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시계열 위성자료를 활용한 갯벌 면적·지형고도·조류로 모니터링 체계
No full text갯벌의 지형·면적·조류로와 같은 형태정보는 해상풍력의 기초 구조물 배치, 해저케이블 경로 설계, 장기 안정성 평가에 직결되며, 준설·퇴적의 누적 효과와 조위 변동을 고려할 때 장주기·광역 모니터링이 요구된다. 항공기 기반 조사가 통상 수년 주기로 이뤄지는 한계를 보이는 만큼, 모니터링 주기를 단축하기 위해서는 반복관측이 가능한 위성 시계열의 활용성이 크다. 본 연구의 목적은 위성 시계열 데이터를 활용해 과거부터 현재까지의 갯벌 형태정보를 일관된 방법론으로 산출하고, 외부 검증자료와의 비교를 통해 위성 기반 산출물의 신뢰 가능 범위를 확인하는 데 있다. 이를 위해, 갯벌 면적은 NDVI·NDWI·NDSI 등 다중 스펙트럴 지수를 활용하여 기계학습 모델로 산출했다. 지형 고도의 경우 시계열 수륙경계선과 관측 조위를 결합한 수위–고도 변환분석으로 재구성했으며, 무인기(UAV) 및 항공 LiDAR 데이터로 교차 검증을 수행했다. 그 결과, 1984–2023년 자료를 5년 간격으로 처리하여 전국 갯벌의 기준 면적을 구축하였고, 동기간 조사원 발행 면적과의 일치도를 확인하였다. 또한 경기만·강화도·곰소만에서는 5년 간격 지형고도 지도를 제작하여 침퇴적 변화와 조류로 형상 변화를 파악하고, 항공기 자료 비교로 공간적 타당성을 점검하였다. 이러한 검토는 위성 시계열 기반 산출물이 외부 자료와의 정합성을 갖추었는지 우선적으로 시험한 결과로서, 향후 항공기 기반의 장주기 조사 사이에 위성 갱신 정보를 보완적으로 적용할 수 있는 근거를 제공한다. 나아가 동일 절차로 주기적 갱신이 가능하므로, 상대적 저변화 구역의 예비 선별 기준을 마련하고 장기 추적 체계로 확장할 수 있음을 시사한다. 향후에는 변화가 거의 없는 지역을 대상으로 단기 면적 변동 탐지의 정밀도를 높이고, 주요 조류로의 공간 패턴 분석을 통합하여 변화 안정 지역의 선별을 고도화할 예정이다.2
HR-ToF-AMS 활용한 해양에어로졸의 화학적 특성 분석 및 기원 분내 분석
No full textMarine aerosols from natural and anthropogenic sources influence atmospheric chemistry and climate but remain under-characterized. This study used HR-ToF-AMS aboard a research vessel to compare sub-micron aerosols in the Yellow Sea and East Sea (Sea of Japan). In the Yellow Sea, nitrate (NO3⁻, 38.1 ± 0.37%) dominated during continental outflow from China, with secondary formation shown by nitrate and VOC oxidation products. PMF identified four organic aerosol sources—hydrocarbon-like OA, oxygenated OA, biomass burning OA (BBOA), and methanesulfonic acid (MSA)—with anthropogenic sources contributing over 88% of organic mass. Strong correlations between BBOA and particle counts (Dp 100–500 nm, R² = 0.94) indicated aerosol growth via adsorption and scavenging. In the East Sea, elevated aerosols and black carbon were observed near industrial coasts. PMF identified five OA sources, including DMS oxidation products. MSA and MSA:sulfate ratios showed stronger marine influence and higher natural aerosol contributions in the East Sea. These findings reveal complex aerosol sources along the Korean Peninsula.2
The crucial role of rainfall in microplastic transfer from terrestrial to marine environments
No full textAlthough rainfall can play a significant role in transporting microplastics to the sea, its impact has been overlooked in the measurement and modeling of microplastic input through waterways. This study aimed to quantify and characterize microplastics entering a coastal bay via streams, with a particular focus on the influence of rainfall-induced stormwater runoff discharge. To achieve this objective, we investigated the emission characteristics of microplastics into Masan Bay via the Samhochoen, an urban creek discharging into the bay, during two rainfall events using time-weighted sampling. The event mean concentrations (EMCs) microplastics ranged from 29.9 to 44.7 n/L. The abundance of microplastics generally peaked in the early stage of runoff and varied according to rainfall intensity during each rainfall event. Polypropylene and polyethylene were found as major polymers accounting for around 60% of total microplastics. Fragments were the dominant shape, and the most common size class was less than 200 μm. The total microplastic load emitted from an urban stream during a rainfall event was estimated to be between 3.75× 108 and 3.62 × 1010 particles. The load of microplastics was heavily affected by the total rainfall depth, and most microplastics were transported in the early stage of runoff. In our previous study, the annual microplastic load from creeks, based solely dry weather data, was estimated at 328 billion particles. This represented 22% of the total microplastic input into Masan Bay, while wastewater treatment plant (WWTP) effluent and atmospheric deposition accounted for 32% and 46%, respectively. However, in present study based on rainfall-event data, the annual load via creeks increased approximately 14-fold to 4.72 trillion particles. This led to a substantial increase in the contribution of creeks to 81% of the total microplastic input, whereas atmospheric deposition and WWTP effluent contributed only 11% and 8%, respectively. These findings suggest that rainfall-driven stormwater runoff discharge is a major contributor to microplastic transport from land to sea. Therefore, rainfall-induced runoff should be considered a critical factor when monitoring or modeling microplastic input through riverine pathways.1
Evaluation of mixed layer depth in Korean waters obtained by reanalysis data sets: spatial distribution and interannual variability
No full textThe mixed layer depth (MLD) plays a vital role in regulating climate by controlling the exchange of momentum, heat, and moisture between the ocean and atmosphere. Improving the simulation of MLD is therefore crucial for reliable climate predictions and projections. However, studies on the interannual variability of MLD using global reanalysis data are insufficient. In this study, we examined the interannual variability of winter (February) MLD in Korean waters over a 25-year period (1994–2018) using two reanalysis data sets, the HYbrid Coordinate Ocean Model (HYCOM) and CMEMS Global Ocean Reanalysis and Simulation (GLORYS), which have been widely used in climate change studies in Korean waters. The reanalysis MLD data were compared with observational estimates from the Korea Oceanographic Data Center (KODC) and NIFS Serial Oceanographic observations (NSO) for February, the month with the deepest MLD. The spatial distribution is relatively well simulated, but the long-term trend is poorly reproduced. Notably, the models underestimate the long-term mean MLD by approximately 25% in regions influenced by the Ulleung Eddy and the Yellow Sea Warm Current. The underestimated bias in the Ulleung Eddy can be attributed to the insufficient resolution of the reanalysis data sets in capturing the finescale structure of the Ulleung Eddy, while the bias in the Yellow Sea Warm Current region is possibly due to lack of tidal mixing in the reanalysis. Furthermore, while the observed MLD shows a deepening trend over most Korean waters during the study period, the models show negligible changes or even a shallowing trend, except in the East/Japan Sea showing a underestimated deepening trend. The models also tend to underestimate the magnitude of interannual variability of the MLD. Empirical Orthogonal Function (EOF) analysis reveals that MLD interannual variability is influenced primarily by variabilities of 10 m wind and 2 m air temperature (~18%), and secondarily by Tsushima Warm Current transport (TWC; ~11%). The TWC transport is closely related to the path of the East Korea Warm Current, suggesting that changes in the current's interannual variability could influence the MLD. Additionally, in other regions, TWC transport is influenced by the Kuroshio current transport, which determines the volume of transport entering Korean waters, thus explaining its association with MLD variability. This finding highlights the importance of oceanic processes in interannual variability in the winter MLD in Korean waters.2
A Study on the Evaluation of Marine Climate Change Monitoring and Forecasting Activities
No full textIn response to growing concerns over climate change, the Korean government enacted the “Act on the Observation and Prediction of Climate and Climate Change” in 2023. This legislation reflects an increased national commitment to strengthening R&D and improving systems for marine climate observation and forecasting. This study aims to assess expert perceptions and evaluate the technological readiness of Korea's marine climate change monitoring and prediction activities. A structured assessment was conducted involving experts from government agencies, research institutes, universities, and private companies to evaluate the technological maturity and relative importance of various activities. Sensitivity analysis was also employed to capture differences in institutional perspectives. The findings reveal that experts strongly recognize the need for strategic government involvement and expanded R&D to address the risks posed by natural disasters and marine environmental challenges. Technological benchmarking indicates that the United States leads globally, while Korea's technology level is approximately 74.1% that of the U.S., with a lag of about 8.7 years. The analysis of priorities shows sectoral differences: public sector and industry experts prioritize the application of climate information, while academic experts place greater emphasis on forecasting capabilities. Experts also highlighted the importance of sustainable policy frameworks and expanded national R&D efforts. The study concludes that institutional affiliation significantly shapes how technological importance and urgency are perceived. These insights suggest the need for the Korean government to tailor marine climate policies based on structured priority assessments. The results are expected to provide a foundational basis for more effective, evidence-based policymaking in the face of accelerating marine climate change.1
Assessment of Microplastic Pollution in the Surface Offshore Waters of South Korea (East Sea) Using a Continuous Underway Sampling Method
No full textMicroplastics (MPs) in marine environments are an emerging concern due to their widespread distribution, ingestion by various marine organisms, and their roles as a source and carrier of hazardous chemicals. This study investigated the levels, geographical distribution, and contamination characteristics of MPs in surface waters of the eastern offshore region of South Korea (East Sea). To date, most studies monitoring MPs in surface seawater have relied on grab sampling, which collects individual seawater samples at specific locations. However, this method offers limited spatial coverage and may not adequately represent the broader patterns of MP pollution. To overcome this limitation, we employed a custom-designed Surface Water Underway Sampler (SWUS), which continuously collects surface water, including the air–sea interface layer, from a fast-moving vessel. In this study, seawater samples (>20㎛) were collected along 15 transect lines in East Sea using the SWUS aboard the R/V Onnuri in April 2023. MPs were detected in all surface water samples collected across the East Sea, with concentrations ranging from 14.8-315.5 n/m³ (mean: 90.0 ± 79.5 n/m³). Notably, 79% of the MPs were smaller than 200 μm. Fragment-type MPs were the most dominant shape (74.8%), followed by fibers (24.8%) and films (0.4%). The predominant polymer types were polyester/polyethylene terephthalate (PES/PET, 29.3%), polypropylene (PP, 28.9%), and alkyd (10.5%), followed by polyethylene vinyl acetate (PEVA, 6.1%), polyamide (PA, 5.9%), and polyethylene (PE, 4.5%). Overall, high-density polymers (> 1 g/cm³) accounted for 58.7% of the total, indicating a relatively higher proportion compared to low-density polymers such as PP, PE, and PEVA. Higher MP abundance was observed in the central regions of the East Sea despite the lower human activity and industrial facilities, suggesting that physical oceanographic processes may play an important role in the transport and distribution of MPs in the region. To our knowledge, this is the first study to assess the distribution patterns of microplastics (>20㎛) in surface waters of the East Sea using the SWUS. This approach improves the representativeness of MP data and provides new insights into the large-scale variability of microplastic concentrations in the ocean surface layer. The findings of this study highlight the utility of SWUS as a valuable tool for high-resolution and spatially extensive monitoring of microplastics in marine environments.1
천해에서 표류형 음향부이를 이용한 중형 무인수상선 방사소음 측정
No full text최근 해양 무인체의 개발 및 활용범위가 증대됨에 따라 이들이 발생시키는 수중방사소음을 정확하게 측정하고 평가하는 것이 함께 중요해지고 있다. 본 연구자들은 이러한 흐름에 부응하여 해양 무인체의 수중방사소음에 대한 공인인증체계를 구축하는 작업을 진행해 오고 있다. 우리는 우선 그 기초가 되는 작업으로서, 천해환경에서 소형 무인수상선의 수중방사소음을 정확히 측정할 수 있는 조건에 대해 연구한 바 있다. 그러나, 무인수상선은 크기나 추진체 종류가 다양하기 때문에 그 수중방사소음의 레벨 크기도 차이를 보일 수 있다. 따라서, 시험체의 사양에 따라 측정조건을 다르게 적용할 필요가 있을 것으로 생각된다. 우리는 이에 대해서 실제로 조사해 보고자 중형 무인수상선 1종을 선정하여, 수심별로 스마트 수중청음기가 장착된 표류형 음향부이를 이용한 실해역 실험을 수행하였다. 본 실험에서 무인수상선은 세 가지 선속으로 운행하였으며, 수중 청음기 위치로부터 무인수상선까지의 거리를 조금씩 바꾸어 가며 운행하였다. 우리는 무인수상선의 운행시간 동안 수중청음기에 수신된 수중방사소음을 미국선급의 지침[3]에 따라 분석함으로써, 중형 무인수상선의 수중방사소음 측정에 적절한 수중청음기와의 이격거리, 음원레벨 분석에 적합한 무인선 운행구간 등을 도출할 수 있었다. [해양수산부 재원으로 해양수산과학기술진흥원의 지원을 받아 수행된 연구임 (RS-2023-00256122)]2
Cryptic Divergence of Rochia nilotica (Gastropoda: Tegulidae) from Chuuk Lagoon, Federated States of Micronesia, Revealed by Morphological and Mitochondrial Genome Analyses
No full textRochia nilotica is a tropical marine gastropod inhabiting Indo-Pacific coral reefs and is an important resource for many Pacific Island nations, where it is used both as food and as a source of shell material for traditional crafts. To better understand the genetic identity of this species in remote regions, we collected individuals from Weno Island in Chuuk Atoll, Federation of Micronesia, and analyzed their complete mitochondrial genome. We also compared two commonly used DNA markers (COX1 and 16S rRNA) together with 13 protein-coding genes from the mitochondrial genome to reconstruct their evolutionary relationships. The genetic results showed that the Chuuk population forms congruent topology with R. nilotica from other regions, but it also occupies a distinct position within the Rochia group. This pattern suggests that long-term geographic isolation of Chuuk Atoll may have shaped unique genetic characteristics in this population. These findings highlight the importance of combining DNA data with traditional shell-based identification to correctly recognize species. Such integrative approaches are essential for conserving marine biodiversity and supporting sustainable aquaculture and fisheries management in isolated reef ecosystems.11Ysciescopu
Marine geophysical exploration for seafloor massive sulfides using unmanned underwater vehicles
No full textSeafloor massive sulfide (SMS) deposits contain strategic metals essential for modern technologies, but traditional exploration methods using water column surveys and direct observation provide limited insight into subsurface extent and structure. This study evaluated three geophysical methods for SMS exploration using unmanned underwater vehicles: self-potential (SP), magnetic, and controlled-source electromagnetic (CSEM) techniques. Through 3D numerical modeling and inversion studies based on the Trans-Atlantic Geotraverse field, we demonstrated that SP and magnetic methods offer cost-effective, passive reconnaissance capabilities with limited depth resolution, while CSEM provides superior high-resolution 3D imaging but requires more sophisticated instrumentation. Autonomous underwater vehicles excel in large-scale surveys, whereas remotely operated vehicles enhance signal detection through closer seafloor proximity. Integration of multiple geophysical data sets significantly improved detection accuracy and reduced interpretive uncertainties. As marine sensors and numerical algorithms advance, these integrated geophysical approaches will play increasingly crucial roles in efficient SMS exploration, with benefits far outweighing survey costs.33Nscopu
Diffusion Model-based Super-resolution of Tidal Flats A Guided DDPM Approach
No full textMonitoring tidal flats requires high-resolution satellite imagery to analyze dynamic land-water interactions and detect subtle geomorphological changes. However, widely used optical satellite sensors frequently encounter limitations in resolution and temporal frequency, preventing detailed coastal analysis. Landsat imagery, with its 30-meter resolution, provides a long-term observational record of tidal flats, while Sentinel-2, with its higher 10-meter resolution, offers enhanced spatial detail. The integration of these datasets enables the utilization of both long-term observations and higher temporal revisit frequencies, a strategy that is particularly advantageous for tidal flats, where rapid water level fluctuations introduce significant variability. Improving the resolution of Landsat imagery to match Sentinel-2 can further strengthen the ability to monitor both short- and long-term tidal flat changes.
In this study, we explore the adaptability of a well-trained denoising diffusion probabilistic model (DDPM) by repurposing it for super-resolution without additional training. Originally designed for cloud removal in optical satellite images, the model is applied to enhance the resolution of tidal flat imagery, transforming 30-meter Landsat data into 10-meter Sentinel-2 quality. Rather than training a new model for super-resolution, we modified the guided sampling process of the pre-trained DDPM to synthesize high-resolution details from lower-resolution inputs. Our approach utilizes gradient-guided diffusion sampling to refine image details beyond the capabilities of conventional upsampling methods, preserving intricate tidal flat structures and improving the clarity of dynamic land-water boundaries.
To evaluate the effectiveness of the proposed method in tidal flats, we compared the super-resolved images with those interpolated using bicubic methods. The evaluation employed quantitative metrics, including the Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR). Preliminary results indicate that the proposed approach consistently outperforms bicubic interpolation, producing sharper geomorphological features and more coherent tidal channel structures. This enhancement is particularly relevant for detecting small-scale changes in sediment transport, intertidal vegetation distribution, and coastline shifts—key factors in understanding tidal flat evolution.
Beyond tidal flat applications, this study showcases the broader potential of reusing pre-trained diffusion models across various remote sensing tasks. For instance, a generative model trained on 250-meter GOCI-II data could be used for both cloud removal and the super-resolution enhancement of coarser-resolution datasets, such as 500-meter GOCI-I imagery. While the resolution of GOCI sensors may not be suitable for tidal flat studies, this approach demonstrates how diffusion models can be adapted flexibly to different satellite platforms, offering new possibilities for large-scale environmental monitoring.
By leveraging existing models without the need for retraining, our method presents a scalable and cost-effective solution for improving tidal flat change detection. Future work will refine the methodology further and explore its applicability across diverse intertidal and coastal monitoring challenges.1