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Research on the Spatial Distribution Pattern and Influencing Factors of China’s Antipoverty (Pro-Poor Tourism) on GIS

Author

Listed:
  • Qing Yang
  • Fengtai Zhang
  • Youzhi An
  • Changcheng Sun
  • Jianfeng Wu
  • Yue Zhang
  • Zhen Wei
  • Jose Luis Calvo-Rolle

Abstract

Eliminating poverty is the common mission of all mankind, and it is also an important task faced by many countries. Pro-poor tourism villages are an active attempt by China to use rural tourism to escape poverty. This paper aims to provide theoretical support for consolidating the results of poverty alleviation and achieving comprehensive poverty alleviation and to provide a scientific basis for policy formulation by using GIS spatial analysis to study the spatial distribution characteristics and influencing factors of 22,651 pro-poor tourism villages in China. The findings revealed that the spatial distribution of pro-poor tourism villages is roughly divided by the Hu line. Pro-poor tourism villages show an uneven agglomeration pattern and present a spatial pattern of dense southeast and sparse northwest with six high-density core areas, among which some cities in the southwest are H-H agglomeration areas. Specifically, topography, annual rainfall, endowment of tourism resources, location transportation, and policy orientation are important factors affecting the spatial distribution of pro-poor tourism villages.

Suggested Citation

  • Qing Yang & Fengtai Zhang & Youzhi An & Changcheng Sun & Jianfeng Wu & Yue Zhang & Zhen Wei & Jose Luis Calvo-Rolle, 2021. "Research on the Spatial Distribution Pattern and Influencing Factors of China’s Antipoverty (Pro-Poor Tourism) on GIS," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-11, March.
    • Handle: RePEc:hin:jnddns:6682498
    DOI: 10.1155/2021/6682498
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    Cited by:

    1. Xueyang Wang & Xiumei Sun & Haotian Zhang & Chaokai Xue, 2022. "Digital Economy Development and Urban Green Innovation CA-Pability: Based on Panel Data of 274 Prefecture-Level Cities in China," Sustainability, MDPI, vol. 14(5), pages 1-21, March.
    2. Yaqiao Xu & Jiayi Hu & Liusan Wu, 2023. "Efficiency Evaluation of China’s Provincial Digital Economy Based on a DEA Cross-Efficiency Model," Mathematics, MDPI, vol. 11(13), pages 1-11, July.
    3. Yuzhen Li & Guofang Gong & Fengtai Zhang & Lei Gao & Yuedong Xiao & Xingyu Yang & Pengzhen Yu, 2022. "Network Structure Features and Influencing Factors of Tourism Flow in Rural Areas: Evidence from China," Sustainability, MDPI, vol. 14(15), pages 1-23, August.
    4. Qi Wen & Caiting Shen & Siyou Xia & Yongsheng Wang, 2022. "Analysis of spatiotemporal variations and effects of regional functions in rural China," Growth and Change, Wiley Blackwell, vol. 53(3), pages 1414-1435, September.
    5. Muhammad Imran & Xiangyang Liu & Rongyu Wang & Shah Saud & Yun Zhao & Muhammad Jalal Khan, 2022. "The Influence of Digital Economy and Society Index on Sustainable Development Indicators: The Case of European Union," Sustainability, MDPI, vol. 14(18), pages 1-16, September.

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