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Cloud Detection from the Himawari-8 Satellite Data Using a Convolutional Neural Network

  • METHODS AND PROCESSING TOOLS AND INTERPRETATION OF SPACE INFORMATION
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Abstract

The methodology of cloud detection from the data of the Himawari-8 geostationary satellite using a convolutional neural network is considered. The model of the cloud classifier has been tested in various scenarios, including winter and summer at night and daytime, as well as at day and night change. According to the test results, it has been found that, even in complex scenarios, the classifier has minimal errors when compared to the cloud-detection algorithms used in global operational practice.

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Authors and Affiliations

  1. Far Eastern Center, State Research Center for Space Hydrometeorology Planeta, Khabarovsk, Russia

    A. I. Andreev & Yu. A. Shamilova

  2. Computer Center, Far Eastern Branch, Russian Academy of Sciences, Khabarovsk, Russia

    A. I. Andreev

Authors
  1. A. I. Andreev
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  2. Yu. A. Shamilova
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Correspondence to A. I. Andreev.

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Translated by O. Pismenov

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Andreev, A.I., Shamilova, Y.A. Cloud Detection from the Himawari-8 Satellite Data Using a Convolutional Neural Network. Izv. Atmos. Ocean. Phys. 57, 1162–1170 (2021). https://doi.org/10.1134/S0001433821090401

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