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Spatial Pattern of the Vitality of Chinese Characteristic Towns: A Perspective from Nighttime Lights

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  • Yuqing Zhang

    (School of Geography, Liaoning Normal University, Dalian 116029, China
    Postdoctoral Station of Geography, Liaoning Normal University, Dalian 116029, China)

  • Kun Shang

    (School of Geography, Liaoning Normal University, Dalian 116029, China)

  • Zhipeng Shi

    (School of Geography, Liaoning Normal University, Dalian 116029, China)

  • Hui Wang

    (School of Geography, Liaoning Normal University, Dalian 116029, China)

  • Xueming Li

    (School of Geography, Liaoning Normal University, Dalian 116029, China
    Centre for Marine Economy and Sustainable Development Research, Liaoning Normal University, Dalian 116029, China)

Abstract

Nighttime light images are valuable indicators of regional economic development, and nighttime light data are now widely used in town monitoring and evaluation studies. Using the nighttime light data acquired through Luojia1-01 and the geographic information system spatial analysis method, this study analyzed the spatial vitality pattern of 402 characteristic towns in six geographic divisions of China. The average DN (Digital Number) value of Guzhen, having the highest vitality level, was 0.05665221, whereas that of Xin’an, having the lowest vitality level, was 0.00000186. A total of 89.5% of towns have a low level of vitality. The regional differences were significant; high vitality towns are concentrated in economically developed coastal areas, mainly in two large regions of east China and south central. The average lighting densities of the towns in east China and south central were 0.004838 and 0.003190, respectively. The lighting density of the towns in west central was low, and the vitality intensity was generally low. A spatially significant positive correlation of small-town vitality was observed, and “high–high” agglomeration was primarily distributed in the Yangtze River Delta, Pearl River Delta, and Fujian coastal areas in east and south China. The towns with high vitality intensity had similarities in their geographical location, convenient transportation conditions, and profound historical heritage or cultural accumulation along with many industrial enterprises. This research empirically demonstrates the feasibility of using the 130-m-high resolution of the nighttime lighting data of Luojia1-01 to evaluate the vitality at the town scale, and the vitality evaluation focuses on the spatial attributes of the town, which is meaningful to guide the development of the town in each region given the vast area of China and the large differences in the development of different regions.

Suggested Citation

  • Yuqing Zhang & Kun Shang & Zhipeng Shi & Hui Wang & Xueming Li, 2022. "Spatial Pattern of the Vitality of Chinese Characteristic Towns: A Perspective from Nighttime Lights," Land, MDPI, vol. 11(1), pages 1-17, January.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:1:p:85-:d:718858
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    References listed on IDEAS

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    1. HUANG,Cuiping & WU,Wei & HU,Xiying, 2018. "Development Paths of Characteristic Towns in Underdeveloped Areas in Central China—— A Case Study of Yichun, Jiangxi," Asian Agricultural Research, USA-China Science and Culture Media Corporation, vol. 10(12), December.
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    Cited by:

    1. Guiling Wang & Mengzhuo Zhang & Yimeng Liu & Li Zhou & Yuxin Xia, 2023. "The Green and Adaptable Development Paths of Provincial Characteristic Towns in Taihu Lake Basin: A Synergy Perspective on Face Value and Resilience," Sustainability, MDPI, vol. 15(9), pages 1-17, May.
    2. Hongyu Gong & Xiaozihan Wang & Zihao Wang & Ziyi Liu & Qiushan Li & Yunhan Zhang, 2022. "How Did the Built Environment Affect Urban Vibrancy? A Big Data Approach to Post-Disaster Revitalization Assessment," IJERPH, MDPI, vol. 19(19), pages 1-25, September.

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