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Comparative Analysis of the Factors Influencing Land Use Change for Emerging Industry and Traditional Industry: A Case Study of Shenzhen City, China

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  • Yunfei Peng

    (Shenzhen Urban Planning and Land Resource Research Center, 8009 Hongli Road, Shenzhen 518040, China)

  • Fangling Yang

    (Shenzhen Urban Planning and Land Resource Research Center, 8009 Hongli Road, Shenzhen 518040, China)

  • Lingwei Zhu

    (Shenzhen Urban Planning and Land Resource Research Center, 8009 Hongli Road, Shenzhen 518040, China)

  • Ruru Li

    (Shenzhen Urban Planning and Land Resource Research Center, 8009 Hongli Road, Shenzhen 518040, China)

  • Chao Wu

    (School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

  • Deng Chen

    (School of Architecture, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China)

Abstract

Analyzing the factors influencing emerging industry land use change is important for promoting industrial transformation and for upgrading and improving the level of intensive use of emerging industry land. In recent years, to solve the problem of land resource shortage and expansion space, Shenzhen has implemented a strategy of promoting urban development through technological innovation and has actively promoted the transformation of inefficient industrial land to emerging industry. This article introduces the development, land use types, and spatial distribution of Shenzhen’s emerging industries. Based on the logistic regression model, we analyze the differences between the factors influencing changes in land use for both emerging and traditional industry. The research results show that the distance from public roads, the distance from highways, the distance from railway freight stations, the proportion of secondary industry, and the proportion of tertiary industry are important explanatory variables for the two types of land use change. Traditional industrial land use is also affected by the land slope, the distance from ports, the population, and fixed asset investment. Emerging industry land use is also affected by the distance from the airport, the number of railway stations, the quality of the population, and innovation-driving forces. These results provide a reference for government to rationally plan emerging industry land and differentiated management of this, in order to fill the current research gap in the field of land use change, and to contribute to research revealing the mechanisms driving changes in emerging industrial land.

Suggested Citation

  • Yunfei Peng & Fangling Yang & Lingwei Zhu & Ruru Li & Chao Wu & Deng Chen, 2021. "Comparative Analysis of the Factors Influencing Land Use Change for Emerging Industry and Traditional Industry: A Case Study of Shenzhen City, China," Land, MDPI, vol. 10(6), pages 1-17, May.
  • Handle: RePEc:gam:jlands:v:10:y:2021:i:6:p:575-:d:565130
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    References listed on IDEAS

    as
    1. Jahanifar, Komeil & Amirnejad, Hamid & Mojaverian, Seyed Mojtaba & Azadi, Hossein, 2020. "Land use change drivers in the Hyrcanian Vegetation Area: Dynamic simultaneous equations system with panel data approach," Land Use Policy, Elsevier, vol. 99(C).
    2. Shenghui Zhou & Ke Wang & Shiqi Yang & Wenli Li & Yuxuan Zhang & Bin Zhang & Yiming Fu & Xiaoyan Liu & Yadi Run & Oliva Gabriel Chubwa & Guosong Zhao & Jinwei Dong & Yaoping Cui, 2020. "Warming Effort and Energy Budget Difference of Various Human Land Use Intensity: Case Study of Beijing, China," Land, MDPI, vol. 9(9), pages 1-15, August.
    3. Geng, Yong & Liu, Wei & Wu, Yuzhao, 2021. "How do zombie firms affect China’s industrial upgrading?," Economic Modelling, Elsevier, vol. 97(C), pages 79-94.
    4. Wang, Boyi & Tian, Li & Yao, Zhihao, 2018. "Institutional uncertainty, fragmented urbanization and spatial lock-in of the peri-urban area of China: A case of industrial land redevelopment in Panyu," Land Use Policy, Elsevier, vol. 72(C), pages 241-249.
    5. Pu Hao & Stan Geertman & Pieter Hooimeijer & Richard Sliuzas, 2012. "The Land-Use Diversity in Urban Villages in Shenzhen," Environment and Planning A, , vol. 44(11), pages 2742-2764, November.
    6. Chunhong Zhao & Jennifer L.R. Jensen & Russell Weaver, 2020. "Global and Local Modeling of Land Use Change in the Border Cities of Laredo, Texas, USA and Nuevo Laredo, Tamaulipas, Mexico: A Comparative Analysis," Land, MDPI, vol. 9(10), pages 1-18, September.
    7. Karen C. Seto & Robert K. Kaufmann, 2003. "Modeling the Drivers of Urban Land Use Change in the Pearl River Delta, China: Integrating Remote Sensing with Socioeconomic Data," Land Economics, University of Wisconsin Press, vol. 79(1), pages 106-121.
    8. Lingyue Li & Zhixin Qi & Shi Xian & Dong Yao, 2021. "Agricultural Land Use Change in Chongqing and the Policy Rationale behind It: A Multiscale Perspective," Land, MDPI, vol. 10(3), pages 1-18, March.
    9. Yongchun Huang & Paul Swamidass & Dheeraj A. Raju, 2016. "The nature of innovation in emerging industries in China: an exploratory study," The Journal of Technology Transfer, Springer, vol. 41(3), pages 451-468, June.
    10. Shu, Hui & Xiong, Ping-ping, 2019. "Reallocation planning of urban industrial land for structure optimization and emission reduction: A practical analysis of urban agglomeration in China’s Yangtze River Delta," Land Use Policy, Elsevier, vol. 81(C), pages 604-623.
    11. Zhou, Yang & Li, Xunhuan & Liu, Yansui, 2020. "Land use change and driving factors in rural China during the period 1995-2015," Land Use Policy, Elsevier, vol. 99(C).
    12. Yu, Junqing & Zhou, Kaile & Yang, Shanlin, 2019. "Land use efficiency and influencing factors of urban agglomerations in China," Land Use Policy, Elsevier, vol. 88(C).
    13. Wheaton, William C., 1982. "Urban residential growth under perfect foresight," Journal of Urban Economics, Elsevier, vol. 12(1), pages 1-21, July.
    14. Bo Zhang & Wei Zhou, 2021. "Spatial–Temporal Characteristics of Precipitation and Its Relationship with Land Use/Cover Change on the Qinghai-Tibet Plateau, China," Land, MDPI, vol. 10(3), pages 1-21, March.
    15. Lindsay Whitfield & Cornelia Staritz & Mike Morris, 2020. "Global Value Chains, Industrial Policy and Economic Upgrading in Ethiopia's Apparel Sector," Development and Change, International Institute of Social Studies, vol. 51(4), pages 1018-1043, July.
    16. Chen, Wei & Shen, Yue & Wang, Yanan & Wu, Qun, 2018. "How do industrial land price variations affect industrial diffusion? Evidence from a spatial analysis of China," Land Use Policy, Elsevier, vol. 71(C), pages 384-394.
    17. Capozza, Dennis R. & Helsley, Robert W., 1989. "The fundamentals of land prices and urban growth," Journal of Urban Economics, Elsevier, vol. 26(3), pages 295-306, November.
    18. Kuang, Wenhui, 2020. "National urban land-use/cover change since the beginning of the 21st century and its policy implications in China," Land Use Policy, Elsevier, vol. 97(C).
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    Cited by:

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    2. Changchun Feng & Hao Zhang & Liang Xiao & Yongpei Guo, 2022. "Land Use Change and Its Driving Factors in the Rural–Urban Fringe of Beijing: A Production–Living–Ecological Perspective," Land, MDPI, vol. 11(2), pages 1-18, February.
    3. Guoliang Xu & Xiaonan Yin & Guangdong Wu & Ning Gao, 2022. "Rethinking the Contribution of Land Element to Urban Economic Growth: Evidence from 30 Provinces in China," Land, MDPI, vol. 11(6), pages 1-16, May.
    4. Peng Wang & Yihui He & Kengcheng Zheng, 2023. "Effects of the Implementation of the Broadband China Policy (BCP) on House Prices: Evidence from a Quasi-Natural Experiment in China," Land, MDPI, vol. 12(5), pages 1-15, May.
    5. Longgao Chen & Xiaoyan Yang & Long Li & Longqian Chen & Yu Zhang, 2021. "The Natural and Socioeconomic Influences on Land-Use Intensity: Evidence from China," Land, MDPI, vol. 10(11), pages 1-25, November.

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