of 17 Cities in Hubei Province, China |
title_full_unstemmed | Spatio-Temporal Evolution and Driving Factors of Rural Settlements in Low Hilly Region—A Case Study of 17 Cities in Hubei Province, China |
title_short | Spatio-Temporal Evolution and Driving Factors of Rural Settlements in Low Hilly Region—A Case Study of 17 Cities in Hubei Province, China |
title_sort | spatio-temporal evolution and driving factors of rural settlements in low hilly region—a case study of 17 cities in hubei province, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7967727/ https://www.ncbi.nlm.nih.gov/pubmed/33804475 http://dx.doi.org/10.3390/ijerph18052387 |
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