Mapping Paddy fields in Japan by using a Sentinel-1 SAR time series supplemented by Sentinel-2 images on Google Earth Engine

Shimpei Inoue, Akihiko Ito, Chinatsu Yonezawa

    Research output: Contribution to journalArticlepeer-review

    19 Citations (Scopus)

    Abstract

    Paddy fields play very important environmental roles in food security, water resource management, biodiversity conservation, and climate change. Therefore, reliable broad-scale paddy field maps are essential for understanding these issues related to rice and paddy fields. Here, we propose a novel paddy field mapping method that uses Sentinel-1 synthetic aperture radar (SAR) time series that are robust for cloud cover, supplemented by Sentinel-2 optical images that are more reliable than SAR data for extracting irrigated paddy fields. Paddy fields were provisionally specified by using the Sentinel-1 SAR data and a conventional decision tree method. Then, an additional mask using water and vegetation indexes based on Sentinel-2 optical images was overlaid to remove non-paddy field areas. We used the proposed method to develop a paddy field map for Japan in 2018 with a 30 m spatial resolution. The producer's accuracy of this map (92.4%) for non-paddy reference agricultural fields was much higher than that of a map developed by the conventional method (57.0%) using only Sentinel-1 data. Our proposed method also reproduced paddy field areas at the prefecture scale better than existing paddy field maps developed by a remote sensing approach.

    Original languageEnglish
    Article number1622
    JournalRemote Sensing
    Volume12
    Issue number10
    DOIs
    Publication statusPublished - 2020 May 1

    Keywords

    • Decision tree
    • Google earth engine
    • Paddy field
    • Sentinel-1
    • Sentinel-2

    ASJC Scopus subject areas

    • Earth and Planetary Sciences(all)

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