IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i9p1379-d895297.html
   My bibliography  Save this article

The Impact of Urbanization on Extreme Climate Indices in the Yangtze River Economic Belt, China

Author

Listed:
  • Wentao Yang

    (National-Local Joint Engineering Laboratory of Geospatial Information Technology, Hunan University of Science and Technology, Xiangtan 411100, China
    Department of Geographical Information Science, Hunan University of Science and Technology, Xiangtan 411100, China)

  • Yining Yan

    (National-Local Joint Engineering Laboratory of Geospatial Information Technology, Hunan University of Science and Technology, Xiangtan 411100, China
    Department of Geographical Information Science, Hunan University of Science and Technology, Xiangtan 411100, China)

  • Zhibin Lin

    (Department of Geographical Information Science, Hunan University of Science and Technology, Xiangtan 411100, China)

  • Yijiang Zhao

    (Department of Computer Science, Hunan University of Science and Technology, Xiangtan 411100, China)

  • Chaokui Li

    (National-Local Joint Engineering Laboratory of Geospatial Information Technology, Hunan University of Science and Technology, Xiangtan 411100, China
    Department of Geographical Information Science, Hunan University of Science and Technology, Xiangtan 411100, China)

  • Xinchang Zhang

    (Department of Geographical Information Science, Guangzhou University, Guangzhou 510006, China)

  • Liang Shan

    (Guangzhou Zengdian Institute of Science and Technology, Guangzhou 511300, China
    Department of Business Management, Central South University, Changsha 410083, China)

Abstract

Urbanization has been proven to be a critical factor in modifying local or regional climate characteristics. This research aims to examine the impact of urbanization on extreme climate indices in the Yangtze River Economic Belt (YREB), China, by using meteorological observation data from 2000 to 2019. Three main steps are involved. First, a clustered threshold method based on remote-sensing nighttime light data is used to extract urban built-up areas, and urban and rural meteorological stations can be identified based on the boundary of urban built-up areas. Nonparametric statistical tests, namely, the Mann–Kendall test and Sen’s slope, are then applied to measure the trend characteristics of extreme climate indices. Finally, the urbanization contribution rate is employed to quantify the impact of urbanization on extreme climate indices. The results indicate that urbanization has a more serious impact on extreme temperature indices than on extreme precipitation indices in the YREB. For extreme temperature indices, urbanization generally causes more (less) frequent occurrence of warm (cold) events. The impact of urbanization on different extreme temperature indices has heterogeneous characteristics, including the difference in contamination levels and spatial variation of the impacted cities. For extreme precipitation indices, only a few cities impacted by urbanization are detected, but among these cities, urbanization contributes to increasing the trend of all indices.

Suggested Citation

  • Wentao Yang & Yining Yan & Zhibin Lin & Yijiang Zhao & Chaokui Li & Xinchang Zhang & Liang Shan, 2022. "The Impact of Urbanization on Extreme Climate Indices in the Yangtze River Economic Belt, China," Land, MDPI, vol. 11(9), pages 1-16, August.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:9:p:1379-:d:895297
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/9/1379/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/9/1379/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jin-Ming Feng & Yong-Li Wang & Zhu-Guo Ma, 2015. "Long-term simulation of large-scale urbanization effect on the East Asian monsoon," Climatic Change, Springer, vol. 129(3), pages 511-523, April.
    2. Guangxun Shi & Peng Ye, 2021. "Assessment on Temporal and Spatial Variation Analysis of Extreme Temperature Indices: A Case Study of the Yangtze River Basin," IJERPH, MDPI, vol. 18(20), pages 1-21, October.
    3. Junliang Qiu & Xiankun Yang & Bowen Cao & Zhilong Chen & Yuxuan Li, 2020. "Effects of Urbanization on Regional Extreme-Temperature Changes in China, 1960–2016," Sustainability, MDPI, vol. 12(16), pages 1-29, August.
    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. Mikio Ishiwatari & Daisuke Sasaki, 2023. "Special Issue “Disaster Risk Reduction and Climate Change Adaptation: An Interdisciplinary Approach”," IJERPH, MDPI, vol. 20(3), pages 1-4, 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:11:y:2022:i:9:p:1379-:d:895297. 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.