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Remote Sensing for Natural Resources    2024, Vol. 36 Issue (1) : 189-199     DOI: 10.6046/zrzyyg.2022410
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Analyzing the spatio-temporal evolution of urban expansion in the Central Plains urban agglomeration and its driving force based on DMSP/OLS and NPP/VIIRS nighttime light images
HU Miaomiao1,2(), YAN Qingwu2,3(), LI Jianhui1
1. Faculty of Surveying and Mapping Engineering, Yellow River Conservancy Technical Institute, Kaifeng 475004, China
2. Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, China
3. School of Public Policy & Management, China University of Mining and Technology, Xuzhou 221116, China
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Abstract  

Discerning the spatial pattern and driving mechanism of urban expansion will contribute to the sustainable development of the Central Plains urban agglomeration (CPUA). Based on the DMSP/OLS and NPP/VIIRS nighttime light images, this study extracted the built-up area of the CPUA from 1993 to 2018 through statistical data comparison. Furthermore, this study delved into the spatial-temporal evolutionary characteristics of the urban expansion in this period on scales of the entire urban agglomeration and prefecture-level cities. Accordingly, this study investigated the driving force behind the spatial-temporal expansion using a driving force model. The results show that: ① In terms of the spatial evolution, with Zhengzhou as the center and the northeast to southwest as the reference direction, the built-up areas and expansion scales of cities in the CPUA were generally large in the central part but small on both sides. With 2010 as the point of division, the expansion type shifted from edge expansion to exclave expansion, and the expansion mode transitioned from planar expansion to multi-center dotted expansion and linear expansion along main traffic routes; ② Regarding the temporal evolution, different cities exhibited significantly distinct expansion area, speed, and intensity. The expansion speed and intensity were both positive, roughly manifesting W-shaped fluctuations. The center of the built-up areas shifted from southwest to northeast, then northeast, then west, then northwest, and finally southeast, wandering between Zhengzhou and Kaifeng cities; ③ The main driving force behind the urban expansion resulting from economic factors, followed by social, transportation, and environmental factors. The top five driving force indicators affecting the urban expansion comprised general public budget revenue, GDP, actually utilized foreign capital, education expenditure, and population density.

Keywords urban expansion      spatio-temporal evolution      driving force      DMSP/OLS      NPP/VIIRS      Central Plains urban agglomeration     
ZTFLH:  TP79  
  F293.2  
Issue Date: 13 March 2024
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Miaomiao HU
Qingwu YAN
Jianhui LI
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Miaomiao HU,Qingwu YAN,Jianhui LI. Analyzing the spatio-temporal evolution of urban expansion in the Central Plains urban agglomeration and its driving force based on DMSP/OLS and NPP/VIIRS nighttime light images[J]. Remote Sensing for Natural Resources, 2024, 36(1): 189-199.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2022410     OR     https://www.gtzyyg.com/EN/Y2024/V36/I1/189
Fig.1  Schematic diagram of Central Plains urban agglomeration
Fig.2  TDN and TLP of the nighttime light before and after correction
Fig.3  Spatial evolution of Central Plains urban agglomeration in built-up range and area
Fig.4  Types of built-up area expansion in the Central Plains urban agglomeration
Fig.5  Statistics on the expansion types of built-up areas in the Zhongyuan urban agglomeration
Fig.6  Expansion scale of Central Plains urban agglomeration as a whole and sub cities
Fig.7  Standard deviation ellipse and its center of gravity change in Central Plains urban agglomeration
Fig.8  Hotspot analysis results
驱动因素 驱动指标
经济因素 GDP(X1)
一般预算收入(X2)
实际利用外资额(X3)
固定资产投资(X4)
第二产业占比(X5)
第三产业占比(X6)
社会因素 年末总人口(X7)
人口密度(X8)
教育支出(X9)
交通因素 客运量(X10)
环境因素 建成区绿化覆盖率(X11)
Tab.1  Selection of urban expansion driving forces and corresponding indicators
驱动力因素 灰色关联度
一般公共预算收入(X2) 0.92
GDP(X1) 0.90
实际利用外资额(X3) 0.89
教育支出(X9) 0.88
人口密度(X8) 0.84
年末总人口(X7) 0.83
客运量(X10) 0.81
第二产业占比(X5) 0.80
第三产业占比(X6) 0.76
固定资产投资(X4) 0.70
建成区绿化覆盖率(X11) 0.60
Tab.2  Grey relational analysis results of urban expansion driving forces
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