High Spatial-Resolution Red Tide Detection in the Southern Coast of Korea Using U-Net from PlanetScope Imagery
SCIE
SCOPUS
Cited 9 time in
WEB OF SCIENCE
Cited 10 time in
Scopus
-
Title
- High Spatial-Resolution Red Tide Detection in the Southern Coast of Korea Using U-Net from PlanetScope Imagery
-
Author(s)
- Shin, Jisun; Jo, Young-Heon; Ryu, Joo Hyung; Khim, Boo-Keun; Kim, Soo Mee
- KIOST Author(s)
- Ryu, Joo Hyung(유주형); Kim, Soo Mee(김수미)
-
Alternative Author(s)
- 유주형; 김수미
-
Publication Year
- 2021-06
-
Abstract
- Red tides caused by Margalefidinium polykrikoides occur continuously along the southern coast of Korea, where there are many aquaculture cages, and therefore, prompt monitoring of bloom water is required to prevent considerable damage. Satellite-based ocean-color sensors are widely used for detecting red tide blooms, but their low spatial resolution restricts coastal observations. Contrarily, terrestrial sensors with a high spatial resolution are good candidate sensors, despite the lack of spectral resolution and bands for red tide detection. In this study, we developed a U-Net deep learning model for detecting M. polykrikoides blooms along the southern coast of Korea from PlanetScope imagery with a high spatial resolution of 3 m. The U-Net model was trained with four different datasets that were constructed with randomly or non-randomly chosen patches consisting of different ratios of red tide and non-red tide pixels. The qualitative and quantitative assessments of the conventional red tide index (RTI) and four U-Net models suggest that the U-Net model, which was trained with a dataset of non-randomly chosen patches including non-red tide patches, outperformed RTI in terms of sensitivity, precision, and F-measure level, accounting for an increase of 19.84%, 44.84%, and 28.52%, respectively. The M. polykrikoides map derived from U-Net provides the most reasonable red tide patterns in all water areas. Combining high spatial resolution images and deep learning approaches represents a good solution for the monitoring of red tides over coastal regions.
-
ISSN
- 1424-8220
-
URI
- https://sciwatch.kiost.ac.kr/handle/2020.kiost/42219
-
DOI
- 10.3390/s21134447
-
Bibliographic Citation
- SENSORS, v.21, no.13, 2021
-
Publisher
- MDPI
-
Subject
- HARMFUL ALGAL BLOOMS; COCHLODINIUM POLYKRIKOIDES BLOOMS; KARENIA-BREVIS BLOOMS; GULF-OF-MEXICO; TOXIC DINOFLAGELLATE; COLOR; SEA; WATERS; EAST; NETWORK
-
Keywords
- Margalefidinium polykrikoides; PlanetScope; southern coast of Korea; convolutional neural network; U-Net
-
Type
- Article
-
Language
- English
-
Document Type
- Article
- Files in This Item:
-
There are no files associated with this item.
Items in ScienceWatch@KIOST are protected by copyright, with all rights reserved, unless otherwise indicated.