Estimation of hazardous and noxious substance (toluene) thickness using hyperspectral remote sensing

Abstract

A hazardous noxious substance (HNS) spill accident is one of the most devastating maritime disasters as it is accompanied by toxicity, fire, and explosions in the ocean. To monitor an HNS spill, it is necessary to develop a remote sensing–based HNS monitoring technique that can observe a wide area with high resolution. We designed and performed a ground HNS spill experiment using a hyperspectral sensor to detect HNS spill areas and estimate the spill volume. HNS images were obtained by pouring 1 L of toluene into an outdoor marine pool and observing it with a hyperspectral sensor capable of measuring the shortwave infrared channel installed at a height of approximately 12 m. The pure endmember spectra of toluene and seawater were extracted using principal component analysis and N-FINDR, and a Gaussian mixture model was applied to the toluene abundance fraction. Consequently, a toluene spill area of approximately 2.4317 m2 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. Because toluene has a maximum extinction coefficient of 1.3055 mm at a wavelength of 1,678 nm, the closest 1,676.5 nm toluene reflectance image was used for thickness estimation. Considering the detection area and ground resolution, the amount of leaked toluene 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%. Previous studies on HNS monitoring based on remote sensing are lacking in comparison to those on oil spills. This study is expected to contribute to the establishment of maritime HNS spill response strategies in the near future based on the novel hyperspectral HNS experiment.