A Study on Applications of High-Frequency Optical Satellite Data to Oceanic Disastrous Phenomena : Focused on Oil Spill and Red Tide

Abstract

The spatial distribution of an oil spill and its temporal dispersion within a coastal bay were investigated using high-resolution optical images. A neural network method was applied to Landsat and DubaiSat-2 images to detect the oil spill. We conducted field observations to measure spectral characteristics of the oil spill and the oil-free sea surface. We were able to detect and eliminate pixels corresponding to ships and ship shadows on the satellite image, resulting in successful oil spill detection. A new recursive neural network method using a near-infrared band was developed to classify oil types into thick or film-like oil and to estimate their areal extents. To understand potential causes of the temporal evolution of the oil spill, we performed numerical modeling with atmospheric and oceanic inputs. Overall, trajectories of oil particles controlled by tidal currents showed good agreement with the detection results from satellite data. Slight discrepancies occurred between satellite data and results from the model simulation using only tidal currents, particularly in the southeastward dispersion or in the spreading of film-like oils into the northern inner channels. This was attributed to the effect of wind-driven Ekman drift. This study suggests that tidal currents played an important role in the temporal dispersion of oil in the bay during initial phases, when wind conditions were relatively weak, and that the Ekman drift became the dominant control on oil movement during periods of weak tidal currents and strong winds. Speckles in the suspended particulate matter (SPM) data of the Geostationary Ocean Color Imager (GOCI) were spatiotemporally analyzed. The speckles were classified into four types based on their appearance: isolated speckle, speckle near cloud, patch-type speckle, and slot-related speckle. The spectral characteristics of the speckles were analyzed. We developed a speckle removal procedure to detect the speckles. The speckle removal improved the quality of the GOCI SPM data. We conclude that the speckles were generated by the unmasked clouds edge, water vapor, and small clouds that move during the spectral scanning sequences. From field cruises around the Korean coast, we found that red tide had a bimodal spectral distribution, having two peaks at 555 nm and 680 nm. A red tide index (RTI) algorithm was developed based on in situ spectral characteristics of red tide bloom and validated by in situ red tide measurements. The RTI algorithm was applied to reprocessed GOCI data with speckle removal for the period from 2011 to 2016. The phenology of red tide, such as starting time, ending time, duration, and spatial probability, was estimated using satellite RTI data. Migration and propagation of red tide along and across the coast was investigated spatially and temporally. The relationship between RTI and environmental parameters, such as sea surface temperature, cloudiness, sea surface wind, river discharge, colored dissolved organic matter, Chlorophyll-a, SPM, were clarified.