As marine transportation has increased in coastal regions, maritime accidents associated with vessels have steadily increased. 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. Various spectral libraries of marine objects and seawaters were constructed through in-situ experiments for spectral analysis of the internal structures of vessels. The hyperspectral images were dimensionally reduced through principal component analysis. 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 N-FINDR and VCA techniques presented a total of 14 vessels, the ICA technique detected seven vessels, and the PPI technique detected two vessels. The pixel-based probability of detection (POD) and false alarm ratio (FAR) for all 14 vessels were 96.40% and 4.30%, respectively. The sizes of the vessels were estimated by extracting the boundaries of the vessels through a two-dimensional gradient and applying the ellipse fitting method. Compared with the digital mapping camera (DMC) images with resolutions of 0.10 m, the root-mean-square errors of the length and width of the vessels were approximately 1.19 m and 0.81 m, respectively. The application of spectral mixing methods provided a high probability of detecting the objects, as well as the overall structures of the decks of the vessels.

With an increase in the overseas maritime transport of hazardous and noxious substances (HNSs), HNS-related spill accidents are on the rise. Thus, there is a need to completely understand the physical and chemical properties of HNSs. This can be achieved through establishing a library of spectral characteristics with respect to wavelengths from visible and near-infrared (VNIR) bands to shortwave infrared (SWIR) wavelengths. In this study, a ground HNS measurement experiment was conducted for artificially spilled HNS by using two hyperspectral cameras at VNIR and SWIR wavelengths. Representative HNSs such as styrene and toluene were spilled into an outdoor pool and their spectral characteristics were obtained. The relative ratio of HNS to seawater decreased and increased at 550 nm and showed different constant ratios at the SWIR wavelength. Noise removal and dimensional compression procedures were conducted by applying principal component analysis on HNS hyperspectral images. Pure HNS and seawater endmember spectra were extracted using four spectral mixture techniques—N-FINDR, pixel purity index (PPI), independent component analysis (ICA), and vertex component analysis (VCA). The accuracy of detection values of styrene and toluene through the comparison of the abundance fraction were 99.42% and 99.56%, respectively. The results of this study are useful for spectrum-based HNS detection in marine HNS accidents.

This study conducted a composite risk assessment to evaluate the environmental impacts of phenol, a Hazardous and Noxious Substance (HNS) released or leaked from port facilities. The study area was designated as the vicinity of Incheon Port, South Korea, where the volume of petrochemical-related materials is substantial and various industrial facilities are located. For the composite risk assessment, various vulnerability maps were developed, incorporating the dispersion range of phenol calculated through numerical modeling. The vulnerability maps were generated by classifying socio-environment, legally protected areas, habitats, and species, followed by integrating these individual vulnerability maps to construct an integrated vulnerability map. The composite risk assessment was conducted by considering both the integrated vulnerability map and the dispersion range of phenol. The assessment results indicated that the highest risk by depth was observed in the lower layers due to the settling characteristics of phenol. Spatially, areas where islands and coastlines converge exhibited relatively higher risks. This was attributed to the high concentrations of phenol released from industrial facilities, such as crude oil refineries, petrochemical plants, and organic compound manufacturers, in regions characterized by intense human activity, sensitive habitats, and legally protected areas. Continuous monitoring of these high-risk areas is crucial for assessing the environmental impacts of HNS substances like phenol.

In this study, variations of radar backscatter features of the tidal channel in Gyeonggi Bay in the Eastern Yellow Sea were investigated using spaceborne synthetic aperture radar (SAR) images. Consistent quasi-linear bright features appeared on the SAR images. Examining the detailed local bathymetry chart, we found that the features were co-located with the major axis of the tidal channel in the region. It was also shown that modulation of the radar backscatter features changed according to the environmental conditions at the time of imaging. For the statistical analysis, the bathymetric features over the tidal channel were extracted by an objective method. In terms of shape, the extracted features had higher variability in width than in length. The analysis of the variation in intensity with the coinciding bathymetric distribution confirmed that the quasi-linear bright features on the SAR images are fundamentally imprinted due to the surface current convergence and divergence caused by the bathymetry-induced tidal current variation. Furthermore, the contribution of environmental factors to the intensity modulation was quantitatively analyzed. A comparison of the variation in normalized radar cross section (NRCS) with tidal current showed a positive correlation only with the perpendicular component of tidal current (r= 0.47). This implies that the modulation in intensity of the tidal channel signatures is mainly affected by the interaction with cross-current flow. On the other hand, the modulation of the NRCS over the tidal channel tended to be degraded as wind speed increased (r= −0.65). Considering the environmental circumstances in the study area, it can be inferred that the imaging capability of SAR for the detection of tidal channel signatures mainly relies on wind speed.