Determination of Harmful Algal Blooms in Satellite Images using Decision Tree Algorithm

Title
Determination of Harmful Algal Blooms in Satellite Images using Decision Tree Algorithm
Author(s)
박수호; 김흥민; 황도현; 김범규; 강돈혁; 윤홍주
KIOST Author(s)
Kang, Don Hyug(강돈혁)
Publication Year
2018-01-24
Abstract
Using a decision tree algorithm, as a kind of machine learning technique, we distinguished the area where the red tide occurred or not occur. The satellite image was divided into smaller size lattices, and each lattice is classified by the inclusion of red tide pixels. 5 filters with different optical properties were created for quantify the features of each lattices. The generated filters were used to computing similarity with each sample lattice. As a result of the classification model, we confirmed 4 features related to the presence or absence of red tide pixels in the grid. As a result of comparison with the verification data, it was confirmed that the grid with the size of 15 km had excellent classification performance.inclusion of red tide pixels. 5 filters with different optical properties were created for quantify the features of each lattices. The generated filters were used to computing similarity with each sample lattice. As a result of the classification model, we confirmed 4 features related to the presence or absence of red tide pixels in the grid. As a result of comparison with the verification data, it was confirmed that the grid with the size of 15 km had excellent classification performance.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/23490
Bibliographic Citation
Proceedings on the 21th International Conference on Electric & Information Communication, pp.85 - 87, 2018
Publisher
ICEIC
Type
Conference
Language
English
Publisher
ICEIC
Related Researcher
Research Interests

Marine security,Underwater Acoustics,해양방위,수중음향

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