IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i9p1673-d1226403.html
   My bibliography  Save this article

Research on Spatial–Temporal Characteristics and Driving Factors of Urban Development Intensity for Pearl River Delta Region Based on Geodetector

Author

Listed:
  • Hanguang Yu

    (School of Information Engineering, China University of Geosciences, Beijing 100083, China)

  • Dongya Liu

    (School of Information Engineering, China University of Geosciences, Beijing 100083, China)

  • Chunxiao Zhang

    (School of Information Engineering, China University of Geosciences, Beijing 100083, China)

  • Le Yu

    (Department for Earth System Science, Tsinghua University, Beijing 100084, China)

  • Ben Yang

    (School of Information Engineering, China University of Geosciences, Beijing 100083, China)

  • Shijiao Qiao

    (School of Information Engineering, China University of Geosciences, Beijing 100083, China)

  • Xiaoli Wang

    (China Land Surveying and Planning Institute, Beijing 100035, China)

Abstract

The Pearl River Delta (PRD) is one of the most dynamic economic regions in the Asia-Pacific region. At present, it still faces many problems, such as the over-exploitation of urban land and unbalanced development. Through the study of the spatial–temporal characteristics of the development intensity of the PRD region and its driving factors, the key points and difficulties of urban development can be intuitively found. In previous studies, geodetector was widely used to determine the impact of driving factors. This paper uses several different research methods, including the Moran index, the semi-variability index, hot and cold spots, etc., based on the land use data of the PRD region in 1990, 2000, 2010, and 2020 to analyze the spatial–temporal characteristics of the development intensity. Combined with the socio-economic data of the statistical yearbook, factor detection and interaction detection of the 10 driving factors of development intensity are carried out based on geodetector, and reasonable optimization suggestions are put forward for the current situation of the region. The main conclusions are as follows: (1) The overall development intensity of the PRD region shows an upward trend, showing a “core periphery” spatial pattern of high center and low periphery centered around the Pearl River estuary. (2) The spatial distribution of cold and hot spots shows agglomeration, mainly in the form of high aggregation and low aggregation. (3) The driving factors for the development intensity for the PRD region in the past 30 years mainly include population agglomeration level, industrial structure level, economic strength level, terrain slope, etc. Among them, any two factors have a stronger interaction than a single factor, and all are enhanced by two factors. The dominant factors of interaction in different periods are different.

Suggested Citation

  • Hanguang Yu & Dongya Liu & Chunxiao Zhang & Le Yu & Ben Yang & Shijiao Qiao & Xiaoli Wang, 2023. "Research on Spatial–Temporal Characteristics and Driving Factors of Urban Development Intensity for Pearl River Delta Region Based on Geodetector," Land, MDPI, vol. 12(9), pages 1-21, August.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:9:p:1673-:d:1226403
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/9/1673/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/12/9/1673/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yongwei Liu & Xiaoshu Cao & Tao Li, 2020. "Identifying Driving Forces of Built-Up Land Expansion Based on the Geographical Detector: A Case Study of Pearl River Delta Urban Agglomeration," IJERPH, MDPI, vol. 17(5), pages 1-17, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ge Shi & Jingran Zhang & Jiahang Liu & Jinghai Xu & Yu Chen & Yutong Wang, 2024. "Spatial Analysis of Lung Cancer Patients and Associated Influencing Factors from the Perspective of Urban Sustainable Development: A Case Study of Jiangsu Province, China," Sustainability, MDPI, vol. 16(22), pages 1-16, November.
    2. Yutong Wang & Jianyu Yang, 2024. "The Spatio-Temporal Development and Influencing Factors of Urban Residential Land Prices in Hebei Province, China," Land, MDPI, vol. 13(8), pages 1-16, August.
    3. Qingyi Chen & Yuting Liu & Zuolin Yao, 2024. "Spatial–Temporal Pattern Evolution and Differentiation Mechanism of Urban Dual Innovation: A Case Study of China’s Three Major Urban Agglomerations," Land, MDPI, vol. 13(9), pages 1-22, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aibin Wu & Yanxia Zhao & Yanjie Qin & Xin Liu & Huitao Shen, 2023. "Analysis of Ecological Environment Quality and Its Driving Factors in the Beijing-Tianjin-Hebei Region of China," Sustainability, MDPI, vol. 15(10), pages 1-21, May.
    2. Yaotao Xu & Peng Li & Jinjin Pan & Yi Zhang & Xiaohu Dang & Xiaoshu Cao & Junfang Cui & Zhi Yang, 2022. "Eco-Environmental Effects and Spatial Heterogeneity of “Production-Ecology-Living” Land Use Transformation: A Case Study for Ningxia, China," Sustainability, MDPI, vol. 14(15), pages 1-20, August.
    3. Yinglin Sun & Bing Liu & Guang Yang & Yongjun Du & Hejiaolong Huang & Ting Wang & Jun Wang, 2023. "Analysis of Spatiotemporal Evolution Patterns and Driving Forces of Reservoirs on the Northern Slope of the Tianshan Mountains in Xinjiang," Sustainability, MDPI, vol. 15(11), pages 1-19, May.
    4. Fengjian Ge & Guiling Tang & Mingxing Zhong & Yi Zhang & Jia Xiao & Jiangfeng Li & Fengyuan Ge, 2022. "Assessment of Ecosystem Health and Its Key Determinants in the Middle Reaches of the Yangtze River Urban Agglomeration, China," IJERPH, MDPI, vol. 19(2), pages 1-16, January.
    5. Jinmeng Lee & Xiaojun Yin & Honghui Zhu & Xin Zheng, 2023. "Geographical Detector-Based Research of Spatiotemporal Evolution and Driving Factors of Oasification and Desertification in Manas River Basin, China," Land, MDPI, vol. 12(8), pages 1-20, July.
    6. Yongwei Liu & Yao Zhang, 2024. "Responses of Ecosystem Services to Land Use/Cover Changes in Rapidly Urbanizing Areas: A Case Study of the Shandong Peninsula Urban Agglomeration," Sustainability, MDPI, vol. 16(14), pages 1-21, July.
    7. Yashon O. Ouma & Boipuso Nkwae & Phillimon Odirile & Ditiro B. Moalafhi & George Anderson & Bhagabat Parida & Jiaguo Qi, 2024. "Land-Use Change Prediction in Dam Catchment Using Logistic Regression-CA, ANN-CA and Random Forest Regression and Implications for Sustainable Land–Water Nexus," Sustainability, MDPI, vol. 16(4), pages 1-30, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:12:y:2023:i:9:p:1673-:d:1226403. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.