IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i3p271-d1342845.html
   My bibliography  Save this article

Identifying Land Use Functions in Five New First-Tier Cities Based on Multi-Source Big Data

Author

Listed:
  • Wangmin Yang

    (College of Resources, Sichuan Agricultural University, Chengdu 611130, China)

  • Yang Ye

    (College of Resources, Sichuan Agricultural University, Chengdu 611130, China)

  • Bowei Fan

    (College of Resources, Sichuan Agricultural University, Chengdu 611130, China)

  • Shuang Liu

    (Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China)

  • Jingwen Xu

    (College of Resources, Sichuan Agricultural University, Chengdu 611130, China)

Abstract

With the continuous development of big data technology, semantic-rich multi-source big data provides broader prospects for the research of urban land use function recognition. This study relied on POI data and OSM data to select the central urban areas of five new first-tier cities as the study areas. The TF-IDF algorithm was used to identify the land use functional layout of the study area and establish a confusion matrix for accuracy verification. The results show that: (1) The common feature of these five cities is that the total number and area of land parcels for residential land, commercial service land, public management and service land, and green space and open space land all account for over 90%. (2) The Kappa coefficients were all in the range [0.61, 0.80], indicating a high consistency of accuracy evaluation. (3) Chengdu and Tianjin have the highest land use function mixing degree, followed by Xi‘an, Nanjing, and Hangzhou. (4) Among the five new first-tier cities, Hangzhou and Nanjing have the highest similarity in land use function structure layout. This study attempts to reveal the current land use situation of five cities, which will provide a reference for urban development planning and management.

Suggested Citation

  • Wangmin Yang & Yang Ye & Bowei Fan & Shuang Liu & Jingwen Xu, 2024. "Identifying Land Use Functions in Five New First-Tier Cities Based on Multi-Source Big Data," Land, MDPI, vol. 13(3), pages 1-22, February.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:3:p:271-:d:1342845
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/3/271/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/13/3/271/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tianle Li & Xinqi Zheng & Chunxiao Zhang & Ruiguo Wang & Jiayu Liu, 2022. "Mining Spatial Correlation Patterns of the Urban Functional Areas in Urban Agglomeration: A Case Study of Four Typical Urban Agglomerations in China," Land, MDPI, vol. 11(6), pages 1-18, June.
    2. Krause, Cory M. & Zhang, Lei, 2019. "Short-term travel behavior prediction with GPS, land use, and point of interest data," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 349-361.
    Full references (including those not matched with items on IDEAS)

    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. Chen, Enhui & Stathopoulos, Amanda & Nie, Yu (Marco), 2022. "Transfer station choice in a multimodal transit system: An empirical study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 337-355.
    2. Sun, Lu & Liu, Xinmin, 2023. "Mining of interactions between travel demand and land use mixture using multi-source data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    3. Lu, Zhong-Wen & Xu, Yuan-Hao & Chen, Jie & Hu, Mao-Bin, 2023. "Investigation of traffic-driven epidemic spreading by taxi trip data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    4. Felipe Lagos & Sebastián Moreno & Wilfredo F. Yushimito & Tomás Brstilo, 2024. "Urban Origin–Destination Travel Time Estimation Using K-Nearest-Neighbor-Based Methods," Mathematics, MDPI, vol. 12(8), pages 1-18, April.
    5. Liangliang Zhou & Yishao Shi & Mengqiu Xie, 2024. "Urban Complexity and the Dynamic Evolution of Urban Land Functions in Yiwu City: A Micro-Analysis with Multi-Source Big Data," Land, MDPI, vol. 13(3), pages 1-28, March.
    6. Gavin Yeo & Shiau Hong Lim & Laura Wynter & Hifaz Hassan, 2019. "MPA-IBM Project SAFER: Sense-Making Analytics for Maritime Event Recognition," Interfaces, INFORMS, vol. 49(4), pages 269-280, July.
    7. Zhaoxian Su & Yang Yang & Yun Wang & Pan Zhang & Xin Luo, 2023. "Study on Spatiotemporal Evolution Features and Affecting Factors of Collaborative Governance of Pollution Reduction and Carbon Abatement in Urban Agglomerations of the Yellow River Basin," IJERPH, MDPI, vol. 20(5), pages 1-20, February.
    8. Qinghai Guo & Zhichao He & Dawei Li & Marcin Spyra, 2022. "Analysis of Spatial Patterns and Socioeconomic Activities of Urbanized Rural Areas in Fujian Province, China," Land, MDPI, vol. 11(7), pages 1-14, June.

    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:13:y:2024:i:3:p:271-:d:1342845. 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.