Comparison of Satellite Imagery for Identifying Seagrass Distribution Using a Machine Learning Algorithm on the Eastern Coast of South Korea

Comparison of Satellite Imagery for Identifying Seagrass Distribution Using a Machine Learning Algorithm on the Eastern Coast of South Korea

Seagrass is an essential component of coastal ecosystems because of its capability to absorb blue carbon, and its involvement in sustaining marine biodiversity. In this study, support vector machine (SVM) technologies with corrected satellite imagery data, were applied to identify the distribution o...

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Bibliographic Details
Main Authors: Liadira Kusuma Widya, Chang-Hwan Kim, Jong-Dae Do, Sung-Jae Park, Bong-Chan Kim, Chang-Wook Lee
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Journal of Marine Science and Engineering
Subjects:
seagrass
remote sensing
support vector machines (SVM)
classification models
Online Access:https://www.mdpi.com/2077-1312/11/4/701

Internet

https://www.mdpi.com/2077-1312/11/4/701

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