합성곱신경망을 활용한 천리안위성 2A호 영상 기반의 동해안 냉수대 감지 연구 = A Study on the GK2A/AMI Image Based Cold Water Detection Using Convolutional Neural Network

다국어 초록 (Multilingual Abstract)

In this study, the classification of cold water and normal water based on Geo-Kompsat 2A images was performed. Daily mean surface temperature products provided by the National Meteorological Satellite Center (NMSC) were used, and convolution neural network (CNN) deep learning technique was applied as a classification algorithm. From 2019 to 2022, the cold water occurrence data provided by the National Institute of Fisheries Science (NIFS) were used as the cold water class. As a result of learning, the probability of detection was 82.5% and the false alarm ratio was 54.4%. Through misclassification analysis, it was confirmed that cloud area should be considered and accurate learning data should be considered in the future.