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2010 年至 2019 年中国的产业蔓延:基于城市标度律的多层次空间分析。

The Industrial Sprawl in China from 2010 to 2019: A Multi-Level Spatial Analysis Based on Urban Scaling Law.

机构信息

School of Public Administration, Central China Normal University, Wuhan 430079, China.

Department of Tourism Management, Jin Zhong University, Jinzhong 030619, China.

出版信息

Int J Environ Res Public Health. 2022 Dec 5;19(23):16255. doi: 10.3390/ijerph192316255.

DOI:10.3390/ijerph192316255
PMID:36498336
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9736417/
Abstract

Studying the spatial-temporal distribution industrial sprawl in China is important to solve industrial sprawl problems and promote urban sustainable development. This paper constructed a multi-level spatial analysis of the Chinese industrial sprawl during 2010-2019 by mainly using urban scaling law, supplemented by GIS methods. Results showed that: (1) China had obvious industrial sprawl with a growth rate of 31.79%, reaching 2762.37 km between 2010 and 2019. (2) There was a stronger industrial sprawl in large cities with a larger population according to urban scaling law, especially in the East. (3) The industrial sprawl was mainly concentrated in the cities in the Northeast, Beijing-Tianjin-Hebei region, Shandong Peninsula, Yangtze River Delta region, Pearl River Delta region, Middle Yangtze River region, Fujian Province, and some cities in the West. (4) The gravity center of industrial sprawl generally moved southwest and distributed in Hubei Province. This study provided references for improving the efficiency of industrial land use and promoting high-quality urban development.

摘要

研究中国工业扩张的时空分布对于解决工业扩张问题、促进城市可持续发展具有重要意义。本研究主要利用城市规模法则,辅以 GIS 方法,对 2010-2019 年中国工业扩张进行多层次的空间分析。结果表明:(1)中国工业扩张明显,增长率为 31.79%,2010-2019 年期间增长了 2762.37 公里。(2)根据城市规模法则,人口较多的大城市工业扩张程度更强,尤其是东部地区。(3)工业扩张主要集中在东北地区、京津冀地区、山东半岛、长三角地区、珠三角地区、长江中游地区、福建省以及西部地区的一些城市。(4)工业扩张的重力中心一般向西南移动,分布在湖北省。本研究为提高工业用地利用效率、促进高质量城市发展提供了参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/102ecad5de2b/ijerph-19-16255-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/99f94a6a1510/ijerph-19-16255-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/4758d0a382f1/ijerph-19-16255-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/a92a91f4022a/ijerph-19-16255-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/2ebfb5d4686d/ijerph-19-16255-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/7263d471a16e/ijerph-19-16255-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/102ecad5de2b/ijerph-19-16255-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/99f94a6a1510/ijerph-19-16255-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/4758d0a382f1/ijerph-19-16255-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/a92a91f4022a/ijerph-19-16255-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/2ebfb5d4686d/ijerph-19-16255-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/7263d471a16e/ijerph-19-16255-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2843/9736417/102ecad5de2b/ijerph-19-16255-g006.jpg

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本文引用的文献

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The spatial spillover effect and nonlinear relationship analysis between land resource misallocation and environmental pollution: Evidence from China.土地资源错配与环境污染的空间溢出效应及非线性关系分析——来自中国的证据。
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How do varying socio-economic factors affect the scale of land transfer? Evidence from 287 cities in China.
不同的社会经济因素如何影响土地流转规模?来自中国287个城市的证据。
Environ Sci Pollut Res Int. 2022 Jun;29(27):40865-40877. doi: 10.1007/s11356-021-18126-6. Epub 2022 Jan 27.
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Relationships between urbanization and CO2 emissions in China: An empirical analysis of population migration.中国城市化与二氧化碳排放的关系:基于人口迁移的实证分析。
PLoS One. 2021 Aug 18;16(8):e0256335. doi: 10.1371/journal.pone.0256335. eCollection 2021.
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Do carbon emissions impact the health of residents? Considering China's industrialization and urbanization.碳排放会影响居民的健康吗?考虑到中国的工业化和城市化。
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