Red tide detection using deep learning and high-spatial resolution optical satellite imagery-Reference-Cited by-同舟云学术

Red tide detection using deep learning and high-spatial resolution optical satellite imagery

Published:2019-12-26 Issue:15 Volume:41 Page:5838-5860
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Lee Min-Sun¹²^ORCID,Park Kyung-Ae²³,Chae Jinho⁴^ORCID,Park Ji-Eun²,Lee Joon-Soo⁵,Lee Ji-Hyun⁶

Affiliation:

1. Hopkins Marine Station, Stanford University , Stanford, CA, USA

2. Department of Earth Science Education, Seoul National University , Seoul, Korea

3. Research Institute of Oceanography, Seoul National University , Seoul, Korea

4. Marine Environmental Research and Information Laboratory , Gunpo, Korea

5. Ocean Climate and Ecology Research Division, National Institute of Fisheries Science , Busan, Korea

6. Department of Science Education, Seoul National University , Seoul, Korea

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2019.1706011

Reference49 articles.

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3. Anderson, D. M. 1989. “Toxic Algal Blooms and Red Tides: A Global Perspective.” Red Tides: Biology, Environmental Science, and Toxicology : Proceedings of the First International Symposium on Red Tides Held November 10-14, 1987.

4. Approaches to monitoring, control and management of harmful algal blooms (HABs)

5. Introduction Neural networks in remote sensing

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