Remote sensing techniques of oil pollution detection
Space observation has a significant contribution to make routine pollution monitoring. The main strengths of the technique lay in the wide, synoptic coverage that provides consistent results over large areas. Repeatability of results also plays a role in ensuring the usefulness of the image data.
There are three main activities related to management of oil spills in the marine environment in which satellite remote sensing has a role: contingency planning, emergency response and monitoring. Contingency planning for oil spills involves gathering baseline data, identifying economically and environmentally sensitive areas and assessing the availability of facilities and equipment to be used in clean-up efforts should an oil spill occur. Disaster response to a specific oil spill incident involves identification of the location and extent of a spill short-term monitoring of spill. Monitoring program involve frequent imaging of areas where spills or illegal dumping are likely to occur.
The contribution of the earth observing system to routine monitoring of marine pollution can be both directly through observation of the pollutant (e.g. oil in the Yellow Sea or algae bloom near the Korea coast) and indirectly through the dynamic signatures extracted (such as current, eddies, internal waves, etc.) and/or sea surface wind field retrieved to assist modelling the trajectory and evolution of detected pollutants.
Due to the changing environmental conditions, location and properties of the oil slicks and their immediate threat to ecosystem, a satellite remote sensing platform is required to have high temporal and spatial resolution and wide spectral resolution, as the position and width of the spectral band is important in distinguishing the oil from the adjacent water.
Using satellite platforms to monitor oil slicks is more cost effective than applying airborne monitoring techniques and therefore would be beneficial when used in a continuous monitoring role. Satellite-borne sensors, particularly Synthetic Aperture Radar (SAR), provide valuable information; however their frequency of overpass should be improved significantly.
Single sensors are unlikely to provide adequate temporal and spatial coverage at adequate resolution for pollution monitoring; therefore networks of sensors are required which are coordinated in terms of the data formats, quality control information and distribution, in addition to initial acquisition. In the marine environment, conditions change rapidly and features are frequently obscured by cloud, thus requiring multiple looks. Systematic, routine monitoring of marine pollutants and the dynamic processes (fronts, currents, eddies, etc.) that transport them require inputs of microwave, infrared (IR) and visible data in ways that take advantage of their respective strengths. Although earth observation has definite strengths, it has weaknesses too and these must be addressed when considering the monitoring of a cloud-covered sea with optical or IR data or looking for oil slick in predominantly calm or gale wind locations with SAR.
With regular passes over oceans, satellites are useful to get statistical information: slicks are observed all over the world seas. For example, study with 1600 ERS SAR images taken over the Mediterranean Sea showed that a half of the images presents at least one slick. Similar estimates were obtained for the Baltic Sea and for the South-East Asia area. Counting every kind of slicks, 10% of ocean surface is estimated to be covered by slicks.
Crude and heavy refined oils have three optical properties which vary slightly from oil to oil, and which make them detectable at sea by optical sensors:
These properties make it possible, not just to detect oil spilt at sea, but also to determine the thickness of the oil layer, and to classify surface oil into broad categories such as light refined, light crude, heavy crude and heavy refined oil. This information is available because the presence of oil modifies the signal received from the sea-water by increasing surface reflection, reducing the signal from the underlying water and adding a contribution from solar induced fluorescence from and scattering by water-droplets in the oil layer and from oil droplets within the water. As a result the interpretation of optical data from oil spills require careful consideration of the viewing angle and the background conditions, particularly the properties of the underlying water, the incident light conditions and, in shallow water, depth and the bottom type.
- Their refractive index is greater than that of seawater
- Their coefficient of light absorption is much stronger than that of water, particularly at shorter wavelengths
- They fluoresce when subjected to bright natural light
Applications for airborne remote sensing of oil using for example an Airborne Imaging Spectrometers at Visible and Near-infrared Wavelengths include the surveillance of routine tanker and off-shore operations, reconnaissance in support of major oil spill response, and the collection of information needed in order to assess the environmental impact of pollution incidents. Information required includes:
Reliable identification of surface oil is only possible if the difference in measured radiance between an oil covered and a clean surface is greater than the background variability. Contrast may be either positive or negative. Very thin layers of oil (a micron or less) are usually brighter than water (positive contrast), particularly in the violet and in the red to near-infrared. Thicker layers of crude oil, on the other hand usually appear darker than water in the visible part of the spectrum, and brighter than water in the near-infrared. Exceptions to this rule do occur, for instance when the water contains a high concentrations of sediments or plankton algae.
- Position and extent of surface oil
- Thickness of surface oil
- Oil type and physical properties
- Position and extent of dispersed oil
Information about areas of surface oil is usually more reliable if a combination of optical and thermal infrared sensors is used.
An infrared (IR) radiometer measures the brightness temperature of the atmosphere-ocean system TB(∆ν) at a spectral interval ∆ν. The TB(∆ν) consists mainly of three components:
Oil shows a number of thermal properties, which can make it distinguishable from seawater. These include a unique heat capacity, thermal conductivity and thermal inertia, (which also change due to the mixing effects of oil and water, emulsifying and weathering). The difference in the thermal properties of oil and seawater allow potential discrimination by the thermal channels aboard remote sensing platforms. The oil film will show a larger diurnal temperature range than the surrounding seawater. The thermal characteristics of oil means that it will become 'visible' on thermal channels during afternoon images; this is due to the fact that oil will act as a black body, absorbing heat and becoming warmer than the surrounding sea water. During the night, the opposite is true; the oil body will loose heat faster than the surrounding water, which is shown as a cooler region on the images. Thinner slicks show a temperature pattern similar to seawater, because the oil is heated by the underlying water body. Thermal gradients can be weakened over time, due to the mixing of the oil with water; therefore the monitoring in the thermal channels will lead to ambiguous results.
- the brightness temperature of the ocean surface attenuated by the atmosphere,
- the brightness temperature of the upwelling atmospheric radiation T↑Batm and
- the brightness temperature of the downwelling atmospheric radiation T↓Batm reflected by the ocean and attenuated by the atmosphere.
- The brightness temperature of the ocean surface TBO(∆ν) = TSK(∆ν) relates to the thermal emissivity of a substance K(∆ν). At ∆ν = 10-13 m the emissivity of oil is assumed as ~0.97, and the emissivity of water as 0.99. Assuming that oil has the same physical temperature TS as the water, the lower temperature as seen on the image is consistent with differences in emissivity. To distinguish the oil slick from the surrounding water during the day, the increase in physical temperature must exceed the emissivity difference, if the slick is to be discriminated from the surrounding water. This would be problematic in high latitude areas, particularly in the winter months when the solar radiation is low.
Thermal fronts and upwelling in the ocean could be potentially mistaken for oil slicks. There have been many conflicting reports regarding the success of thermal channels to detect the oil slicks. What is clear, the difference in the thermal characteristics between oil and water provide the means by which the two can be discriminated readily.
There are several airborne remote sensors for application to oil spill detection/assessment. A common sensor is an IR radiometer or an IR/ultraviolet (UV) system. This sensor class can detect oil under a variety of conditions, discriminate oil from some backgrounds and has the lowest cost of any sensor. The inherent weaknesses include the inability to discriminate oil among weeds or debris and under certain lighting conditions, oil is not detected. Furthermore, water-in-oil emulsions are sometimes not detected in the infrared. New technology has made IR technology very cheap and practical, so despite its limitations, it will be a very important tool in the future. The laser fluorosensor is a most-useful instrument because of its unique capability to identify oil on backgrounds that include water, soil, weeds, ice and snow. It is the only sensor that can positively discriminate oil on most backgrounds. Disadvantages include the large size, weight and high cost.
The microwave range of the electromagnetic spectrum can be used effectively to measure many variables and phenomena central to the research and monitoring of oil pollution. The passive instruments (radiometers), carried by satellites, are particularly valuable over the open oceans since they give global coverage and many microwave frequencies penetrate clouds. This permits measurements of sea surface and atmospheric properties influencing on oil spill behaviour and transport in all weather conditions. Detection of oil films from satellite altitudes is now impossible due to large field of view (pure spatial resolution) of microwave radiometers. Operation of these instruments from aircraft and from ships and platforms provides the high resolution data that allows oil spill detection and monitoring. Physical base for oil spill detection by microwave radiometer is the difference in emissivity of the polluted and clean areas of the sea surface. For calm sea, this difference is only due to the fact that dielectric permittivity of oil products is less than that of the sea water. For rough sea, the changes in emissivity are also due to the changes of the sea surface roughness: oil slicks damp small scale roughness that in turn causes the decrease of emissivity of the slick areas against the background.
Think slicks (oil layer thickness d < 30-50 mkm) (they are formed at low-volume oil discharges and as well as observed in the periphery zones of the large-volume discharges) do not change emissivity of the calm sea surface. At the presence of roughness, however, think slick areas are characterized by the reduced emissivity. The emissivity of thick oil films (d > 50 mkm) is a function of oil dielectric permittivity and thickness d. (Of course it depends also on frequency, polarization and incidence angle of the radiometers). Since the emissivity is an oscillating function of d (due to interference of waves reflected from the air-oil and oil-water boundaries) and the period of oscillation decreases with the increase of frequency, 2-3 microwave radiometers operating at different frequencies are used to estimate oil layer thickness.
It is necessary to emphasize that the brightness contrasts of the polluted sea surface against the surrounding clean waters depend both on the slick area brightness and on the atmospheric brightness temperature and absorption.
Synthetic Aperture Radar (SAR) is an effective tool well adapted to detect surface pollution and can fill the lack of pollution survey which affects seas and coasts. SARs image oil slicks allowing estimation of the pollution risk in coastal areas. SAR images can be acquired through clouds unlike infrared or optical images.
The SAR sensor probes variations of the short gravity-capillary waves. These waves are very sensitive to the highly variable dynamics, of the atmospheric boundary layer and of the upper sea layers. So, the SAR image can be regarded as an instantaneous imprint of the traces of these dynamics on the sea surface. Since their lateral variations are expressed also as gray scale variations on the single band SAR image, they may result into complicated sceneries, posing thus difficulties in the identification of man-made oil spills. To this end the experience of the interpreter and especially its ability to apprehend the nature of the imaged manifestations, becomes a critical factor. As such experience however is not widely available, efforts are in progress, for the development of systems, which may facilitate the detection and identification of man-made oil spills in an automatic or at least in a semi-automatic way (Levett and Sullivan, 1993; Wahl et al, 1994; Calabresi et al, 1999).
Wave damping, function of slick nature, is more important for oil slicks than for natural films. The higher the elasticity, the higher the image contrast is, but there is no linear relation. Therefore, it is not easy to distinguish slick nature with contrast. Thickness is also related to slick nature: oil slicks are thicker than natural films. Otherwise, a radar measurement limitation is that slicks can only be detected if they are "new" slicks (radar wave does not penetrate ocean surface), and they are quickly carried in subsurface, due to wave mixing.
SAR measurement is also limited to sea state related to meteorological conditions. When there is not enough wind like in the lee of costal mountains or an island, capillary waves are not created, radar backscattering becomes weak, and contrast is insufficient. Otherwise, so much wind induces an important backscattering and thus contrast decreases. Moreover, waves induced by strong wind quickly drag slicks in the ocean sub-surface, where it can not be detected. Some other conditions like oceanic internal waves for example, quickly distort slicks which become less dense, thus less easy to be detected.
For correct SAR measurement, the wind speed has to be higher than 2-3 m/s, the upper wind speed value is less obvious to show, but some images have been made up to 10-14 m/s. In other way, wind is a limitation for natural film generation, which can only exist for wind speed up to 3-5 m/s, it can help for classification step for wind higher than these values.