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International CCF Conference on Artificial Intelligence

ICAI 2018: Artificial Intelligence pp 127–138Cite as

Automatic Cloud Detection Based on Deep Learning from AVHRR Data

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 888))

Abstract

Thanks to the development of satellite remote sensing technology, more observing data are acquired and can be used for various purposes. However, statistical data show that half of the earth’s surface is covered by clouds, which may seriously influence the usability of remote sensing data. Most existing cloud detection methods are manual or semi-automatic methods with low efficiency. This paper focuses on automatic cloud detection over sea surface from Advanced Very High Resolution Radiometer (AVHRR) data. A novel cloud detection framework named DBN-Otsu Hybrid Model (DOHM) has been proposed, which combines Deep Belief Networks (DBN) and Otsu’s method for the first time. DOHM adopts adaptive thresholds to replace manual interventions, implementing full automation. Experimental results show that DOHM achieves the highest average accuracy ratio among the six detection methods. Moreover, DOHM makes a good balance between False Alarm Rate (FAR) and Miss Rate (MR).

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Acknowledgement

The satellite data are provided by Satellite Ground Station of Ocean University of China.

This work is supported by the National Natural Science Foundation of China (61572448, 61673357), the Natural Science Foundation of Shandong Province (ZR2014JL043), and the Key R&D Program of Shandong Province (2018GSF120015).

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Authors and Affiliations

  1. Ocean University of China, Qingdao, 266100, People’s Republic of China

    Meng Qiu, Haoyu Yin, Qiang Chen & Yingjian Liu

Authors
  1. Meng Qiu
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  2. Haoyu Yin
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  3. Qiang Chen
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  4. Yingjian Liu
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Corresponding author

Correspondence to Yingjian Liu .

Editor information

Editors and Affiliations

  1. Nanjing University, Nanjing, China

    Zhi-Hua Zhou

  2. Hong Kong University of Science and Technology, Hong Kong SAR, China

    Qiang Yang

  3. Nanjing University, Nanjing, China

    Yang Gao

  4. JD Finance, Beijing, China

    Yu Zheng

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© 2018 Springer Nature Singapore Pte Ltd.

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Qiu, M., Yin, H., Chen, Q., Liu, Y. (2018). Automatic Cloud Detection Based on Deep Learning from AVHRR Data. In: Zhou, ZH., Yang, Q., Gao, Y., Zheng, Y. (eds) Artificial Intelligence. ICAI 2018. Communications in Computer and Information Science, vol 888. Springer, Singapore. https://doi.org/10.1007/978-981-13-2122-1_10

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  • DOI: https://doi.org/10.1007/978-981-13-2122-1_10

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2121-4

  • Online ISBN: 978-981-13-2122-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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