Enhanced oil spill detection sensors in low-light environments

Abstract

Although advances have been made in oil spill remote detection, many electro-optic sensors do not provide real-time images, do not work well under degraded visual environments, nor provide a measure of extreme oil thickness in marine environments. A joint program now exists between BSEE and NVESD that addresses these capability gaps in remote sensing of oil spills. Laboratory experiments, calibration techniques, and field tests were performed at Fort Belvoir, Virginia; Santa Barbara, California; and the Ohmsett Test Facility in Leonardo, New Jersey. Weathered crude oils were studied spectroscopically and characterized with LWIR, and low-light-level visible/NIR, and SWIR cameras. We designed and fabricated an oil emulsion thickness calibration cell for spectroscopic analysis and ground truth, field measurements. Digital night vision cameras provided real-time, wide-dynamic-range imagery, and were able to detect and recognize oil from full sun to partial moon light. The LWIR camera provided quantitative oil analysis (identification) for >1 mm thick crude oils both day and night. Two filtered, co-registered, SWIR cameras were used to determine whether oil thickness could be measured in real time. Spectroscopic results revealed that oil emulsions vary with location and weathered state and some oils (e.g., ANS and Santa Barbara seeps) do not show the spectral rich features from archived Deep Water Horizon hyperspectral data. Multi-sensor imagery collected during the 2015 USCG Airborne Oil Spill Remote Sensing & Reporting Exercise and the design of a compact, multiband imager are discussed.

Oil Spill Detection Using Machine Learning and Infrared Images

“…In the Short Wave Infrared (SWIR) band (1000-1700 nm), crude oil has a different reflectance spectrum when compared to water [24]. The use in low light conditions is tested in [25], and it has been proven to be successful. The high cost and the limited commercial availability is the downside of this solution.…”

The Challenges of Remotely Measuring Oil Slick Thickness

“…The reflectivity measurements presumed that reflectivity was greatest for the thickest oils, however other studies show this is not the case. Allik et al measured the reflectivities of two oils and one emulsion, and the results showed that reflectivities varied [44]. The Alaska North Slope (ANS) crude showed lesser reflectivity than its emulsions.…”

“…Allik et al carried out a reflectivity study of oils and emulsions of various thicknesses over the range of 300 to 2300 nm [44]. It was noted that the spectra were very similar in the visible range, but the emulsions had higher reflectivity in the spectral region of 900 to 2300 nm (SWIR).…”

“…Allik et al carried out a series of tests on a small pool using long-wave thermal imagery [44]. Oils of various thicknesses were imaged over several hours, including into the night.…”

Determination of Crude Oil Thickness at Night Using Thermal Imagery

“…When discussing the challenges of measuring oil slick thickness, Fingas could not find consistent spectral signatures to gauge oil slick thickness [1]. In contrast, the long wave infrared (LWIR) atmospheric window has been used for the identification of millimeter oil spills [8][9][10][11][12]. Oil spill detection with uncooled, inexpensive microbolometers is well established and relies on capturing thermal radiation, not filtered spectra.…”