IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i5p454-d542258.html
   My bibliography  Save this article

Local Climate Zone Mapping Using Multi-Source Free Available Datasets on Google Earth Engine Platform

Author

Listed:
  • Lingfei Shi

    (College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou 450002, China)

  • Feng Ling

    (Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430077, China)

Abstract

As one of the widely concerned urban climate issues, urban heat island (UHI) has been studied using the local climate zone (LCZ) classification scheme in recent years. More and more effort has been focused on improving LCZ mapping accuracy. It has become a prevalent trend to take advantage of multi-source images in LCZ mapping. To this end, this paper tried to utilize multi-source freely available datasets: Sentinel-2 multispectral instrument (MSI), Sentinel-1 synthetic aperture radar (SAR), Luojia1-01 nighttime light (NTL), and Open Street Map (OSM) datasets to produce the 10 m LCZ classification result using Google Earth Engine (GEE) platform. Additionally, the derived datasets of Sentinel-2 MSI data were also exploited in LCZ classification, such as spectral indexes (SI) and gray-level co-occurrence matrix (GLCM) datasets. The different dataset combinations were designed to evaluate the particular dataset’s contribution to LCZ classification. It was found that: (1) The synergistic use of Sentinel-2 MSI and Sentinel-1 SAR data can improve the accuracy of LCZ classification; (2) The multi-seasonal information of Sentinel data also has a good contribution to LCZ classification; (3) OSM, GLCM, SI, and NTL datasets have some positive contribution to LCZ classification when individually adding them to the seasonal Sentinel-1 and Sentinel-2 datasets; (4) It is not an absolute right way to improve LCZ classification accuracy by combining as many datasets as possible. With the help of the GEE, this study provides the potential to generate more accurate LCZ mapping on a large scale, which is significant for urban development.

Suggested Citation

  • Lingfei Shi & Feng Ling, 2021. "Local Climate Zone Mapping Using Multi-Source Free Available Datasets on Google Earth Engine Platform," Land, MDPI, vol. 10(5), pages 1-18, April.
  • Handle: RePEc:gam:jlands:v:10:y:2021:i:5:p:454-:d:542258
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/5/454/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/10/5/454/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Lingfei Shi & Feng Ling & Giles M. Foody & Zhen Yang & Xixi Liu & Yun Du, 2021. "Seasonal SUHI Analysis Using Local Climate Zone Classification: A Case Study of Wuhan, China," IJERPH, MDPI, vol. 18(14), pages 1-13, July.

    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:10:y:2021:i:5:p:454-:d:542258. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.