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Spatiotemporal Evolution and Driving Factors of Land Development: Evidence from Shandong Province, China

Author

Listed:
  • Chuansong Zhao

    (School of Economics, Shandong University of Finance and Economics, Jinan 250014, China)

  • Ran Geng

    (School of Business, Shandong Normal University, Jinan 250358, China)

  • Jianxu Liu

    (School of Economics, Shandong University of Finance and Economics, Jinan 250014, China)

  • Liuying Peng

    (School of Economics, Shandong University of Finance and Economics, Jinan 250014, China)

  • Woraphon Yamaka

    (Faculty of Economics, Chiang Mai University, Chiang Mai 50200, Thailand)

Abstract

As populations and economies have grown rapidly, questions of land development and use have intensified. It has become a major global concern to achieve sustainable land use practices. This study reveals evolution of the spatiotemporal pattern of land development intensity of counties in Shandong Province by introducing a land development intensity measurement model combined with three-dimensional trend surface and spatial autocorrelation analyses. Geodetector and geographically weighted regression models were employed to demonstrate the interplay and spatiotemporal heterogeneity between development intensity and drivers. The empirical results show that the value of land development intensity of counties in Shandong Province shows a general growth trend, with the number of counties with higher values gradually increasing and the number of counties with lower values gradually decreasing. We also found that the spatial heterogeneity of land development intensity across counties in Shandong Province is significant, and the spatial distribution pattern is basically consistent with the “one group, two centers and three circles” strategy proposed by the Shandong Provincial Government. There is also a positive spatial correlation and clustering effect of land development intensity of counties in Shandong Province. High (low) value clusters are concentrated in core hot (cold) counties, driving some of the surrounding counties towards radial development. The alteration in the intensity of county land development is a complex occurrence that is shaped by numerous factors. Among these, GDP per capita and population density have the primary influence on land development of counties in Shandong Province. To achieve coordinated regional social, economic, and environmental benefits, land development within the county should adhere to the principle of adapting to local conditions and implement differentiated development strategies according to different development intensities.

Suggested Citation

  • Chuansong Zhao & Ran Geng & Jianxu Liu & Liuying Peng & Woraphon Yamaka, 2023. "Spatiotemporal Evolution and Driving Factors of Land Development: Evidence from Shandong Province, China," Sustainability, MDPI, vol. 15(20), pages 1-21, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:20:p:15069-:d:1263337
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    References listed on IDEAS

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    1. Han Huang & Yang Zhou & Mingjie Qian & Zhaoqi Zeng, 2021. "Land Use Transition and Driving Forces in Chinese Loess Plateau: A Case Study from Pu County, Shanxi Province," Land, MDPI, vol. 10(1), pages 1-15, January.
    2. Chengri Ding & Erik Lichtenberg, 2011. "Land And Urban Economic Growth In China," Journal of Regional Science, Wiley Blackwell, vol. 51(2), pages 299-317, May.
    3. Wang, Liye & Zhang, Siyu & Tang, Lanping & Lu, Yanchi & Liu, Yanfang & Liu, Yaolin, 2022. "Optimizing distribution of urban land on the basis of urban land use intensity at prefectural city scale in mainland China," Land Use Policy, Elsevier, vol. 115(C).
    4. Hongtao Jiang & Jian Yin & Yuanhong Qiu & Bin Zhang & Yi Ding & Ruici Xia, 2022. "Industrial Carbon Emission Efficiency of Cities in the Pearl River Basin: Spatiotemporal Dynamics and Driving Forces," Land, MDPI, vol. 11(8), pages 1-22, July.
    5. Zhou, Yang & Li, Yamei & Xu, Chenchen, 2020. "Land consolidation and rural revitalization in China: Mechanisms and paths," Land Use Policy, Elsevier, vol. 91(C).
    6. Cao, Rui-fen & Zhang, An-lu & Cai, Yin-ying & Xie, Xiang-xiang, 2020. "How imbalanced land development affects local fiscal condition? A case study of Hubei Province, China," Land Use Policy, Elsevier, vol. 99(C).
    7. Wenhai Xie & Wanfu Jin & Kairui Chen & Jilin Wu & Chunshan Zhou, 2019. "Land Use Transition and Its Influencing Factors in Poverty-Stricken Mountainous Areas of Sangzhi County, China," Sustainability, MDPI, vol. 11(18), pages 1-19, September.
    8. Weiping Zhang & Peiji Shi & Huali Tong, 2022. "Research on Construction Land Use Benefit and the Coupling Coordination Relationship Based on a Three-Dimensional Frame Model—A Case Study in the Lanzhou-Xining Urban Agglomeration," Land, MDPI, vol. 11(4), pages 1-16, March.
    9. Cao, Yu & Zhang, Xiaoling & Zhang, Xukun & Li, Heng, 2020. "The incremental construction land differentiated management framework: the perspective of land quota trading in China," Land Use Policy, Elsevier, vol. 96(C).
    10. Nazneen Ferdous & Chandra Bhat, 2013. "A spatial panel ordered-response model with application to the analysis of urban land-use development intensity patterns," Journal of Geographical Systems, Springer, vol. 15(1), pages 1-29, January.
    11. Xu, Feng & Wang, Zhanqi & Chi, Guangqing & Zhang, Zhexi, 2020. "The impacts of population and agglomeration development on land use intensity: New evidence behind urbanization in China," Land Use Policy, Elsevier, vol. 95(C).
    12. Li, Yurui & Li, Yi & Karácsonyi, Dávid & Liu, Zhengjia & Wang, Yongsheng & Wang, Jieyong, 2020. "Spatio-temporal pattern and driving forces of construction land change in a poverty-stricken county of China and implications for poverty-alleviation-oriented land use policies," Land Use Policy, Elsevier, vol. 91(C).
    13. O’Brien, Philip & Lord, Alex & Dembski, Sebastian, 2020. "How do planners manage risk in alternative land development models? An institutional analysis of land development in the Netherlands," Land Use Policy, Elsevier, vol. 91(C).
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