Fishing activities have been recognized as one of the primary contributors to marine environmental pollution. Studies have been conducted on the impact of fishing activities on the accumulation of marine debris, but most of these studies have been conducted at specific points in time. This study collected marine debris data over four years in the coastal area of Korea. Data on the magnitude of nearshore fishing activities during the same period were collected and analyzed. Regression models were constructed to explore the impact of nearshore fishing activities on coastal waste accumulation over time. This research aimed to understand the influence of nearshore fishing activities on the accumulation of ocean-sourced coastal waste, leading to the development of a time series regression model. The results indicated that time series models have substantially more explanatory power compared to conventional models, emphasizing the importance of temporal considerations in quantifying the relationship between fishing activities and coastal litter over time.

Despite the existence of standardized collision regulations such as the International Regulations for Preventing Collisions at Sea (COLREGs), ship collisions continue to occur, indicating persistent gaps in how navigators interpret and apply these rules. The COLREGs are globally adopted rules that govern vessel conduct to avoid collisions. Borderline encounter situations—such as those between head-on and crossing, or overtaking and crossing—pose particular challenges, often resulting in inconsistent or ambiguous interpretations. This study models navigator awareness as a probabilistic function of encounter angle, aiming to identify interpretive transition zones and cognitive uncertainty in rule application. A structured survey was conducted with 101 licensed navigators, each evaluating simulated ship encounter scenarios with varying relative bearings. Responses were collected using a Likert scale and analyzed in angular sectors known for interpretational ambiguity: 006–012° for head on to crossing (HC) and 100–160° for overtaking to crossing (OC). Gaussian curve fitting was applied to the response distributions, with the awareness center (μ) and standard deviation (σ) serving as indicators of consensus and ambiguity. The results reveal sharp shifts in awareness near 008° and 160°, suggesting cognitively unstable zones. Risk-averse interpretation patterns were also observed, where navigators tended to classify borderline situations more conservatively under uncertainty. These findings suggest that navigator awareness is not deterministic but probabilistically structured and context sensitive. The proposed awareness modeling framework helps bridge the gap between regulatory prescriptions and real world navigator behavior, offering practical implications for MASS algorithm design and COLREGs refinement.

본 연구에서는 해양 환경 및 안전 규제에 대한 IMO의 각종 국제협약 내용을 분석하여 최적 안전항로 지원 시스템의 개념설계를 수행하였다. MARPOL Annex VI의 개정안은 선박의 에너지 효율을 개선하기 위해 에너지효율 운항지표의 자발적 모니터링을 요구하고 있다. 극지해역 운항선박 안전기준은 극지해역 항해에 대한 운항범위와 환경조건의 평가를 요구하고 있다. IMO e-Navigation 이행계획에서는 조화로운 방식으로 전자 정보를 제공하는 수단인 해상서비스 포트폴리오를 요구하고 있다. 본 연구를 통해 최적 안전항로 지원 시스템의 개념설계를 수행하였고, 이 때 필요한 정보들을 도출하였다. 최적 안전항로 지원 시스템의 데이터베이스는 선박성능 데이터베이스, 해도 데이터베이스, 운항안전 데이터베이스 및 해양기상 데이터베이스로 구성하였다. 선박성능 데이터베이스는 선박 제원, 선박성능 계수, 각종 외력에 의한 부가저항 자료로 구성된다. 해도 데이터베이스는 해도 및 수로 서지 등으로 구성된다. 운항안전 데이터베이스는 항해 경보, 기상 경보, 조난 경보, 해빙 위험 등으로 구성된다. 해양기상 데이터베이스는 기상 정보, 실시간 수로 및 환경 정보 등으로 구성된다. 이를 바탕으로 선박성능 데이터베이스의 예제를 만들었고, 이를 위한 해양기상 데이터베이스 구축 방안을 제시하였다.