Influence of Dispersed Oil on the Remote Sensing Reflectance—Field Experiment in the Baltic Sea

Abstract

Remote sensing techniques currently used to detect oil spills have not yet demonstrated their applicability to dispersed forms of oil. However, oil droplets dispersed in seawater are known to modify the local optical properties and, consequently, the upwelling light flux. Theoretically possible, passive remote detection of oil droplets was never tested in the offshore conditions. This study presents a field experiment which demonstrates the capability of commercially available sensors to detect significant changes in the remote sensing reflectance Rrs of seawater polluted by six types of dispersed oils (two crude oils, cylinder lubricant, biodiesel, and two marine gear lubricants). The experiment was based on the comparison of the upwelling radiance Lu measured in a transparent tank floating in full immersion in seawater in the Southern Baltic Sea. The tank was first filled with natural seawater and then polluted by dispersed oils in five consecutive concentrations of 1–15 ppm. After addition of dispersed oils, spectra of Rrs noticeably increased and the maximal increase varied from 40% to over three-fold at the highest oil droplet concentration. Moreover, the most affected Rrs band ratios and band differences were analyzed and are discussed in the context of future construction of algorithms for dispersed oil detection.

Semi-Empirical Model of Remote-Sensing Reflectance for Chosen Areas of the Southern Baltic

“…The analysis based on the optical model of the Sea Basin identified the most universal spectral index of Rrs for 555 nm/440 nm for dispersed oil detection using any optical parameters [15]. The impact of absorption coefficient (a(λi)) and backscattering coefficient bb(λi ) on Rrs(λi ) is highly variable, thus the interpretation of reflectance spectra requires a simultaneous multi-parameter analysis of light propagation in seawater [16,17].…”

“…aph(620)cal = 0.008(Chl a) 0.926 , (10) ad(420)cal = 0.071(SPM) 0.809 , (11) ad(488)cal = 0.045(SPM) 0.762 , (12) ad(555)cal = 0.031(SPM) 0.646 , (13) ad(620)cal = 0.002(SPM) 0.592 , ( 14) bbp(420)cal = 0.011(SPM) 0.911 , (15) bbp(488)cal = 0.008(SPM) 0.891 , ( 16) bbp(555)cal = 0.007(SPM) 0.935 , (17) bbp(620)cal = 0.005(SPM) 0.881 . (18) Relationships between aCDOM(λi) and aCDOM(400) (Equations ( 19)-( 22)) are well approximated by second order non-linear exponential functions: .…”

OS-BREEZE: Oil Spills Boundary Red Emission Zone Estimation Using Unmanned Surface Vehicles

“…The emergence of remote sensing techniques, which utilize satellite, aircraft, or drone sensing [ 7 , 8 , 9 , 10 ], enable oil spill detection efficiently without the need for in situ sampling. Effective oil spill surveillance is essential for managing oil spill events, and remote sensing technology can help to identify spills early before they cause significant harm.…”

Monte Carlo Radiative Transfer Simulation to Analyze the Spectral Index for Remote Detection of Oil Dispersed in the Southern Baltic Sea Seawater Column: The Role of Water Surface State

“…Oily substances may be under the surface of the water, both as a result of the influence of the environment and the deliberate transfer of oil from the form of a floating layer on the surface of the water to the submerged form, which is justified in terms of ensuring easier access for oil-decomposing bacteria, but may also be dictated by a desire to hide illegal oil discharge. In any case, there is a need to conduct research on the efficiency of substances supporting the dispersion of oil [1] and research on the possibility of detecting oil contamination in the form of an emulsion [2,3].…”