For the foreseeable future, as today, spill response will depend on the ability to trap and remove oil. That reality places heavy importance on the speed and accuracy of detection, because these physical methods, according to Larry Nies, a professor of civil engineering at Purdue University, "are generally most effective if you get there in time and are the first line of defense." 
In practice, the majority of oil spill detection continues to be performed by the least costly method: visual observation from the air, along with still and video photography. But the many critical deficiencies of this approach include limitations on seeing ability imposed by atmospheric and sea conditions, as well as complete inoperability in rain, fog or darkness. The Minerals Management Service (MMS) warns that all estimates of oil thickness and coverage by visual observations "should be viewed with considerable caution."
Increasingly, aircraft-based remote sensors (which work by detecting color, reflectance, temperature, roughness and other sea surface properties) are proving useful in a variety of oil spill detection modes, such as large area surveillance, site specific monitoring, and tactical assistance in emergencies.  Yet, while airborne sensors offer greater accuracy and the advantage of operating beyond the optical spectral region, they are expensive and require highly trained personnel to control the systems and interpret results.
At the top end of spill detection technology, the ideal system: 1. would be completely automatic to reduce operational staff, 2. would be capable of delivering real-time data (including wave and current information) with no need for post-processing, and 3. would be able to see oil spills in the dark, enabling 24-hour vigilance.
In 2005, a Norway-based company developed a system that satisfies some of these requirements by capturing and processing digitized radar images from standard X-band navigation radars. The system features a user-friendly graphical interface that shows the oil spill, its area, velocity and other information valuable for a discovery and recovery operation. This technology is based on the fact that areas covered by oil will reflect less microwave power due to dampening of sea surface capillary waves.  These very short waves, or tiny ripples, are the predominant scatterers of microwave radiation from the ocean's surface. A coating of oil changes the water's surface tension in a way that reduces the presence of capillary waves, resulting in less microwave radiation. So, sections covered in oil show up as dark areas in radar sea surface images. 
Other research seeks to get a jump on detection by accurately predicting slick trajectories using data such as salinity, temperature, bottom pressure, and number and area of the slicks, obtained from an array of orbital satellites. A recently proposed computational methodology uses the Case-Based Reasoning (CBR) methodology to forecast the probability of finding oil in certain open sea areas after an oil spill.  CBR depends on the case base, a database where a collection of problems is stored, keeping a relationship with the solutions to every problem stored, which gives the system the ability to generalize in order to solve new problems and predict outcomes. 
Currently, there are two critical shortfalls in the technical ability to measure and assess the extent of marine environment oil spills. Thickness sensors, which would be valuable as triage tools for targeting the thickest portions first, do not yet exist. Additionally, there is no practical approach to remotely detecting or mapping oil trapped in, under, on or among ice. 
Another fairly recent addition to the spill cleanup team's arsenal is a series of data-gathering buoys and other ocean-based instruments that allow response teams to get a real-time sense of the conditions at sea.
Regardless of the sophistication of the detection system, once government and oil company officials have been notified of a spill, they are dependent on the system's data and analysis to quickly make targeted decisions and immediately deploy the appropriate containment and cleanup measures.
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