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Overview and future trends in oil spill remote sensing
Spill Science & Technology Bulletin, Vol. 1, No. 1, pp. 11-21, 1994
Pergamon
Elsevier Science Ltd
1353-2561(94)00003-4
Printed in Great Britain 1353-2561/94 $7.00+0.00
Overview and Future Trends in Oil Spill Remote Sensing RON GOODMAN
Research and Technology, Imperial Oil Resources Limited, Calgary, Alberta T2L 2K8, Canada (Tel: 403 932 4331; Fax: 403 932 4263)
Remote sensing has great potential to provide data to improve oil spill response efforts. There are a number of sensors available that have been proven capable of detecting oil on water and measuring some of its properties. There is no single sensor that provides all the data needed, and hence a combination of sensors must be used. Even if finances and aircraft load capacity were unlimited, there are still many parameters of an oil slick that cannot be measured by remote sensing. This paper describes the currently available sensors and their method of operation and outlines some new developments that have the potential to increase the amount of data available from an airborne remote sensing operation.
Surveillance and tracking of oil spills has been a feature of most spill response situations for many years. The simplest and most direct method uses visual observations from an aircraft and hand plotting of the data on a map. This technique has proven adequate for most small spills. The results of the observations are typically presented orally using maps produced during the flight. In recent years, a variety of remote sensors have been developed for the detection of oil on water and on shorelines (Goodman, 1992). All of the remote sensing systems use some form of electromagnetic radiation to detect the oil. The atmosphere is a good absorber for much of the electromagnetic spectrum, and remote sensing systems must operate using the few transparent windows as shown in Table 1 and Fig. 1. These bands represent regions of the electromagnetic spectrum where the atmosphere has an attenuation of
less than 1 d b m - 1 and hence are suitable for remote sensing (Preissner, 1979). The effects of weather for wavelengths greater than 1 mm should be noted: infrared, visible, and ultraviolet sensors will not detect oil through thick fog or heavy rain.
Present State-of-the-Art The present state-of-the-art in the detection of oil on water relies to a large extent on visual observations, supplemented by sensors that extend the spectrum of visual observation. These involve image-producing systems that operate in the thermal infrared (TIR), midIR (MIR), near IR (NIR), and ultraviolet (UV) bands.
Visual observations The most commonly used visual detector is the
Table 1 Remote sensing bands.
Band
Wavelength
Types of instruments
Radar Passive microwave Thermal infrared (TIR) Mid-band infrared (MIR) Near infrared (NIR) Visual Ultraviolet
1-30 cm 2-8 mm 8-14 #m 3 5/~m 1 3/~m 350-750 nm 250-350 nm
SLAR/SAR Radiometers Video cameras and line scanners Video cameras and line scanners Film and video cameras Film, video cameras and spectrometers Film, video cameras and line scanners 11
R. GOODMAN 1000 Fog (0.1 g/m
3)
Visibility 50 m 100
~
10
Heavy rain (25 mmJh)
Drizzle (0.25 mm/h)
o.1 I I
d IR
*%%O,,o*,,°,oO.OoO \
Submillimeter 0.01 10GHz 3 cm
Mid IR
t
\ \
100 3 mm
1 THz 0.3 rnm
10 30 p
100 3.0 p
1000 0.3 p
Near IR
Microwave q
Frequency Wavelength
Visible
"In many cases, region below band ~ = ~ e n t s almosphedc windows for aJrbsee sensing
Fig. 1 Atmospheric windows.
human eye. With the exception of a very narrow range of oil thicknesses where interference patterns can occur, the appearance of oil on water varies from a silver-grey to brown and changes in apparent colour occur over a range of several orders of magnitude in the oil thickness. The lack of strong spectral features means that most passive visual detectors are not well adapted to the detection of oil on water. The skilled visual observer uses changes in the texture of the surface and pattern recognition, and not colour to identify oil slicks. A problem with most visual observations is the interference caused by sun glitter. At low sun angles, the rough ocean surface reflects the solar radiation and hence obscures the presence of the oil.
Infrared imaging systems There are three somewhat distinct bands in the infrared in which the atmospheric transmission is sufficiently low to allow detection from an airborne platform. Tests of all three of these regions were conducted a number of years ago to determine which of the regions is the most suitable for remote sensing (O'Neil et al., 1983). The cost of systems operating in the infrared is lowest for the near IR, with an increase by a factor of five for mid-IR cameras, and a further increase by a factor of three for cameras operating in the thermal IR. There are two factors that allow oil to be detected on water using an infrared sensor: the oil and water are 12
actually at a different temperature, or there is an emissivity difference between oil and water that produces an apparent temperature difference even though the oil and water are actually at the same temperature. It is only in the thermal IR that the emissivity of oil (0.93) and water (0.98) is sufficiently different that an image can be produced. In the other two bands, the oil and water must be at a different temperature in order to be detected. This implies that there must be some source of external radiation, either naturally from the sun or supplied by the instrument.
Near 117 (NIR) (1-3 lun). There are two types of equipment that have been developed for operation in this band. The one system uses a simple detector and illumination system (Wright & Wright, 1973). It has a response time of several seconds and a range of a few tens of meters and thus is not suitable for remote sensing. The other system is a video imaging detector that operates like a video camera and depends on an external excitation source. The contrast between oil and water in this band is low, and there are a number of interferences due to chlorophyll and water vapour bands in this part of the spectrum. The camera version of these systems has a slow response time and requires high ( > 1°C) temperature differences to produce any contrast. The advantages of near infrared systems are: I. they are uncomplicated to operate and the interpretation of the output is relatively simple; Spill Science & Technology Bulletin 1(1)
FUTURE TRENDS IN REMOTE SENSING 2. they are light and consume little power and are suitable for mounting in aircraft of opportunity; and 3. they are the least expensive of the infrared systems. The disadvantages of near infrared systems are: 1. they cannot penetrate cloud; 2. they cannot operate at night; 3. they produce many false targets from plant material; and 4. they lack contrast, which makes the image difficult to interpret.
Mid-band infrared systems ( M I R ) (3-5 Itm). As with the near IR systems, the mid-band IR systems depend on actual temperature differences to detect the presence of oil on the water. In this band, there are very few interferences, and cameras are available that can detect temperature differences as small as 0.02°C. This high sensitivity allows the detection of small amounts of oil on water, under daylight conditions. The main interference with these systems is the small-scale temperature changes that occur owing to the complex circulation patterns in the ocean. These are poorly understood and
can produce patterns that might be confused with oil. A typical output from a mid-band IR detector is shown in Fig. 2. The advantages of mid-band infrared systems are: 1. they are uncomplicated to operate and the interpretation of the output is relatively simple; 2. they are light and consume little power and are suitable for mounting in aircraft of opportunity; 3. a wide variety of lenses are available for these systems; and 4. they are a moderately expensive infrared system. The disadvantage of mid-band infrared systems are: 1. they cannot penetrate cloud but can penetrate light fog; 2. they cannot operate at night; 3. they produce some false targets caused by ocean circulation patterns; and 4. they cannot be used through a window of an aircraft. Thermal infrared systems ( TIR) (8-14 l~m). Thermal infrared detectors provide a two-dimensional image,
Fig. 2 Mid-band infrared output.
Spill Science & TechnologyBulletin 1(1)
13
R. GOODMAN whose density is a function of the surface temperature of the scene, using two-dimensional solid-state arrays and a real-time processor. All thermal infrared systems require cooling the detector to liquid air (nitrogen) temperatures using either a Joule Thompson or a Stirling cycle engine. For slicks of thicknesses between 50 and 500 ~tm, the oil appears to be at a lower temperature than the surrounding water. While slicks of these thicknesses are at the same actual temperature as the water, the oil is a less effective emitter than the water and hence appears cooler. It is possible to maintain a significant real temperature difference between oil and water if there is sufficient oil thickness ( > 500 #m) to insulate the upper layers of the oil from the water. The thermal infrared system will not detect thin sheens but can differentiate between two levels of oil thickness with the transition between 'hot' oil and 'cold' oil at about 500 ktm. The detection of the oil does not depend on solar radiation, so a thermal infrared detector can operate both day and night. Since water vapour is a good absorber of the signal, an infrared system cannot be used through cloud. There is little difference in the infrared emission characteristics of various types of crude oil, but there are large differences between oil and other naturally occurring objects in the ocean. The infrared detector provides discrimination between oil and other materials. There is a wide variety of thermal infrared systems. Detectors such as pyroelectric vidicon and thermocouple detectors have been developed for other purposes. While such systems have an attractive price, they do not have suitable sensitivity to detect oil on water. Acceptable systems for detecting oil on water must detect temperature differences of less than 0.2°C. Most systems produce a standard television output, which can be displayed on a TV monitor and recorded, using a video tape-recorder. Using this method of output, it is easy to obtain and record an image in a compact format. If further analysis of the image is required, the TV format must be converted into a computer-readable format. This requires the use of a frame grabber. A thermal infrared system output is shown in Fig. 3. The advantages of thermal infrared systems are: 1. they are uncomplicated to operate and the interpretation of the output is relatively simple; 2. they are light and consume little power and are suitable for mounting in aircraft of opportunity; 3. they can operate both day and night; 4. they can easily differentiate between oil and other natural objects; 5. they can distinguish between sheen and thick oil and detect thickness gradients; and 6. they are relatively inexpensive, but are the most costly of the infrared systems. The disadvantages of thermal infrared systems are: 14
Fig. 3 Thermal infrared output. I. they cannot penetrate cloud, but can penetrate light fog; 2. they cannot measure absolute oil thickness; 3. the application of dispersant causes significant changes in the emissive properties of the oil and can confuse the interpretation of the images; and 4. there are few materials that are transparent to infrared and hence the detector must be either mounted without a window or by using a germanium window, which is very expensive and not readily available. Ultraviolet
It is difficult to differentiate oil visually from other naturally occurring materials. In the ultraviolet, the reflectivity of oil and water are different, and this forms the basis for the detection of oil in the ultraviolet. The reflectivity ofoil in the ultraviolet is 1.02, whereas that of water is 0.722. Since reflectivity is a surface phenomenon, any hydrocarbon on the surface, independent of thickness, will be detected. It is the sheen that is detected by ultraviolet sensors. Most UV systems use a standard television camera with a suitable filter package. The filters have a passband of 0.25q).35 #m and are used in combination with a polarizer to eliminate glare. A typical ultraviolet image is shown in Fig. 4. The advantages of ultraviolet systems are: 1. they are simple, lightweight, and require little power; 2. they are suitable for mounting in aircraft of opportunity; 3. they produce a video output that is simple to display and record; and 4. they are relatively inexpensive. The disadvantages of ultraviolet systems are: I. they detect the presence of any hydrocarbon on the water surface and cannot differentiate between sheen and thicker oil slicks; and 2. they can only operate under daylight conditions with clear visibility. Spill Science & Technology Bulletin 1(1)
FUTURE TRENDS IN REMOTE SENSING
Fig. 4
Ultraviolet output.
Radar SLAR (Side Looking Airborne Radar) has been used to observe the distribution of floating oil. This is a special type of imaging radar and is quite different from standard marine and airborne radar systems. A SLAR image is formed by the reflection of radar signals from small gravity and capillary waves. These waves are the little ripples or 'cats paws' that can be seen over any water surface when the wind blows. The oil spill is visible to the radar because a very thin film of oil suppresses these small waves and the sea surface appears smooth, both visually, and to the radar. Thus, there is less radar signal return from these regions, and the oil slick shows as a dark region on the image. A film as thin as a few microns can suppress capillary waves (Nithack & Witte, 1984). There is both an upper and a lower limit of wind speeds needed to produce a significant radar return. Under low wind-speed conditions, there is very little wind-stress and any area will be fiat and have a low reflectivity to radar. The radar image would indicate that there is oil everywhere. The low wind cut-off appears to be between 2.5 and 5 m s-1. This limit is dependent on the presence of organic materials on the sea surface. Above this lower limit cut-off, the windstress is sufficient to rupture the naturally occurring organic slicks and hence provide a method of discrimination between oil and water. At wind speeds greater than 10 m s- 1, the wind-stress is sufficient to tear up the oil slick into small patches of a size less than the radar resolution. In terms of oil spill response, skimmers and in situ burning are most effective at sea-states lower than the lower limit of radar detection. A typical SLAR image is shown in Fig. 5. The advantages of SLAR systems are: 1. they can operate under all weather conditions and readily penetrate cloud; and Spill Science & Technology Bulletin l(1)
Fig. 5
SLAR image.
2. aircraft with SLAR can fly at high altitudes and can cover large areas quickly. The disadvantages of SLAR systems are: I. the systems are heavy and require a large externally mounted antenna; 2. they are quite expensive; 3. one of the major problems with using SLAR imagery to track oil spills is that there are a number of targets that can lead to false returns. At wind conditions near the lower limit, such ocean features as wind shadows, freshwater fronts, plankton blooms, and kelp beds can produce images that are difficult to distinguish from that of oil on water. Wind shadows from shore features are hard to differentiate from the presence of oil; and 4. the ability to generate an image of an oil slick is strongly dependent on surface wind conditions. Drifter buoys Although not a remote sensing technique, a common method of following an oil spill is to deploy specially designed buoys into the spill, near the source. The design of the buoy hull is very critical to its ability to follow the oil (Roddis, 1982). An oil slick on the open ocean has a thickness of a few millimeters and moves with the ocean surface. All buoys protrude above the water surface and are thus subject to different wind regimes. Similarly, the effects of near-surface ocean currents cause the buoys to 15
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R. GOODMAN
follow the slick to a day or less (Costanzo, 1994). A typical modern tracker buoy is shown in Fig. 6.
Future trends
gies have been developed to measure oil thickness; one using microwave radiometers, and the other, using a laser-acoustic measurement system. Microwave radiometer
Existing remote sensing technology can detect the presence of oil, and give some indication of its relative thickness. Two parameters are needed to provide additional information to the response effort: the thickness of the slick, and the nature and identity of the oil. The volume of oil can be determined from the thickness and the area of the slick. It is important to characterize the oil in order to optimize the response tactics and to identify the source of the spill. With curent systems, it is possible to measure the area of the spill. This information has limited value, since it is the volume of the oil on the water that is useful to the managers of the spill response. Two separate technolo-
Microwave radiometers are passive sensors that measure the naturally emitted and reflected radiation from the ocean surface. There are significant differences between the emissivity and reflectivity ofoil and water. If the wavelength is chosen to be longer than the oil thickness, then it is possible to measure the relative thickness of the oil film. Typical microwave radiometers operate in the 5-94 G H z region of the spectrum (Hollinger, 1974). A typical image is shown in Fig. 7. The advantages of microwave radiometers are: 1. they have all-weather operational capability, except when heavy rain is present; and
Fig. 6 Moderntracker buoy.
Q.
E
#
¢1 rE O) L.. m
245 E
g
139
¢~
12
11 10 7 Tank #
4
1.0 0.0
Fig. 7 Microwave radiometerimage. 16
Spill Science & Technology Bulletin 1(1)
F U T U R E T R E N D S IN R E M O T E S E N S I N G
2. they are an imaging system with the potential to measure relative thickness.
of laser and acoustic technologies. The main properties of oil that are used in this measurement are its acoustic or mechanical properties, which are very different from the electromagnetic and optical properties that are normally associated with remote sensing. A pulse of energy supplied by the laser impacts on the oil film causing local heating. This local heating causes the oil to expand, and a dome-shaped protrusion forms at the surface. The vertical component of the deformation is proportional to the thickness of the oil. This change in height or the rate of change of the height can be detected by using another laser and a Fabry-Perot interferometer (Brown et al., 1994a). A typical output is shown in Fig. 8. The advantages of a laser-acoustic system are:
The disadvantages of microwave radiometers are: 1. they require a special antenna and hence a dedicated aircraft; 2. they are expensive and complex to operate and maintain; 3. there is limited experience with microwave radiometers in field situations; and 4. limited spatial resolution causes averaging over a large area of the slick. Oil slick inhomogeneities are smaller than the sensor footprint (Hurford, 1985; Goodman, 1994a), which results in the determination of the average value of the oil thickness integrated over a large area.
1. it can measure the absolute thickness of the oil without ambiguity, and requires only a knowledge of the thermal properties of the oil. These properties are similar for a wide variety of oil types; and 2. it is an active system and can operate both day and night.
Laser-acoustic oil thickness sensor A laser-acoustic oil thickness sensor is an absolute thickness measurement system that uses a combination surface signal
2.5--
first echo
2.0-
second echo
=. 1.5
m E i1)
Laser-ultrasonic signal
/
E
Surface displacement
~ 1.oQ.
f
~5
0.5--
0.0
I
2
: l l l r r l l l l r l
J[I
3
4
5
6
I~lF 7
I 8
• m e (psec) Fig. 8
Laser acoustic output.
Spill Science & Technology Bulletin 1(1)
17
R. G O O D M A N
The disadvantages of the laser-acoustic system are 1. it is large and needs a significant amount of power; 2. it cannot penetrate cloud or fog; and 3. it has not been field prove.
Laser fluorosensor If the oil can be excited, using intense ultraviolet radiation from a laser, a fluorescence return, which is unique to the presence of oil on the water surface, can be detected in the visible. The laser fluorosensor is a complex instrument that can identify and classify the presence of oil on water and shorelines. The main background radiation that interferes with the detection of oil is the contribution of suspended phytoplankton or dissolved organic matter (Gelbstoff). This generates a broad spectrum return in addition to a specific return from chlorophyll at 685 nm. Laser fluorosensors are nadir systems, which produce a line scan as a result of the forward motion of the aircraft. A laser is used to excite the oil. There are two characteristics of the visible return spectrum that can be used to detect the presence of oil: spectral analysis and decay time (Brown et al., 1994b). A multi-channel spectrometer is used to analyse the spectral characteristics of the return signal. From this spectral information, the presence of oil can be determined for both water and shoreline situations.
An alternative method of identifying the oil is the use of the decay characteristics of the fluorescence. Since typical decay times are 1-20 ns, the exciting pulse should be less than 1 ns and the return system needs to have a bandwidth in excess of 1 GHz. In most systems, these bandwidths are achieved, using time domain optical systems, rather than coventional electronic methods. An analysed output is shown in Fig. 9. The advantages of laser fluoresensors are: 1. they are active systems and hence can operate both day and night; 2. they can positively differentiate oil from other surface materials and can provide an indication of the type ofoil on the water; and 3. they can detect oil on shorelines. The disadvantages of laser fluorosensors are: 1. they are generally bulky and require a significant amount of power; 2. they are presently point detectors; and 3. they operate in the UV and visible bands and hence cannot operate under conditions of fog or cloud. Data communication
Once the data have been collected by a remote sensing system, they must be communicated to those who can use it. Current technology involves the presentation of
LEAF 3-D F l u o r e s c e n c e Spectra CFB P e t a w a w a May 7, 1993 Flight 6, Pass 2
~Path °r..¢
)===4
Fig. 9 18
Laser fluorosensor.
Spill Science & Technology Bulletin 1(l)
FUTURE TRENDS IN REMOTE SENSING
these data on a map, which is used for briefing the spill response organization. The preparation of the map is a time-consuming process and reduces the immediacy of the data. Since remote sensing operations are clientdriven, care must be taken to ensure that the data are available to those who need them in a timely manner and in a suitable format. One of the methods of reducing time delays for the users is the transmission of the imagery directly from the aircraft to the operations or command centre. While this would seem to be a simple process, there are several limitations to this operation. There is a balance between the amount of data transmitted, and the length of time for the transmission, and the bandwidth needed for transmission. All broad-bandwidth data transmission systems operate at frequencies which have a line-of-sight propagation. Since many remote sensing missions are flown at altitudes of less than 1000 m, the range of transmission is about 100 km. If the response headquarters is located in a mountainous area, this range may be limited to 10 km or even less. Many remote sensing missions require flight lengths in excess of 100 kin, and thus a much narrower band in the H F region is used. Since it can take several minutes to transmit a single image, the processing and interpretation of the data must take place on board the aircraft, ifa narrow-band system is used. The full data set will only be available after the aircraft has returned to base. In addition to the technical issues of data transmission from the plane to the command centre, there are significant problems in obtaining a licence to operate this equipment. There is no international standard for such transmissions, and there is no set of frequencies assigned for this use. This limits the ability of a high technology remote sensing aircraft to operate on an international basis. There is an intrinsic assumption that the rapid transmission of some part or all of the remote sensing data would be immediately useful to the oil spill response staff. In order to be easily interpretable by the client, the data must be resolved, and computer trajectory models run, in order to predict the future motion of the oil. At the present time, the integration of remote sensing images, ground observations, and trajectory model outputs has many problems (Goodman, 1994b). While there is considerable research activity being undertaken to provide integration of remote sensing information, and other data in a form suitable for the oil spill response manager, there is still more work to be done.
Myths While surveillance and tracking are an integral component of most oil spill response plans, remote Spill Science & Technology Bulletin 1(1)
sensing has not yet achieved this status. With the exception of infrared/ultraviolet systems and imaging radars (Side Looking Airborne Radar), there has been little use of complex remote sensing systems during major spills. The main reason for this is the limited availability of remote sensing systems at a suitable timescale, and a lack of understanding by response managers of the capabilities of remote sensing technologies to assist in the spill response. This lack of experience of the remote sensing community in responding to spills has led to several myths associated with the use of remote sensing in oil spill response.
Myth 1. Remote sensing is essential to a spill and will significantly improve the spill response Remote sensing, like any other technology associated with oil spill response, is only useful if it gives added value and information to the managers of the spill. In many cases, a number of trained observers can collect all the data needed for both tactical and strategic response functions. Spill response managers need three critical parameters: 1. the location and volume of the oil in order to plan the level of response effort and to evaluate the effectiveness of various tactics such as skimmers, chemicals or in situ burning; 2. the viscosity of the oil, so that suitable recovery equipment can be selected; and 3. the location and volume of oil on shorelines. It is difficult to give accurate estimates of these parameters using visual methods. Most remote sensing systems can only provide little improvement to the quality of the measurement of these three parameters.
Myth 2. Complex high-resolution spectrometers, operating in the visible range (350-750 nm), are useful for detecting oil on water There is little difference between the reflected spectra of various types of oil, and there are no strong features in the oil reflectance spectrum because oil is a complex physical mixture of hydrocarbons. The reflected spectrum is much more a function of solar radiation (cloud cover and sun angle) than it is ofoil properties. There are better regions of the electromagnetic spectrum where the contrast between oil and water is greater than in the visual region.
Myth 3. High-quality output and data processing are essential The most important criterion for obtaining remote sensing data is time. An oil spill is a dynamic situation and thus data are needed quickly after the flight. For 19
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R. GOODMAN
tactical decision-making, delays of an hour or so are acceptable, but any information that is only available after 2 or 3 h is of little use for response purposes. For strategic planning purposes, a longer delay may be acceptable if better quality data are presented, or if the available data are better integrated.
Myth 4. Dedicated aircraft are essential for oil spill remote sensin9 There are a number of concerns that must be addressed when choosing between a dedicated aircraft, and an aircraft of opportunity. A dedicated aircraft is required for many of the more advanced remote sensing techniques, since permanent mounting of parts of the remote sensing system is required. The main problem with a dedicated remote sensing aircraft is cost, and hence availability. The most appropriate aircraft for remote sensing should fly low and slow and be able to operate from a small airport. These requirements are the antithesis of the requirements for the aircraft to arrive quickly from a distant airport. In a large spill situation, close tactical support for the guidance of skimming or chemical application systems is required. Since there may be a number of such operations taking place simultaneously, a number of remote sensing systems are needed. Another major advantage of using aircraft of opportunity is that the local pilot will be familiar with the area and the peculiarities of flying in the region.
Myth 5. Satallite imagery is the solution to oil spill remote sensin9 One of the problems with most remote sensing systems is the lack of a synoptic overview of the spill, especially when the area of the spill is large. It would seem obvious that the use of satellite imagery would be
the solution to this problem. The difficulty with satellite imagery is that it has too low a resolution, and is generally not optimized for oil spill detection. Even if a suitable degree of definition could be achieved, there are many problems of data transmission and data analysis that cause significant time delays in the production of the imagery. As stated earlier, images more than 2-3 h old have only limited value for tactical purposes owing to the dynamic nature of an oil slick. These time delays, combined with the infrequent passes of many satellites, mean that this technology is unlikely to be useful for the remote sensing of oil on water, however, satellite imagery could be used for assisting in determining ocean and wind fields that are useful for trajectory models.
Conclusions Remote sensing has a significant role to perform during the response to an oil spill. The current technologies used are visual observation, a combination of IR/UV sensors, and SLAR radar. New developments such as microwave radiometers, laser fluorosensors, and laser-acoustic systems show promise for improving the availability of oil slick characteristics to oil spill response staff. The ability to measure oil on shorelines and to obtain a good estimate of oil volumes from the air is likely to be available in the next few years. These two additional pieces of information will greatly assist in decision-making during the response to an oil-spill incident. A summary of capabilities of all sensors discussed in this paper is presented in Table 2. There is still much research and development effort required for oil spill remote sensing. There are a number of new sensing systems that must be tested and evaluated before they can become operational for oil spill response. Experiments at sea must be conducted with oil to prove these systems and evaluate their utility and performance.
Table 2 Summary of sensor technology. Sensor
Wavelength (2)
Night operation
Thickness
Radar
1 30 cm
Yes
No
Passive microwave Thermal infrared (TIR) Mid-band infrared (MIR) Near infrared (NIR) Visual Ultraviolet Laser fluorosensor Laser-acoustic
2 8 mm
Yes
Relative
8-14/~m
Yes
Relative
3-5/~m
No
No
1-3/zm
No
No
350-750 nm 250-350 nm 0.308/~m 0.4-0.6 #m 1.06 #m
No No Yes
No No Yes < 20 ~m Absolute value
20
Yes
Weather limitations
False targets
Image quality
Dedicated aircraft
Cost
Heavy fog and rain Heavy fog and rain Light fog
High
High
Yes
High
Low
Yes
High
Medium
Low resolution High
No
Medium
Very light fog Clear
High
High
No
Low
High
High
No
Very low
Clear Clear Light fog
High Low Very low
No No Yes
Very low Very low High
Very light fog
Low
High High Line profile Line profile
Yes
High
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FUTURE TRENDS IN REMOTE SENSING
Potential clients and users must be educated as to the capabilities and limitations of these systems. These groups must become familiar with the output of remote sensing systems so that they can transform the graphical data into information useful for decision-making during an incident. For remote sensing to be used at the tactical level in direct support of containment and recovery operations, dispersant application or in situ burning, the cost of simple remote sensing systems must be reduced considerably so that each working task force can have its own remote sensing system. The European oil spill response community and the national governments of the European community have made much greater use of remote sensing for spill response than the corresponding groups in North America. There are many groups actively developing new sensors, new methods of using existing sensors, and new methods of integrating remote sensing into the oil spill response effort. In North America, the main groups associated with this development are MSRC, Environment Canada, and Imperial Oil Ltd. In Europe, there are active groups in Denmark, Germany, Great Britain, Italy, and Sweden who undertake remote sensing research and development.
Acknowledgements--The author thanks Mr Merv Fingas of Environment Canada, Dr Jerry Gait of the National Oceanographic and Atmospheric Administration (NOAA), and Dr Jay Pearlman of TRW for many discussions on the issues of remote sensing for oil spills. The author also thanks the members of the Imperial Oil Resources Environment Team (Hugh Brown, Peter Nicholson and Stefan Reinecke) for their assistance in collecting much of the data used in this paper. Thanks are due to Gary Hover of the U.S. Coast Guard, Dr Carl Brown of Environment Canada, and Dr Michael Mussetto of TRW, who have contributed freely of their knowledge of remote sensing and some of the diagrams in this paper. The many fruitful discussions with Charles Giammona of MSRC have contributed to the author's understanding of remote-sensing needs and objectives. Technical discussions with Stu Penny ofAR 3 have helped clarify many aspects of some of the sensor technology discussed. The continuing support for remote sensing research by Imperial Oil Resources Ltd is gratefully acknowledged.
Spill Science & Technology Bulletin 1(1)
References Brown, C. E., Fruhwirth, M., Fingas, M. F., Goodman, R. H., Choquet, M., Heon, R., Vaudreuil, G., Monchalin, J.-P. & Padioleau, C. (1994a). Laser ultrasonic remote sensing of oil thickness: absolute measurement of oil slick thickness. In Proc. First Int. Airborne, Remote Sensin 9 Conf. Exhibition, Paper C3, 11 15 September 1994 (in press), Strasbourg, France. Brown, C. E., Wang, Z., Fruhwirth, M. & Fingas, M. F. (1994b). May 1993 oil spill sensor test program: correlation of laser fluorosensor data with chemical analysis. In Proc. Seventeenth Arctic Mar. Oil Spill Program ( A M O P ) Technical Seminar 8-10 June 1994, pp. 1239 1261. Vancouver, BC. Costanzo, D. (1994). Trimble/Orion GPS oil spill tracking buoy initial field trials. In Proc. Seventeenth Arctic Marine Oil Spill Program ( A M O P ) Technical Seminar, 8-10 June 1994, pp. 1219 1225. Vancouver, BC. Goodman, R. H. (1992). Overview and future trends in oil spill remote sensing. In Conf. Proc. MTS'92, 19-21 October 1992, pp. 98 108. Washington, DC. Goodman, R. H. (1994a). Remote sensing resolution and oil slick inhomogeneities. In Proc. Second Thematic Conf. on Remote Sensin 9 for Marine and Coastal Environ, 31 January 2 February 1994, Vol. 1, pp. 1 6. New Orleans, LA. Goodman, R. H. (1994b). Remote sensing, models and oil-spill response. In Proc. First Int. Airborne Remote Sensing Conf. Exhibition, Paper C10, 11 15 September 1994 (In press), Strasbourg, France. H ollinger, J. P. (1974). The determination of oil thickness by means of multifrequency passive microwave techniques. Naval Res. Lab., Washington, DC, NRL Memorandum Report 2953. Hurford, N. (1985). Use of airborne microwave radiometry for the detection and investigation of oil slicks at sea. Warren Springs Laboratory, Stevenage, England LR-505(OP) Report PB85-237246 1985. Nithack, J. & Witte, F. (1984). Oilspill detection with DFVLR X-band SLAR. In Proc. IGARSS '84 27 30 August 1984, pp. 863 870. Strasbourg, France. O'Neil, R., Neville, R. A. & Thompson, V. (1983). The Arctic Marine Oilspill Program (AMOP) Remote Sensing Study. Environment Canada Report EPS 4-EC-83-3 Ottawa, Canada 257 pp. Preissner, J. (1979). The influence of the atmosphere on passive radiometric measurements. In AGARD Conf. Proc. No. 245 entitled Millimeter and Submillimeter Wave Propagation and Circuits tSpitz, E., ed.) Section 48, pp. 1 14. 1979 AGARD Neuilly sur Seine, France. Roddis, H. A. T. (1982). Development and testing of ice-tracking buoys automatically. In Proc. Fifth Arctic Marine Oilspill Program ( A M O P ) Technical Seminar, June 1982, pp. 913-923. Edmonton, Alberta. Wright, D. E. & Wright, J. A. (1973). Evaluation of an infrared oil film monitor. US Coast Guard Report CG-D-51-74, Department of Transportation, 1973. Washington, DC.
21
Pergamon
Elsevier Science Ltd
1353-2561(94)00003-4
Printed in Great Britain 1353-2561/94 $7.00+0.00
Overview and Future Trends in Oil Spill Remote Sensing RON GOODMAN
Research and Technology, Imperial Oil Resources Limited, Calgary, Alberta T2L 2K8, Canada (Tel: 403 932 4331; Fax: 403 932 4263)
Remote sensing has great potential to provide data to improve oil spill response efforts. There are a number of sensors available that have been proven capable of detecting oil on water and measuring some of its properties. There is no single sensor that provides all the data needed, and hence a combination of sensors must be used. Even if finances and aircraft load capacity were unlimited, there are still many parameters of an oil slick that cannot be measured by remote sensing. This paper describes the currently available sensors and their method of operation and outlines some new developments that have the potential to increase the amount of data available from an airborne remote sensing operation.
Surveillance and tracking of oil spills has been a feature of most spill response situations for many years. The simplest and most direct method uses visual observations from an aircraft and hand plotting of the data on a map. This technique has proven adequate for most small spills. The results of the observations are typically presented orally using maps produced during the flight. In recent years, a variety of remote sensors have been developed for the detection of oil on water and on shorelines (Goodman, 1992). All of the remote sensing systems use some form of electromagnetic radiation to detect the oil. The atmosphere is a good absorber for much of the electromagnetic spectrum, and remote sensing systems must operate using the few transparent windows as shown in Table 1 and Fig. 1. These bands represent regions of the electromagnetic spectrum where the atmosphere has an attenuation of
less than 1 d b m - 1 and hence are suitable for remote sensing (Preissner, 1979). The effects of weather for wavelengths greater than 1 mm should be noted: infrared, visible, and ultraviolet sensors will not detect oil through thick fog or heavy rain.
Present State-of-the-Art The present state-of-the-art in the detection of oil on water relies to a large extent on visual observations, supplemented by sensors that extend the spectrum of visual observation. These involve image-producing systems that operate in the thermal infrared (TIR), midIR (MIR), near IR (NIR), and ultraviolet (UV) bands.
Visual observations The most commonly used visual detector is the
Table 1 Remote sensing bands.
Band
Wavelength
Types of instruments
Radar Passive microwave Thermal infrared (TIR) Mid-band infrared (MIR) Near infrared (NIR) Visual Ultraviolet
1-30 cm 2-8 mm 8-14 #m 3 5/~m 1 3/~m 350-750 nm 250-350 nm
SLAR/SAR Radiometers Video cameras and line scanners Video cameras and line scanners Film and video cameras Film, video cameras and spectrometers Film, video cameras and line scanners 11
R. GOODMAN 1000 Fog (0.1 g/m
3)
Visibility 50 m 100
~
10
Heavy rain (25 mmJh)
Drizzle (0.25 mm/h)
o.1 I I
d IR
*%%O,,o*,,°,oO.OoO \
Submillimeter 0.01 10GHz 3 cm
Mid IR
t
\ \
100 3 mm
1 THz 0.3 rnm
10 30 p
100 3.0 p
1000 0.3 p
Near IR
Microwave q
Frequency Wavelength
Visible
"In many cases, region below band ~ = ~ e n t s almosphedc windows for aJrbsee sensing
Fig. 1 Atmospheric windows.
human eye. With the exception of a very narrow range of oil thicknesses where interference patterns can occur, the appearance of oil on water varies from a silver-grey to brown and changes in apparent colour occur over a range of several orders of magnitude in the oil thickness. The lack of strong spectral features means that most passive visual detectors are not well adapted to the detection of oil on water. The skilled visual observer uses changes in the texture of the surface and pattern recognition, and not colour to identify oil slicks. A problem with most visual observations is the interference caused by sun glitter. At low sun angles, the rough ocean surface reflects the solar radiation and hence obscures the presence of the oil.
Infrared imaging systems There are three somewhat distinct bands in the infrared in which the atmospheric transmission is sufficiently low to allow detection from an airborne platform. Tests of all three of these regions were conducted a number of years ago to determine which of the regions is the most suitable for remote sensing (O'Neil et al., 1983). The cost of systems operating in the infrared is lowest for the near IR, with an increase by a factor of five for mid-IR cameras, and a further increase by a factor of three for cameras operating in the thermal IR. There are two factors that allow oil to be detected on water using an infrared sensor: the oil and water are 12
actually at a different temperature, or there is an emissivity difference between oil and water that produces an apparent temperature difference even though the oil and water are actually at the same temperature. It is only in the thermal IR that the emissivity of oil (0.93) and water (0.98) is sufficiently different that an image can be produced. In the other two bands, the oil and water must be at a different temperature in order to be detected. This implies that there must be some source of external radiation, either naturally from the sun or supplied by the instrument.
Near 117 (NIR) (1-3 lun). There are two types of equipment that have been developed for operation in this band. The one system uses a simple detector and illumination system (Wright & Wright, 1973). It has a response time of several seconds and a range of a few tens of meters and thus is not suitable for remote sensing. The other system is a video imaging detector that operates like a video camera and depends on an external excitation source. The contrast between oil and water in this band is low, and there are a number of interferences due to chlorophyll and water vapour bands in this part of the spectrum. The camera version of these systems has a slow response time and requires high ( > 1°C) temperature differences to produce any contrast. The advantages of near infrared systems are: I. they are uncomplicated to operate and the interpretation of the output is relatively simple; Spill Science & Technology Bulletin 1(1)
FUTURE TRENDS IN REMOTE SENSING 2. they are light and consume little power and are suitable for mounting in aircraft of opportunity; and 3. they are the least expensive of the infrared systems. The disadvantages of near infrared systems are: 1. they cannot penetrate cloud; 2. they cannot operate at night; 3. they produce many false targets from plant material; and 4. they lack contrast, which makes the image difficult to interpret.
Mid-band infrared systems ( M I R ) (3-5 Itm). As with the near IR systems, the mid-band IR systems depend on actual temperature differences to detect the presence of oil on the water. In this band, there are very few interferences, and cameras are available that can detect temperature differences as small as 0.02°C. This high sensitivity allows the detection of small amounts of oil on water, under daylight conditions. The main interference with these systems is the small-scale temperature changes that occur owing to the complex circulation patterns in the ocean. These are poorly understood and
can produce patterns that might be confused with oil. A typical output from a mid-band IR detector is shown in Fig. 2. The advantages of mid-band infrared systems are: 1. they are uncomplicated to operate and the interpretation of the output is relatively simple; 2. they are light and consume little power and are suitable for mounting in aircraft of opportunity; 3. a wide variety of lenses are available for these systems; and 4. they are a moderately expensive infrared system. The disadvantage of mid-band infrared systems are: 1. they cannot penetrate cloud but can penetrate light fog; 2. they cannot operate at night; 3. they produce some false targets caused by ocean circulation patterns; and 4. they cannot be used through a window of an aircraft. Thermal infrared systems ( TIR) (8-14 l~m). Thermal infrared detectors provide a two-dimensional image,
Fig. 2 Mid-band infrared output.
Spill Science & TechnologyBulletin 1(1)
13
R. GOODMAN whose density is a function of the surface temperature of the scene, using two-dimensional solid-state arrays and a real-time processor. All thermal infrared systems require cooling the detector to liquid air (nitrogen) temperatures using either a Joule Thompson or a Stirling cycle engine. For slicks of thicknesses between 50 and 500 ~tm, the oil appears to be at a lower temperature than the surrounding water. While slicks of these thicknesses are at the same actual temperature as the water, the oil is a less effective emitter than the water and hence appears cooler. It is possible to maintain a significant real temperature difference between oil and water if there is sufficient oil thickness ( > 500 #m) to insulate the upper layers of the oil from the water. The thermal infrared system will not detect thin sheens but can differentiate between two levels of oil thickness with the transition between 'hot' oil and 'cold' oil at about 500 ktm. The detection of the oil does not depend on solar radiation, so a thermal infrared detector can operate both day and night. Since water vapour is a good absorber of the signal, an infrared system cannot be used through cloud. There is little difference in the infrared emission characteristics of various types of crude oil, but there are large differences between oil and other naturally occurring objects in the ocean. The infrared detector provides discrimination between oil and other materials. There is a wide variety of thermal infrared systems. Detectors such as pyroelectric vidicon and thermocouple detectors have been developed for other purposes. While such systems have an attractive price, they do not have suitable sensitivity to detect oil on water. Acceptable systems for detecting oil on water must detect temperature differences of less than 0.2°C. Most systems produce a standard television output, which can be displayed on a TV monitor and recorded, using a video tape-recorder. Using this method of output, it is easy to obtain and record an image in a compact format. If further analysis of the image is required, the TV format must be converted into a computer-readable format. This requires the use of a frame grabber. A thermal infrared system output is shown in Fig. 3. The advantages of thermal infrared systems are: 1. they are uncomplicated to operate and the interpretation of the output is relatively simple; 2. they are light and consume little power and are suitable for mounting in aircraft of opportunity; 3. they can operate both day and night; 4. they can easily differentiate between oil and other natural objects; 5. they can distinguish between sheen and thick oil and detect thickness gradients; and 6. they are relatively inexpensive, but are the most costly of the infrared systems. The disadvantages of thermal infrared systems are: 14
Fig. 3 Thermal infrared output. I. they cannot penetrate cloud, but can penetrate light fog; 2. they cannot measure absolute oil thickness; 3. the application of dispersant causes significant changes in the emissive properties of the oil and can confuse the interpretation of the images; and 4. there are few materials that are transparent to infrared and hence the detector must be either mounted without a window or by using a germanium window, which is very expensive and not readily available. Ultraviolet
It is difficult to differentiate oil visually from other naturally occurring materials. In the ultraviolet, the reflectivity of oil and water are different, and this forms the basis for the detection of oil in the ultraviolet. The reflectivity ofoil in the ultraviolet is 1.02, whereas that of water is 0.722. Since reflectivity is a surface phenomenon, any hydrocarbon on the surface, independent of thickness, will be detected. It is the sheen that is detected by ultraviolet sensors. Most UV systems use a standard television camera with a suitable filter package. The filters have a passband of 0.25q).35 #m and are used in combination with a polarizer to eliminate glare. A typical ultraviolet image is shown in Fig. 4. The advantages of ultraviolet systems are: 1. they are simple, lightweight, and require little power; 2. they are suitable for mounting in aircraft of opportunity; 3. they produce a video output that is simple to display and record; and 4. they are relatively inexpensive. The disadvantages of ultraviolet systems are: I. they detect the presence of any hydrocarbon on the water surface and cannot differentiate between sheen and thicker oil slicks; and 2. they can only operate under daylight conditions with clear visibility. Spill Science & Technology Bulletin 1(1)
FUTURE TRENDS IN REMOTE SENSING
Fig. 4
Ultraviolet output.
Radar SLAR (Side Looking Airborne Radar) has been used to observe the distribution of floating oil. This is a special type of imaging radar and is quite different from standard marine and airborne radar systems. A SLAR image is formed by the reflection of radar signals from small gravity and capillary waves. These waves are the little ripples or 'cats paws' that can be seen over any water surface when the wind blows. The oil spill is visible to the radar because a very thin film of oil suppresses these small waves and the sea surface appears smooth, both visually, and to the radar. Thus, there is less radar signal return from these regions, and the oil slick shows as a dark region on the image. A film as thin as a few microns can suppress capillary waves (Nithack & Witte, 1984). There is both an upper and a lower limit of wind speeds needed to produce a significant radar return. Under low wind-speed conditions, there is very little wind-stress and any area will be fiat and have a low reflectivity to radar. The radar image would indicate that there is oil everywhere. The low wind cut-off appears to be between 2.5 and 5 m s-1. This limit is dependent on the presence of organic materials on the sea surface. Above this lower limit cut-off, the windstress is sufficient to rupture the naturally occurring organic slicks and hence provide a method of discrimination between oil and water. At wind speeds greater than 10 m s- 1, the wind-stress is sufficient to tear up the oil slick into small patches of a size less than the radar resolution. In terms of oil spill response, skimmers and in situ burning are most effective at sea-states lower than the lower limit of radar detection. A typical SLAR image is shown in Fig. 5. The advantages of SLAR systems are: 1. they can operate under all weather conditions and readily penetrate cloud; and Spill Science & Technology Bulletin l(1)
Fig. 5
SLAR image.
2. aircraft with SLAR can fly at high altitudes and can cover large areas quickly. The disadvantages of SLAR systems are: I. the systems are heavy and require a large externally mounted antenna; 2. they are quite expensive; 3. one of the major problems with using SLAR imagery to track oil spills is that there are a number of targets that can lead to false returns. At wind conditions near the lower limit, such ocean features as wind shadows, freshwater fronts, plankton blooms, and kelp beds can produce images that are difficult to distinguish from that of oil on water. Wind shadows from shore features are hard to differentiate from the presence of oil; and 4. the ability to generate an image of an oil slick is strongly dependent on surface wind conditions. Drifter buoys Although not a remote sensing technique, a common method of following an oil spill is to deploy specially designed buoys into the spill, near the source. The design of the buoy hull is very critical to its ability to follow the oil (Roddis, 1982). An oil slick on the open ocean has a thickness of a few millimeters and moves with the ocean surface. All buoys protrude above the water surface and are thus subject to different wind regimes. Similarly, the effects of near-surface ocean currents cause the buoys to 15
REVIEW
R. GOODMAN
follow the slick to a day or less (Costanzo, 1994). A typical modern tracker buoy is shown in Fig. 6.
Future trends
gies have been developed to measure oil thickness; one using microwave radiometers, and the other, using a laser-acoustic measurement system. Microwave radiometer
Existing remote sensing technology can detect the presence of oil, and give some indication of its relative thickness. Two parameters are needed to provide additional information to the response effort: the thickness of the slick, and the nature and identity of the oil. The volume of oil can be determined from the thickness and the area of the slick. It is important to characterize the oil in order to optimize the response tactics and to identify the source of the spill. With curent systems, it is possible to measure the area of the spill. This information has limited value, since it is the volume of the oil on the water that is useful to the managers of the spill response. Two separate technolo-
Microwave radiometers are passive sensors that measure the naturally emitted and reflected radiation from the ocean surface. There are significant differences between the emissivity and reflectivity ofoil and water. If the wavelength is chosen to be longer than the oil thickness, then it is possible to measure the relative thickness of the oil film. Typical microwave radiometers operate in the 5-94 G H z region of the spectrum (Hollinger, 1974). A typical image is shown in Fig. 7. The advantages of microwave radiometers are: 1. they have all-weather operational capability, except when heavy rain is present; and
Fig. 6 Moderntracker buoy.
Q.
E
#
¢1 rE O) L.. m
245 E
g
139
¢~
12
11 10 7 Tank #
4
1.0 0.0
Fig. 7 Microwave radiometerimage. 16
Spill Science & Technology Bulletin 1(1)
F U T U R E T R E N D S IN R E M O T E S E N S I N G
2. they are an imaging system with the potential to measure relative thickness.
of laser and acoustic technologies. The main properties of oil that are used in this measurement are its acoustic or mechanical properties, which are very different from the electromagnetic and optical properties that are normally associated with remote sensing. A pulse of energy supplied by the laser impacts on the oil film causing local heating. This local heating causes the oil to expand, and a dome-shaped protrusion forms at the surface. The vertical component of the deformation is proportional to the thickness of the oil. This change in height or the rate of change of the height can be detected by using another laser and a Fabry-Perot interferometer (Brown et al., 1994a). A typical output is shown in Fig. 8. The advantages of a laser-acoustic system are:
The disadvantages of microwave radiometers are: 1. they require a special antenna and hence a dedicated aircraft; 2. they are expensive and complex to operate and maintain; 3. there is limited experience with microwave radiometers in field situations; and 4. limited spatial resolution causes averaging over a large area of the slick. Oil slick inhomogeneities are smaller than the sensor footprint (Hurford, 1985; Goodman, 1994a), which results in the determination of the average value of the oil thickness integrated over a large area.
1. it can measure the absolute thickness of the oil without ambiguity, and requires only a knowledge of the thermal properties of the oil. These properties are similar for a wide variety of oil types; and 2. it is an active system and can operate both day and night.
Laser-acoustic oil thickness sensor A laser-acoustic oil thickness sensor is an absolute thickness measurement system that uses a combination surface signal
2.5--
first echo
2.0-
second echo
=. 1.5
m E i1)
Laser-ultrasonic signal
/
E
Surface displacement
~ 1.oQ.
f
~5
0.5--
0.0
I
2
: l l l r r l l l l r l
J[I
3
4
5
6
I~lF 7
I 8
• m e (psec) Fig. 8
Laser acoustic output.
Spill Science & Technology Bulletin 1(1)
17
R. G O O D M A N
The disadvantages of the laser-acoustic system are 1. it is large and needs a significant amount of power; 2. it cannot penetrate cloud or fog; and 3. it has not been field prove.
Laser fluorosensor If the oil can be excited, using intense ultraviolet radiation from a laser, a fluorescence return, which is unique to the presence of oil on the water surface, can be detected in the visible. The laser fluorosensor is a complex instrument that can identify and classify the presence of oil on water and shorelines. The main background radiation that interferes with the detection of oil is the contribution of suspended phytoplankton or dissolved organic matter (Gelbstoff). This generates a broad spectrum return in addition to a specific return from chlorophyll at 685 nm. Laser fluorosensors are nadir systems, which produce a line scan as a result of the forward motion of the aircraft. A laser is used to excite the oil. There are two characteristics of the visible return spectrum that can be used to detect the presence of oil: spectral analysis and decay time (Brown et al., 1994b). A multi-channel spectrometer is used to analyse the spectral characteristics of the return signal. From this spectral information, the presence of oil can be determined for both water and shoreline situations.
An alternative method of identifying the oil is the use of the decay characteristics of the fluorescence. Since typical decay times are 1-20 ns, the exciting pulse should be less than 1 ns and the return system needs to have a bandwidth in excess of 1 GHz. In most systems, these bandwidths are achieved, using time domain optical systems, rather than coventional electronic methods. An analysed output is shown in Fig. 9. The advantages of laser fluoresensors are: 1. they are active systems and hence can operate both day and night; 2. they can positively differentiate oil from other surface materials and can provide an indication of the type ofoil on the water; and 3. they can detect oil on shorelines. The disadvantages of laser fluorosensors are: 1. they are generally bulky and require a significant amount of power; 2. they are presently point detectors; and 3. they operate in the UV and visible bands and hence cannot operate under conditions of fog or cloud. Data communication
Once the data have been collected by a remote sensing system, they must be communicated to those who can use it. Current technology involves the presentation of
LEAF 3-D F l u o r e s c e n c e Spectra CFB P e t a w a w a May 7, 1993 Flight 6, Pass 2
~Path °r..¢
)===4
Fig. 9 18
Laser fluorosensor.
Spill Science & Technology Bulletin 1(l)
FUTURE TRENDS IN REMOTE SENSING
these data on a map, which is used for briefing the spill response organization. The preparation of the map is a time-consuming process and reduces the immediacy of the data. Since remote sensing operations are clientdriven, care must be taken to ensure that the data are available to those who need them in a timely manner and in a suitable format. One of the methods of reducing time delays for the users is the transmission of the imagery directly from the aircraft to the operations or command centre. While this would seem to be a simple process, there are several limitations to this operation. There is a balance between the amount of data transmitted, and the length of time for the transmission, and the bandwidth needed for transmission. All broad-bandwidth data transmission systems operate at frequencies which have a line-of-sight propagation. Since many remote sensing missions are flown at altitudes of less than 1000 m, the range of transmission is about 100 km. If the response headquarters is located in a mountainous area, this range may be limited to 10 km or even less. Many remote sensing missions require flight lengths in excess of 100 kin, and thus a much narrower band in the H F region is used. Since it can take several minutes to transmit a single image, the processing and interpretation of the data must take place on board the aircraft, ifa narrow-band system is used. The full data set will only be available after the aircraft has returned to base. In addition to the technical issues of data transmission from the plane to the command centre, there are significant problems in obtaining a licence to operate this equipment. There is no international standard for such transmissions, and there is no set of frequencies assigned for this use. This limits the ability of a high technology remote sensing aircraft to operate on an international basis. There is an intrinsic assumption that the rapid transmission of some part or all of the remote sensing data would be immediately useful to the oil spill response staff. In order to be easily interpretable by the client, the data must be resolved, and computer trajectory models run, in order to predict the future motion of the oil. At the present time, the integration of remote sensing images, ground observations, and trajectory model outputs has many problems (Goodman, 1994b). While there is considerable research activity being undertaken to provide integration of remote sensing information, and other data in a form suitable for the oil spill response manager, there is still more work to be done.
Myths While surveillance and tracking are an integral component of most oil spill response plans, remote Spill Science & Technology Bulletin 1(1)
sensing has not yet achieved this status. With the exception of infrared/ultraviolet systems and imaging radars (Side Looking Airborne Radar), there has been little use of complex remote sensing systems during major spills. The main reason for this is the limited availability of remote sensing systems at a suitable timescale, and a lack of understanding by response managers of the capabilities of remote sensing technologies to assist in the spill response. This lack of experience of the remote sensing community in responding to spills has led to several myths associated with the use of remote sensing in oil spill response.
Myth 1. Remote sensing is essential to a spill and will significantly improve the spill response Remote sensing, like any other technology associated with oil spill response, is only useful if it gives added value and information to the managers of the spill. In many cases, a number of trained observers can collect all the data needed for both tactical and strategic response functions. Spill response managers need three critical parameters: 1. the location and volume of the oil in order to plan the level of response effort and to evaluate the effectiveness of various tactics such as skimmers, chemicals or in situ burning; 2. the viscosity of the oil, so that suitable recovery equipment can be selected; and 3. the location and volume of oil on shorelines. It is difficult to give accurate estimates of these parameters using visual methods. Most remote sensing systems can only provide little improvement to the quality of the measurement of these three parameters.
Myth 2. Complex high-resolution spectrometers, operating in the visible range (350-750 nm), are useful for detecting oil on water There is little difference between the reflected spectra of various types of oil, and there are no strong features in the oil reflectance spectrum because oil is a complex physical mixture of hydrocarbons. The reflected spectrum is much more a function of solar radiation (cloud cover and sun angle) than it is ofoil properties. There are better regions of the electromagnetic spectrum where the contrast between oil and water is greater than in the visual region.
Myth 3. High-quality output and data processing are essential The most important criterion for obtaining remote sensing data is time. An oil spill is a dynamic situation and thus data are needed quickly after the flight. For 19
REVIEW
R. GOODMAN
tactical decision-making, delays of an hour or so are acceptable, but any information that is only available after 2 or 3 h is of little use for response purposes. For strategic planning purposes, a longer delay may be acceptable if better quality data are presented, or if the available data are better integrated.
Myth 4. Dedicated aircraft are essential for oil spill remote sensin9 There are a number of concerns that must be addressed when choosing between a dedicated aircraft, and an aircraft of opportunity. A dedicated aircraft is required for many of the more advanced remote sensing techniques, since permanent mounting of parts of the remote sensing system is required. The main problem with a dedicated remote sensing aircraft is cost, and hence availability. The most appropriate aircraft for remote sensing should fly low and slow and be able to operate from a small airport. These requirements are the antithesis of the requirements for the aircraft to arrive quickly from a distant airport. In a large spill situation, close tactical support for the guidance of skimming or chemical application systems is required. Since there may be a number of such operations taking place simultaneously, a number of remote sensing systems are needed. Another major advantage of using aircraft of opportunity is that the local pilot will be familiar with the area and the peculiarities of flying in the region.
Myth 5. Satallite imagery is the solution to oil spill remote sensin9 One of the problems with most remote sensing systems is the lack of a synoptic overview of the spill, especially when the area of the spill is large. It would seem obvious that the use of satellite imagery would be
the solution to this problem. The difficulty with satellite imagery is that it has too low a resolution, and is generally not optimized for oil spill detection. Even if a suitable degree of definition could be achieved, there are many problems of data transmission and data analysis that cause significant time delays in the production of the imagery. As stated earlier, images more than 2-3 h old have only limited value for tactical purposes owing to the dynamic nature of an oil slick. These time delays, combined with the infrequent passes of many satellites, mean that this technology is unlikely to be useful for the remote sensing of oil on water, however, satellite imagery could be used for assisting in determining ocean and wind fields that are useful for trajectory models.
Conclusions Remote sensing has a significant role to perform during the response to an oil spill. The current technologies used are visual observation, a combination of IR/UV sensors, and SLAR radar. New developments such as microwave radiometers, laser fluorosensors, and laser-acoustic systems show promise for improving the availability of oil slick characteristics to oil spill response staff. The ability to measure oil on shorelines and to obtain a good estimate of oil volumes from the air is likely to be available in the next few years. These two additional pieces of information will greatly assist in decision-making during the response to an oil-spill incident. A summary of capabilities of all sensors discussed in this paper is presented in Table 2. There is still much research and development effort required for oil spill remote sensing. There are a number of new sensing systems that must be tested and evaluated before they can become operational for oil spill response. Experiments at sea must be conducted with oil to prove these systems and evaluate their utility and performance.
Table 2 Summary of sensor technology. Sensor
Wavelength (2)
Night operation
Thickness
Radar
1 30 cm
Yes
No
Passive microwave Thermal infrared (TIR) Mid-band infrared (MIR) Near infrared (NIR) Visual Ultraviolet Laser fluorosensor Laser-acoustic
2 8 mm
Yes
Relative
8-14/~m
Yes
Relative
3-5/~m
No
No
1-3/zm
No
No
350-750 nm 250-350 nm 0.308/~m 0.4-0.6 #m 1.06 #m
No No Yes
No No Yes < 20 ~m Absolute value
20
Yes
Weather limitations
False targets
Image quality
Dedicated aircraft
Cost
Heavy fog and rain Heavy fog and rain Light fog
High
High
Yes
High
Low
Yes
High
Medium
Low resolution High
No
Medium
Very light fog Clear
High
High
No
Low
High
High
No
Very low
Clear Clear Light fog
High Low Very low
No No Yes
Very low Very low High
Very light fog
Low
High High Line profile Line profile
Yes
High
Spill Science & Technology Bulletin 1(1)
FUTURE TRENDS IN REMOTE SENSING
Potential clients and users must be educated as to the capabilities and limitations of these systems. These groups must become familiar with the output of remote sensing systems so that they can transform the graphical data into information useful for decision-making during an incident. For remote sensing to be used at the tactical level in direct support of containment and recovery operations, dispersant application or in situ burning, the cost of simple remote sensing systems must be reduced considerably so that each working task force can have its own remote sensing system. The European oil spill response community and the national governments of the European community have made much greater use of remote sensing for spill response than the corresponding groups in North America. There are many groups actively developing new sensors, new methods of using existing sensors, and new methods of integrating remote sensing into the oil spill response effort. In North America, the main groups associated with this development are MSRC, Environment Canada, and Imperial Oil Ltd. In Europe, there are active groups in Denmark, Germany, Great Britain, Italy, and Sweden who undertake remote sensing research and development.
Acknowledgements--The author thanks Mr Merv Fingas of Environment Canada, Dr Jerry Gait of the National Oceanographic and Atmospheric Administration (NOAA), and Dr Jay Pearlman of TRW for many discussions on the issues of remote sensing for oil spills. The author also thanks the members of the Imperial Oil Resources Environment Team (Hugh Brown, Peter Nicholson and Stefan Reinecke) for their assistance in collecting much of the data used in this paper. Thanks are due to Gary Hover of the U.S. Coast Guard, Dr Carl Brown of Environment Canada, and Dr Michael Mussetto of TRW, who have contributed freely of their knowledge of remote sensing and some of the diagrams in this paper. The many fruitful discussions with Charles Giammona of MSRC have contributed to the author's understanding of remote-sensing needs and objectives. Technical discussions with Stu Penny ofAR 3 have helped clarify many aspects of some of the sensor technology discussed. The continuing support for remote sensing research by Imperial Oil Resources Ltd is gratefully acknowledged.
Spill Science & Technology Bulletin 1(1)
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