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Multi-Dimensional Analysis of Urban Growth Characteristics Integrating Remote Sensing Data: A Case Study of the Beijing-Tianjin-Hebei Region
被引:0
|作者:
Zhou, Yuan
[1
,2
,3
,4
]
Zhao, You
[5
,6
]
机构:
[1] Hebei Normal Univ, Sch Geog Sci, Shijiazhuang 050024, Peoples R China
[2] Hebei Normal Univ, Hebei Key Res Inst Humanities & Social Sci Univ, GeoComputat & Planning Ctr, Shijiazhuang 050024, Peoples R China
[3] Hebei Key Lab Environm Change & Ecol Construct, Shijiazhuang 050024, Peoples R China
[4] Hebei Technol Innovat Ctr Remote Sensing Identific, Shijiazhuang 050024, Peoples R China
[5] Macao Polytech Univ, Fac Humanities & Social Sci, Macau 999078, Peoples R China
[6] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Reg Sustainable Dev Modeling, Beijing 100101, Peoples R China
关键词:
urban growth;
horizontal expansion;
vertical expansion;
influencing mechanism;
urban-rural difference;
nighttime light;
NIGHTTIME LIGHT;
DMSP-OLS;
EXPANSION;
LAND;
PATTERNS;
CHINA;
IMPACT;
POPULATION;
EMISSIONS;
D O I:
10.3390/rs17030548
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Sustainable urban growth is an important issue in urbanization. Existing studies mainly focus on urban growth from the two-dimensional morphology perspective due to limited data. Therefore, this study aimed to construct a framework for estimating long-term time series of building volume by integrating nighttime light data, land use data, and existing building volume data. Indicators of urban horizontal expansion (UHE), urban vertical expansion (UVE), and comprehensive development intensity (CDI) were constructed to describe the spatiotemporal characteristics of the horizontal growth, vertical growth, and comprehensive intensity of the Beijing-Tianjin-Hebei (BTH) urban agglomeration from 2013 to 2023. The UHE and UVE increased from 0.44 and 0.30 to 0.50 and 0.53, respectively, indicating that BTH has simultaneously experienced horizontal growth and vertical growth and the rate of vertical growth was more significant. The UVE in urban areas and suburbs was higher and continuously increasing; in particular, the UVE in the suburbs changed from 0.35 to 0.60, showing the highest rate of increase. The most significant UHE growth was mainly concentrated in rural areas. The spatial pattern of the CDI was stable, showing a declining trend along the urban-suburb-rural gradient, and CDI growth from 2013 to 2023 was mainly concentrated in urban and surrounding areas. In terms of temporal variation, the CDI growth during 2013-2018 was significant, while it slowed after 2018 because economic development had leveled off. Economic scale, UHE, and UVE were the main positive factors. Due to the slowdown of CDI growth and population growth, economic activity intensity, population density, and improvement in the living environment showed a negative impact on CDI change. The results confirm the validity of estimating the multi-dimensional growth of regions using remote sensing data and provide a basis for differentiated spatial growth planning in urban, suburban, and rural areas.
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页数:25
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