Spatio-Temporal Evolution and Drivers of High-Quality Utilization of Urban Land in Chinese Cities
被引:0
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作者:
Liu, Jinhua
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机构:
Cent China Normal Univ, Sch Publ Adm, Wuhan 430079, Peoples R China
Cent China Normal Univ, Inst Nat Resource Governance, Wuhan 430079, Peoples R ChinaCent China Normal Univ, Sch Publ Adm, Wuhan 430079, Peoples R China
Liu, Jinhua
[1
,2
]
Huang, Xiaozhou
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机构:
Hubei Univ Econ, Sch Stat & Math, Wuhan 430205, Peoples R ChinaCent China Normal Univ, Sch Publ Adm, Wuhan 430079, Peoples R China
Huang, Xiaozhou
[3
]
机构:
[1] Cent China Normal Univ, Sch Publ Adm, Wuhan 430079, Peoples R China
[2] Cent China Normal Univ, Inst Nat Resource Governance, Wuhan 430079, Peoples R China
[3] Hubei Univ Econ, Sch Stat & Math, Wuhan 430205, Peoples R China
urban land use;
high-quality development;
spatio-temporal evolution;
driving factors;
D O I:
10.3390/land13071077
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
High-quality utilization of urban land (HUUL) is essential for optimizing urban land use and promoting high-quality development. Previous research has mainly focused on examining urban land use efficiency, neglecting the connection between urban land use and high-quality development. This study reveals the intrinsic association mechanism between high-quality development and urban land use, which can provide comprehensive theoretical and empirical support for high-quality land use and high-quality urban development. This study constructed an evaluation system for HUUL that comprehensively adopted the entropy method, kernel density estimation, and the geodetector model to analyze the spatio-temporal evolution and driving factors of the HUUL levels of 284 Chinese cities from 2006 to 2020. The measurement results showed that during 2006-2020, the HUUL level showed an apparent upward trend, and the eastern region > the central region > the overall region > the western region > the northeast region. From the kernel density map, there was a noticeable trend of varying degrees of increase in the difference of the main peak position of the HUUL level among cities in all regions except the west. Furthermore, some cities in the eastern and western regions had significantly higher HUUL levels than the others. According to the results of the factor analysis, it is evident that innovative use and open use are the internal primary factors that drive the enhancement of the HUUL level. Moreover, the level of economic development is the external primary factor that facilitates the improvement in HUUL level.
机构:
Department of Land Management,College of Economics and Administration,Jilin Agricultural UniversityDepartment of Land Management,College of Economics and Administration,Jilin Agricultural University
Qie Ruiqing
Li Min
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机构:
Department of Land Management,College of Economics and Administration,Jilin Agricultural UniversityDepartment of Land Management,College of Economics and Administration,Jilin Agricultural University
机构:
Cent South Univ, Business Sch, Changsha, Peoples R ChinaCent South Univ, Business Sch, Changsha, Peoples R China
Hong, Kai-rong
Qiu, Lin-shu
论文数: 0引用数: 0
h-index: 0
机构:
Cent South Univ, Business Sch, Changsha, Peoples R ChinaCent South Univ, Business Sch, Changsha, Peoples R China
Qiu, Lin-shu
Yang, Dong-xiao
论文数: 0引用数: 0
h-index: 0
机构:
Hunan Univ, Sch Econom & Trade, Changsha, Peoples R ChinaCent South Univ, Business Sch, Changsha, Peoples R China
Yang, Dong-xiao
Jiang, Minxing
论文数: 0引用数: 0
h-index: 0
机构:
Nanjing Univ Informat Sci & Technol, Sch Business, Nanjing, Peoples R China
Nanjing Univ Informat Sci & Technol, Dev Inst Jiangbei New Area, Nanjing, Peoples R ChinaCent South Univ, Business Sch, Changsha, Peoples R China
机构:
Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China
Collaborat Innovat Ctr Geospatial Technol, Wuhan 430079, Peoples R ChinaWuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China
Qin, Kun
Xu, Yuanquan
论文数: 0引用数: 0
h-index: 0
机构:
Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R ChinaWuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China
Xu, Yuanquan
Kang, Chaogui
论文数: 0引用数: 0
h-index: 0
机构:
Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China
NYU, Ctr Urban Sci Progress, Brooklyn, NY 11201 USAWuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China
Kang, Chaogui
Sobolevsky, Stanislav
论文数: 0引用数: 0
h-index: 0
机构:
NYU, Ctr Urban Sci Progress, Brooklyn, NY 11201 USAWuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China
Sobolevsky, Stanislav
Kwan, Mei-Po
论文数: 0引用数: 0
h-index: 0
机构:
Chinese Univ Hong Kong, Dept Geog & Resource Management, Shatin, Hong Kong, Peoples R China
Chinese Univ Hong Kong, Inst Space & Earth Informat Sci, Shatin, Hong Kong, Peoples R China
Univ Utrecht, Dept Human Geog & Spatial Planning, NL-3584 CB Utrecht, NetherlandsWuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China
机构:
Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
Chinese Acad Sci, Nanjing Inst Geog & Limnol, Key Lab Watershed Geog Sci, Nanjing 210008, Peoples R ChinaHohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
Cui, Yuanzheng
Zha, Hui
论文数: 0引用数: 0
h-index: 0
机构:
Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R ChinaHohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
Zha, Hui
Dang, Yunxiao
论文数: 0引用数: 0
h-index: 0
机构:
Zhejiang Univ Finance & Econ, Inst Land & Urban Rural Dev, Hangzhou 310018, Peoples R ChinaHohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
Dang, Yunxiao
Qiu, Lefeng
论文数: 0引用数: 0
h-index: 0
机构:
Zhejiang Univ Finance & Econ, Inst Land & Urban Rural Dev, Hangzhou 310018, Peoples R ChinaHohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
Qiu, Lefeng
He, Qingqing
论文数: 0引用数: 0
h-index: 0
机构:
Wuhan Univ Technol, Sch Resources & Environm Engn, Wuhan 430070, Peoples R ChinaHohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
He, Qingqing
Jiang, Lei
论文数: 0引用数: 0
h-index: 0
机构:
Guangzhou Univ, Sch Geog & Remote Sensing, Guangzhou 510006, Peoples R ChinaHohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China