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Analysis of Spatial and Temporal Variation and Influencing Factors of Rural Land Dependence from the Perspective of Human-Land Relationship

Author

Listed:
  • Liuna Guo

    (College of Mining Engining, North China University of Science and Technology, Tangshan 063210, China)

  • Lina Guo

    (College of Mining Engining, North China University of Science and Technology, Tangshan 063210, China
    Tangshan Key Laboratory of Remote Sensing of Resources and Environment, Tangshan 063210, China)

  • Jiaming Li

    (College of Foreign Languages, North China University of Science and Technology, Tangshan 063210, China)

  • Yanxia Zhao

    (College of Management, North China University of Science and Technology, Tangshan 063210, China)

  • Guanghui Jiang

    (School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

Abstract

Face the issues of rural youth outflow, increase of aging population, and rural decline, this research explored the spatiotemporal evolution characteristics and influencing factors of the rural human-land relationship using the quantification index of rural land dependence. The research defines the concept of rural land dependence and constructs an evaluation index system for rural land dependence. By using the entropy weight method, the research quantitatively measures the high and low levels of rural land dependence in 30 provincial administrative units in China from 2006 to 2020. Besides, the GIS spatial analysis and geodetector are used to explore and analyze the spatial-temporal pattern and influencing factors of China’s land dependence. The results show that: (1) Temporal evolution: Since 2006, the level of rural land dependence in China has shown a decreasing trend, with economic dependence > population dependence > spatial dependence in terms of partial dependence differences. (2) Spatial pattern: During the study period, there are regional differences in the spatial distribution of rural land dependence in China, with a “high in the southwest and low in the eastern coastal areas” characteristic. The distribution of high-dependence areas has changed from being concentrated to being dispersed, while the distribution of low-dependence areas has changed from being dispersed to being concentrated. (3) Influencing factors analysis: From 2006 to 2018, the number of large agricultural employees is the main influencing factor of land dependence. With the decrease of population dependence and the increase of spatial dependence indexes, as well as the influence of the social environment, the area of rural areas and the total area of the region became the main influencing factor of land dependence from 2018 to 2020. The results can provide scientific basis for deepening the research on rural land use efficiency, and also provide decision support for promoting rural sustainable development and achieving common prosperity.

Suggested Citation

  • Liuna Guo & Lina Guo & Jiaming Li & Yanxia Zhao & Guanghui Jiang, 2023. "Analysis of Spatial and Temporal Variation and Influencing Factors of Rural Land Dependence from the Perspective of Human-Land Relationship," Sustainability, MDPI, vol. 15(13), pages 1-18, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:9861-:d:1175816
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    References listed on IDEAS

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    1. Melendres, Clark N. & Lee, Ji Yong & Kim, Bongkyun & Nayga, Rodolfo M., 2022. "Increasing yield and farm income of upland farmers: The case of Panay Island Upland Sustainable Rural Development Project in the Philippines," Journal of Asian Economics, Elsevier, vol. 82(C).
    2. Marcos Carchano & Inmaculada Carrasco & Sebastián Castillo & M. Carmen García-Cortijo, 2021. "The Social Economy as a Factor of Economic Development and Resilience of Population in Rural Areas. A Study of Mediating Effects in Castilla-La Mancha (Spain)," Sustainability, MDPI, vol. 13(10), pages 1-19, May.
    3. Gema Cárdenas Alonso & Ana Nieto Masot, 2017. "Towards Rural Sustainable Development? Contributions of the EAFRD 2007–2013 in Low Demographic Density Territories: The Case of Extremadura (SW Spain)," Sustainability, MDPI, vol. 9(7), pages 1-20, July.
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    1. Yingyuan Liu & Qian Wan & Wenhui Chen, 2024. "Digital Inclusive Finance as a Catalyst for Rural Revitalization: An Empirical Analysis from the County Development Perspective in Hubei Province," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 11548-11580, September.

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