In maritime accidents leading to missing persons, acquiring accurate underwater environment information is crucial for effective search and rescue (SAR) operations. Current remote sensing techniques have limitations in providing comprehensive data beneath the sea surface. This study proposes a novel technology that enhances underwater visibility estimation by incorporating numerical modeling with high-resolution satellite data. First, turbidity was calculated utilizing the 560 nm surface reflectance data from Sentinel-2. The accuracy of turbidity values was assessed by comparison with in-situ turbidity data. To delineate detailed vertical mixing patterns influencing underwater visibility distribution, a comprehensive vertical profile database for water temperature and salinity was established using the Regional Ocean Modeling System (ROMS) model. Indices of vertical mixing, as a critical factor influencing underwater visibility, was achieved through quantitative analysis of seawater temperature and salinity data. The detailed underwater visibility distance is calculated by incorporating turbidity and vertical mixing effects. Subsequently, the underwater visibility will be validated through in-situ experimental measurements of both vertical and horizontal visibility along the coast using a Secchi disk. The outcomes of this study are anticipated to significantly contribute to enhancing the efficiency of rapid search and rescue operations for missing persons at sea.

In this study, we developed a technology for detecting small objects by conducting two aerial experiments targeting various objects, including ships, mannequins, and maritime safety equipment floating in coastal areas, thereby acquiring hyperspectral image data. By utilizing the hyperspectral data, we detected the pixels corresponding to the edges of ships and employed an ellipse fitting approach to identify the vessels, achieving a length error of 0.44 m. The N-FINDR spectral unmixing technique was applied to detect lifebuoys, buoyant apparatus, and mannequins, resulting in relatively small length errors ranging from 0.08 to 0.17 m.

Over the past 30 years, satellite altimeters have continuously observed the sea surface height (SSH) in the global ocean, providing clear evidence for the global average sea level rise based on these observations. Accurate altimeter-observed SSH is essential for studying the spatial and temporal variability of SSH in regional seas. In this study, we utilized measurements from the Ieodo Ocean Research Station (IORS) and validated the SSH observed by satellite altimeters (Envisat, Jason-1, Jason-2, SARAL, Jason-3, and Sentinel-3A/B). The bias and root mean square error for SSH from each satellite ranged between 1.58-4.69 cm and 6.33-9.67 cm, respectively. As the matchup distance between the satellite ground track and IORS increased, the error of the satellite SSH significantly amplified. Tide and atmospheric effects in the satellite data were verified by estimating tides using harmonic analysis and calculating inverse barometric effects using atmospheric pressure from IORS. It was confirmed that for accurate tidal corrections of satellite SSH data around the Korean Peninsula, an improvement in the tide data of satellites is necessary.

According to the Protocol on Preparedness, Response and Co-operation to Pollution Incidents by Hazardous and Noxious Substances (OPRC-HNS Protocol), hazardous and noxious substances (HNS) is referred to as a chemical substance, except for oil, that impairs the ocean by destroying the environment or are harmful to humans and marine life [1] . The increase in maritime transport of HNSs from the larger and faster ships entails the potential risk of marine HNS spill accidents. Highly toxic HNSs, such as benzene, toluene, and xylene, have serious adverse effects on the human body and various organisms living in the marine ecosystems. Most colorless and transparent HNSs have limitations in visual identification and can cause secondary accidents due to explosions and fires, making human access difficult. So, HNS remote sensing based on satellites and aircraft is important for HNS detection at sea because it has the advantage of monitoring a wide area and observing it at a high resolution. To monitor this HNS spill, we designed and performed a ground HNS spill experiment using a hyperspectral sensor to detect HNS areas and estimate the spill volume. The experiment was conducted at the Centre of Documentation, Research and Experimentation on Accidental Water Pollution (CEDRE) marine pool in BREST, France. The HNS image was obtained by pouring 1 L of toluene into an outdoor marine pool and observing it with a hyperspectral sensor capable of measuring the short-wave infrared (SWIR) channel installed at a height of approximately 12 m ( Figure 1 ). At a height of 12 m, the spatial resolution of the SWIR sensor is 10.3 mm and 5.3 mm in the horizontal and vertical directions, respectively. The pure endmember spectra of toluene and seawater were extracted using principal component analysis (PCA) and N-FINDR. This method has the advantage of not requiring input variables other than the number of pure substances. And a Gaussian mixture model (GMM) was applied to the toluene abundance fraction. This model is useful when the data contain multiple Gaussian distributions. The GMM represents a normally distributed subpopulation within the entire population, and it is possible to automatically learn subpopulations without requiring data on subpopulations [2] , [3] . Considering that the histogram of the abundance fraction corresponding to all pixels constituting the HNS image is composed of two peaks containing toluene and seawater rather than a single peak, the GMM is judged to be more suitable than a single model. Empirical linear calibration based on vicarious radiometric calibration was used as an atmospheric correction method for hyperspectral images. It constructs a linear equation using the pixel value of a specific index, whose reflectance is known in advance and is applied to the total image. Rectangular-shaped target plates with white (95%), gray (50%), and black (5%) reflectance were pre-positioned for inclusion in the hyperspectral image. Consequently, a toluene area of approximately 2.4317 mm 2 was detected according to the 36% criteria suitable for HNS detection. The HNS thickness estimation was based on a three-layer two-beam interference theory model [4] . In this model, the HNS thickness was estimated based on the relationship between the reflectance and transmittance at the interface composed of three layers of air, HNS, and seawater. Because toluene has a maximum extinction coefficient of 1.3055 mm at a wavelength of 1678 nm, the closest 1676.5 nm toluene reflectance image was used for thickness estimation. Considering the detection area and ground resolution, the amount of toluene that leaked was estimated to be 0.9336 L. As the amount of toluene used in the actual ground experiment was 1 L, the accuracy of our estimation is approximately 93.36%. Although we precisely designed and constructed the HNS spill experiment and retrieved the actual amount of spill material with reasonable result, there are many possibility to affect to the estimation of HNS thickness in the complicated marine environment. One of the most important causes may be the wind speed controlling evaporation of the HNS and rapid mixing with ambient seawater. The effect of wind field on the thickness estimation should be further investigated based on more intensive experiment in both marine pool circumstances and real sea environment. In this study, the estimated total toluene volume was slightly reduced compared with the amount of toluene spilled in the experiment. The elapsed time from toluene leakage to observation with the hyperspectral sensor was up to 3 min, and there is a possibility that some toluene had evaporated or dissolved. In addition to the effect of wind speed, the evaporation of toluene is affected by other atmospheric and marine environments, such as air temperature, humidity, temperature difference between the air and sea surface temperatures, sea state including various waves. Previous studies on HNS monitoring based on remote sensing are lacking compared with those on oil spills. Considering these limitations, this study evaluated the applicability of HNS detection and thickness estimation based on oil-like reflectance spectral trends at the SWIR wavelengths. The toluene detection results based on hyperspectral remote sensing are expected to be utilized for monitoring marine HNS accidents and evaluating harmful marine ecosystem environments.

Validation of daily Optimum Interpolation Sea Surface Temperature (OISST) data from 1982 to 2018 was performed by comparison with quality-controlled in-situ water temperature data from Korea Oceanographic Data Center observations in the Korean coastal regions. In contrast to the relatively high accuracy of the SSTs in the open ocean, the SSTs of the coastal regions exhibited large root-mean-square errors (RMSE) and a bias, which tended to be amplified towards the coastal lines. The coastal SSTs in the Yellow Sea presented much higher RMSE and bias due to the appearance of cold water on the surface induced by tidal mixing over shallow bathymetry. The long-term trends of OISSTs were also compared with those of in-situ water temperatures over decades. Although the trends of OISSTs deviate from those of in-situ temperatures in coastal regions, the spatial patterns of the OISST trends revealed a similar structure to those of in-situ temperature trends.

The Remotely sensed satellite or airborne images can aid rapid vessel monitoring over wide areas at high resolutions. In this study, airborne hyperspectral experiments were performed to detect marine vessels mainly including fishing boat and yacht by applying pixel-based mixture techniques and to estimate the size of the vessels through an objective ellipse fitting method. Several hyperspectral mixture algorithms, such as N-FINDR, pixel purity index (PPI), independent component analysis (ICA), and vertex component analysis (VCA), were used for the detection of vessels. The pixel-based probability of detection (POD) and false alarm ratio (FAR) for all 14 vessels were 96.40% and 4.30%, respectively. Compared with the digital mapping camera (DMC) images with resolutions of 0.10 m, the root-mean-square error of the length and width of the vessels were approximately 1.19 m and 0.81 m, respectively.

KOMPSAT-5 is the first satellite in Korea equipped with X-band Synthetic Aperture Radar (SAR) instrument and has been operated since August 2013. The availability of KOMPSAT-5 is highlighted as the need of high resolution wind for coastal monitoring. However, the previous study for the estimated wind from KOMPSAT-5 showed that the accuracy is lower than other SAR satellites. Therefore, in this study, we developed the correction equation of normalized radar cross section (NRCS) for improvement of wind from KOMPSAT-5 and validated the equation compared with the buoy measurements. Theoretical estimated NRCS and observed NRCS showed linear relationship with incidence angle. Before applying the correction equation, the accuracy of the estimated wind speed showed the root-mean-square errors (RMSE) of 2.89 m s-1and bias of -0.55 m s-1. The errors were significantly reduced to the RMSE of 1.60 m s-1and bias of -0.38 m s-1after applying the correction equation.

Hazardous Noxious Substance (HNS) is transported entirely through large vessels, so there is always a potential risk of marine HNS spills. In the event of an HNS accident, it can cause enormous human and property damage, so prompt detection is required. However, there is a limit to human access by ship, we need to use remote sensing data. In this study, ground experiments using hyperspectral cameras were performed to construct a spectral library of HNS. We classified the HNS and non-HNS by applying the hyperspectral mixture algorithm, and presented the HNS detection probability for every pixel by calculating the spectrum-based abundance fraction. The results of this study are expected to be used to estimate the extent of HNS spill in the event of a marine HNS accident.

Wave-current interaction was investigated when the waves traveled through ocean current in the Kuroshio region using satellite altimeter data. The SWH (significant wave height) decreased when the wave propagated in the same direction as current, while the SWH increased when the wave traveled in the opposite direction to the current. The swell-ray model was applied to investigate the modification of SWH according to the wave advection and refraction effect. The wave refraction clearly presented in the current. The convergence (divergence) of the swell-ray was found in the area where the positive (negative) peak was observed in the strong current region.

Sea surface wind is one of the most important factors for waves, ocean currents, ocean circulation, and atmosphere-ocean interactions, and provides a comprehensive understanding of complex marine phenomena. Many researchers have been studying on sea surface wind using scatterometer, and the wind field data from scatteromter is accurate to within ± 2 m/s and 20 °. However, the wind field data from scatteromter have disadvantages such as lack of coastal wind field data and analysis of small scale ocean phenomenon due to low spatial resolution.

Sea surface wind is one of the most important parameters of ocean - atmosphere interaction and affects hear flux, oceanic mixed layer and oceanic surface layer circulation through continuous interaction with the atmosphere. Especially in recent years, due to rapid changes in global environment caused by rapid climate change, sea surface wind plays a major role in the understanding of seawater inflow and exchange processes and marine biogeochemical processes of atmospheric gases.

In this study, we accomplished to detect oil spill from DubaiSat-2 and Landsat OLI data using VIS/NIR channels with high spatial resolution and we classified oil spill in two types, such as thick oil and film-like oil. It is hard to recognize film-like oil even at the field and more complex to discriminate film-like oil than thick oil from the satellite data because it shows similar appearance with sea water color and their widespread distributions. In this respect, it is significant that we has developed the algorithm for film-like oil. And also we figured out the effects of tidal current and wind driven current to the movement of oil spill by particle tracking.

The SAR-derived wind fields presented the detailed structure of wind fields along the coastal areas, which had heretofore been unobtainable from scatterometer observation. Comparison of the retrieved SAR wind speeds with in-situ buoy wind measurements showed a small difference of less than 1 m/s, which implied that the results of SAR wind retrieval satisfied the limit of accuracy of satellite scatterometry. The retrieved SAR wind fields off the east coast of Korea during August 2007 showed the distinct patterns of low wind along the coastal region. The analysis of SAR wind fields with coincided SST images indicated that these spatial distinctions of SAR wind fields were associated with the upwelling events. Based on wind and SST data from satellite data and in-situ measurements, it was found that the changes in MABL stability caused by upwelling events dominantly generated the variation of SAR wind fields at the coastal regions.

For the retrieval of satellite-derived sea surface temperature (SST), an empirical regression algorithm has been widely used so far despite its local bias. Recently, as fast radiative transfer model (RTM) enable near real-time simulations of clear-sky BTs, a hybrid SST algorithm has been suggested, which is based on regression between the incremental values (satellite-observed BT minus first-guess BT, and in-situ SST minus first-guess SST) and scaling procedures. In this study, the hybrid SST was retrieved from Communication, Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data and compared to regression SSTs in the seas around Korea. Comparison with in-situ SST measurements showed that the hybrid SST ensured higher accuracy, especially in nighttime. As nighttime RMSE compared to in-situ SST was improved from 0.88°C to 0.38°C, RMSE for whole matchups was also improved from 0.84°C to 0.45°C for the period of May 2014.

In this study, we investigated the accuracies of SSS in the northwest Pacific Ocean for the recent three years (2012-2014) by comparison with in situ salinity measurements from Argo floats, moored buoys, and many of ship CTD measurements. The satellite SSS errors of the northwest Pacific Ocean presented characteristic dependence on latitudes close to the global ocean but were mostly underestimated at all ranges of SST and wind speed.

RADARSAT-2 is a follow-up to RADARSAT-1 and is an all weather Earth observation satellite with fully polarimetric imaging capability. The synthetic aperture radars (SARs) onboard both RADARSATs are C-band imaging radars and they are well suited for Earth's ecosystem monitoring and maritime surveillance, because of the near polar orbit and their unique all weather imaging capability, independent of solar illumination. In this paper, RADARSAT-2 is first introduced and several applications of various modes of SAR data to coastal zone problems are discussed, including the coastal surface wind, waterline mapping, and polarimetric SAR data inversion for topographic and geological parameters of tidal flats. Coastal zones, the important interface between the land and the ocean, where a large proportion of the world's population inhabits, continuously change and evolve. The dynamic interaction of coastal winds, coupled with the coastal waves and currents, continuously erode rocks and land mass, and move and deposit various sediments on a continuous basis, along with the tides. Estimation of wind speeds and directions in coastal areas are empirically formulated and can further be improved with the available fully polarimetric data from RADARSAT-2. The water line mapping critically depends on the SAR frequency, or the wavelength of the SAR data used, and RADARSAT-2 SAR data using C-band should map waterlines more accurately than the longer wavelength L- or P-band SAR systems. The roughness parameters and partial information on the tidal flat compositions can be obtained from fully polarimetric SAR data. Some results obtained from NASA AIRSAR(2000) L-band data and RADARSAT-2(2008) C-band data do not fully agree with field measurements and further investigation is in progress. The inversion of polarimetric SAR data is a very complex problem and critically depends on the SAR signal frequency and model functions. RADARSAT-2 is an imaging radar, which is very flexible and powerful tool for potential coastal zone applications. Key RADARSAT-2 features and potential coastal zone application capabilities are also briefly reviewed.