비디오 모니터링 데이터를 활용한 U-Net 기반 Waterline추출 자동화 및 해안선 추정

• 영문명: Automated Waterline Extraction and Shoreline Estimation Using U-Net Based Video Monitoring System
• 발행기관: 한국연안방재학회
• 저자명: 이창율(Chang-yul Lee) 도기덕(Ki-deok Do) 장성열(Sung-yeol Chang) 김인호(Inho Kim)
• 간행물 정보: 『한국연안방재학회지』제12권 제1호, 1~15쪽, 전체 15쪽
• 주제분류: 자연과학 > 지질학
• 파일형태: PDF
• 발행일자: 2025.03.31

국문 초록

Coastal erosion has caused significant ecological damage and substantial social and economic losses, emphasizing the necessity for long-term monitoring of shorelines. Video monitoring systems have emerged as effective tools for observing shorelines changes. However, the shoreline extracted from video monitoring systems represents the waterline, defined as the boundary where waves reach the beach. The extraction of waterlines using these systems often requires manual parameter adjustments to account for dynamic coastal environments. Furthermore, the extracted waterline is influenced by variations in waves and currents, posing challenges for consistent and reliable monitoring. To address these issues, this study utilizes the deep learning model ‘U’-shaped Neural Network (U-Net) to analyze images of Chuam Beach. A dataset comprising 204 pairs of Time-exposure (TimeX) images was developed to train the U-Net model, which was subsequently utilized to propose an automated method for waterline extraction. Using the extracted waterlines, the beach slope was calculated, enabling the estimation of a tide-based shoreline unaffected by wave and currents variations. Comparative analysis with UAV (Unmanned Aerial Vehicle)-based shoreline data revealed a maximum vertical error of 0.18 m for the waterline and 0.27 m for the shoreline, demonstrating high accuracy. These findings indicate that the U-Net model effectively and accurately detects waterlines, while the proposed shoreline estimation method ensures consistent monitoring of shoreline changes, including advances and retreats.

목차

1. 서 론

2. 연구 지역 및 데이터 취득

3. 해안선 추출을 위한 모델 설계

4. 해안선 추출 과정

5. 결 론

References

키워드

Coastal erosion Video Monitoring System U-Net shoreline monitoring waterline