IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i5p1759-d330004.html
   My bibliography  Save this article

Identifying Driving Forces of Built-Up Land Expansion Based on the Geographical Detector: A Case Study of Pearl River Delta Urban Agglomeration

Author

Listed:
  • Yongwei Liu

    (School of Business, Ludong University, Yantai 264025, China)

  • Xiaoshu Cao

    (Institute of Transport Geography and Spatial Planning, Shaanxi Normal University, Xi’an 710119, China
    School of Geography Science and Planning, Sun Yat-sen University, Guangzhou 510275, China)

  • Tao Li

    (Institute of Transport Geography and Spatial Planning, Shaanxi Normal University, Xi’an 710119, China)

Abstract

Understanding the driving forces behind built-up land expansion is crucial in urban planning and management. Using the Pearl River Delta urban agglomeration as research area, four landscape metrics were used to analyze landscape characteristics of urban expansion from 1990 to 2015. Spatial autocorrelation analysis was used to study the characteristics of built-up land expansion, while geographical detector was employed to identify the driving forces of urban land growth and their interactions. The results show the extent of built-up land has been increasing, the structure has become more complex, the level of fragmentation has been increasing, and the aggregation degree is in decline. The built-up landscape index shows spatial heterogeneity occurring in the core and peripheral towns of cities, as well as in the core and peripheral areas of the entire region. Also, changes in the built-up landscape index indicate increased spatial aggregation occurring in the past 25 years. Results from the geographical detector show natural, socio-economic, and transportation-related factors have substantial influence on built-up land expansion. Elevation, slope, population density, change in population density, and road network density were shown to have high influencing power. The influencing powers of slope and change in population density were also found to be different from other factors, highlighting their important role in urban development. Also, there were two types of interactions found, enhance nonlinear and enhance bivariate interactions, indicating the compounding influence of interactions between significant determinants. This study provides a new perspective and methodological approach in evaluating the driving forces behind built-up land expansion and their interactions.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:5:p:1759-:d:330004
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/5/1759/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/5/1759/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. John E. Fernández, 2007. "Resource Consumption of New Urban Construction in China," Journal of Industrial Ecology, Yale University, vol. 11(2), pages 99-115, April.
    2. 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.
    3. Qiuxia Zheng & Yaoqiu Kuang & Ningsheng Huang, 2016. "Coordinated Development between Urban Tourism Economy and Transport in the Pearl River Delta, China," Sustainability, MDPI, vol. 8(12), pages 1-15, December.
    4. J. I. Pascual & N. Lorente & Z. Song & H. Conrad & H.-P. Rust, 2003. "Selectivity in vibrationally mediated single-molecule chemistry," Nature, Nature, vol. 423(6939), pages 525-528, May.
    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. 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.
    2. 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.
    3. 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.
    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. 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.
    6. 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.
    7. 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.

    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. Chau, Nancy H. & Qin, Yu & Zhang, Weiwen, 2015. "Networked Leaders in the Shadow of the Market – A Chinese Experiment in Allocating Land Conversion Rights," Working Papers 250022, Cornell University, Department of Applied Economics and Management.
    2. David Hidalgo García & Julián Arco Díaz & Adelaida Martín Martín & Emilio Gómez Cobos, 2022. "Spatiotemporal Analysis of Urban Thermal Effects Caused by Heat Waves through Remote Sensing," Sustainability, MDPI, vol. 14(19), pages 1-24, September.
    3. Tommaso Orusa & Annalisa Viani & Enrico Borgogno-Mondino, 2024. "Earth Observation Data and Geospatial Deep Learning AI to Assign Contributions to European Municipalities Sen4MUN: An Empirical Application in Aosta Valley (NW Italy)," Land, MDPI, vol. 13(1), pages 1-21, January.
    4. Jianglong Chen & Jinlong Gao & Feng Yuan, 2016. "Growth Type and Functional Trajectories: An Empirical Study of Urban Expansion in Nanjing, China," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-18, February.
    5. Weiguo Liu & Karen C Seto, 2008. "Using the ART-MMAP Neural Network to Model and Predict Urban Growth: A Spatiotemporal Data Mining Approach," Environment and Planning B, , vol. 35(2), pages 296-317, April.
    6. M. Joseph Sirgy & Eda Gurel-Atay & Dave Webb & Muris Cicic & Melika Husic-Mehmedovic & Ahmet Ekici & Andreas Herrmann & Ibrahim Hegazy & Dong-Jin Lee & J. Johar, 2013. "Is Materialism All That Bad? Effects on Satisfaction with Material Life, Life Satisfaction, and Economic Motivation," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 110(1), pages 349-366, January.
    7. Guangjin Tian & Zhifeng Yang & Yichun Xie, 2007. "Detecting Spatiotemporal Dynamic Landscape Patterns Using Remote Sensing and the Lacunarity Index: A Case Study of Haikou City, China," Environment and Planning B, , vol. 34(3), pages 556-569, June.
    8. Taiyang Zhong & Xianjin Huang & Lifang Ye & Steffanie Scott, 2014. "The Impacts on Illegal Farmland Conversion of Adopting Remote Sensing Technology for Land Inspection in China," Sustainability, MDPI, vol. 6(7), pages 1-26, July.
    9. D'Agata, Alessia & Alaimo, Leonardo Salvatore & Cudlín, Pavel & Salvati, Luca, 2023. "Easy come, easy go: Short-term land-use dynamics vis à vis regional economic downturns," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    10. Michail Fragkias & Karen C Seto, 2007. "Modeling Urban Growth in Data-Sparse Environments: A New Approach," Environment and Planning B, , vol. 34(5), pages 858-883, October.
    11. Yan Wang & Ranran Zhao, 2024. "Coupling coordination development between eco-investment, tourism, and logistics in Anhui Province, China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    12. Chuanchuan Yuan & Li Gan & Huili Zhuo, 2022. "Coupling Mechanisms and Development Patterns of Revitalizing Intangible Cultural Heritage by Integrating Cultural Tourism: The Case of Hunan Province, China," Sustainability, MDPI, vol. 14(12), pages 1-16, June.
    13. Deng, Xiangzheng & Huang, Jikun & Rozelle, Scott & Uchida, Emi, 2008. "Growth, population and industrialization, and urban land expansion of China," Journal of Urban Economics, Elsevier, vol. 63(1), pages 96-115, January.
    14. 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.
    15. Shu, Cheng & Xie, Hualin & Jiang, Jinfa & Chen, Qianru, 2018. "Is Urban Land Development Driven by Economic Development or Fiscal Revenue Stimuli in China?," Land Use Policy, Elsevier, vol. 77(C), pages 107-115.
    16. Lei, Yayuan & Flacke, Johannes & Schwarz, Nina, 2021. "Does Urban planning affect urban growth pattern? A case study of Shenzhen, China," Land Use Policy, Elsevier, vol. 101(C).
    17. Philip ME Garboden, 2019. "Sources and Types of Big Data for Macroeconomic Forecasting," Working Papers 2019-3, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    18. Prashanti Sharma & Rajesh Bahadur Thapa & Mir Abdul Matin, 2020. "Examining forest cover change and deforestation drivers in Taunggyi District, Shan State, Myanmar," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(6), pages 5521-5538, August.
    19. Deininger, Klaus & Jin, Songqing, 2009. "Securing property rights in transition: Lessons from implementation of China's rural land contracting law," Journal of Economic Behavior & Organization, Elsevier, vol. 70(1-2), pages 22-38, May.
    20. Ragil Haryanto & Imam Buchori & Nany Yuliastuti & Ibnu Saleh & Agung Sugiri & Bagus Nuari & Nisriena Rachmi Putri, 2020. "Preparedness to Implement a Spatial Plan: The Impact of the Land Cooperative in Central Bangka Regency," Sustainability, MDPI, vol. 12(24), pages 1-19, December.

    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:jijerp:v:17:y:2020:i:5:p:1759-:d:330004. 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.