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The Evolution of the Urban Spatial Pattern in the Yangtze River Economic Belt: Based on Multi-Source Remote Sensing Data

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  • Yang Li

    (Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210046, China
    School of Geographic Science, Nanjing Normal University, Nanjing 210046, China)

  • Hua Shao

    (College of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China)

  • Nan Jiang

    (Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210046, China
    School of Geographic Science, Nanjing Normal University, Nanjing 210046, China)

  • Ge Shi

    (Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210046, China
    School of Geographic Science, Nanjing Normal University, Nanjing 210046, China)

  • Xin Cheng

    (College of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China)

Abstract

The development of the Yangtze River Economic Belt (YREB) is an important national regional development strategy and a strategic engineering development system. In this study, the evolution of urban spatial patterns in the YREB from 1990 to 2010 was mapped using the nighttime stable light (NSL) data, multi-temporal urban land products, and multiple sources of geographic data by using the rank-size distribution and the Gini coefficient method. Through statistical results, we found that urban land takes on the feature of “high in the east and low in the west”. The study area included cities of different development stages and sizes. The nighttime light increased in most cities from 1992 to 2010, and the rate assumed an obvious growth tendency in the three urban agglomerations in the YREB. The results revealed that the urban size distribution of the YREB is relatively dispersed, the speed of urban development is unequal, and the trend of urban size structure shows a decentralized distribution pattern that has continuously strengthened from 1990 to 2010. Affected by factors such as geographical conditions, spatial distance, and development stage, the lower reaches of the Yangtze River have developed rapidly, the upper and middle reaches have developed large cities, and a contiguous development trend is not obvious. The evolution of urban agglomerations in the region presents a variety of spatial development characteristics. Jiangsu, Zhejiang, and Shanghai have entered a phase of urban continuation, forming a more mature interregional urban agglomeration, while the YREB inland urban agglomerations are in suburbanization and multi-centered urban areas. At this stage, the conditions for the formation of transregional urban agglomerations do not yet exist, and there are many uncertainties in the boundary and spatial structure of each urban agglomeration.

Suggested Citation

  • Yang Li & Hua Shao & Nan Jiang & Ge Shi & Xin Cheng, 2018. "The Evolution of the Urban Spatial Pattern in the Yangtze River Economic Belt: Based on Multi-Source Remote Sensing Data," Sustainability, MDPI, vol. 10(8), pages 1-21, August.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:8:p:2733-:d:161695
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    References listed on IDEAS

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    1. Paolo Veneri, 2013. "On City Size Distribution: Evidence from OECD Functional Urban Areas," OECD Regional Development Working Papers 2013/27, OECD Publishing.
    2. Moura, Newton J. & Ribeiro, Marcelo B., 2006. "Zipf law for Brazilian cities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 441-448.
    3. Shi, Kaifang & Chen, Yun & Yu, Bailang & Xu, Tingbao & Chen, Zuoqi & Liu, Rui & Li, Linyi & Wu, Jianping, 2016. "Modeling spatiotemporal CO2 (carbon dioxide) emission dynamics in China from DMSP-OLS nighttime stable light data using panel data analysis," Applied Energy, Elsevier, vol. 168(C), pages 523-533.
    4. Gan, Li & Li, Dong & Song, Shunfeng, 2006. "Is the Zipf law spurious in explaining city-size distributions?," Economics Letters, Elsevier, vol. 92(2), pages 256-262, August.
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    2. Weiguang Wang & Yangyang Wang, 2023. "Regional Differences, Dynamic Evolution and Driving Factors Analysis of PM 2.5 in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    3. Yu Cao & Yucen Wang & Guoyu Li & Xiaoqian Fang, 2019. "Vegetation Response to Urban Landscape Spatial Pattern Change in the Yangtze River Delta, China," Sustainability, MDPI, vol. 12(1), pages 1-18, December.
    4. Yizhen Wu & Mingyue Jiang & Zhijian Chang & Yuanqing Li & Kaifang Shi, 2020. "Does China’s Urban Development Satisfy Zipf’s Law? A Multiscale Perspective from the NPP-VIIRS Nighttime Light Data," IJERPH, MDPI, vol. 17(4), pages 1-26, February.
    5. Xin Cheng & Hua Shao & Yang Li & Chao Shen & Peipei Liang, 2019. "Urban Land Intensive Use Evaluation Study Based on Nighttime Light—A Case Study of the Yangtze River Economic Belt," Sustainability, MDPI, vol. 11(3), pages 1-21, January.
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    7. Huimin Xu & Shougeng Hu & Xi Li, 2023. "Urban Distribution and Evolution of the Yangtze River Economic Belt from the Perspectives of Urban Area and Night-Time Light," Land, MDPI, vol. 12(2), pages 1-21, January.

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