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3. surveillance

An Assessment of Surface Surveillance Capabilities
for Oil Spill Response using Airborne Remote Sensing
Provided for IPIECA and OGP
Abstract. This report provides an assessment of airborne surveillance for oil spill
response, carried out for IPIECA and OGP under contract OSR-JIP Polar 001.
11 May 2015
Kim Partington
Polar Imaging Limited
Reference PIL-4000-38-TR-1.1
An Assessment of Surface Surveillance Capabilities for Oil Spill Response using Airborne Remote Sensing
11th May 2015
PIL-4000-38-TR-1.1
Issuing Authority
Name
Kim Partington, Managing Director, Polar Imaging Limited
Address
“Farthings”, Stoke Road, Hurstbourne Tarrant,
Andover, Hampshire, United Kingdom SP11 0BA
Telephone
+44 7796 956594
Fax
+44 870 705 9990
Email
[email protected]
Company registration 5919275
Date of incorporation
VAT registration
30 August 2006
892821689
Delivery
Copy No.:
Delivered to:
1
Office copy
2
Richard Eyers, Shell
3
Rob Cox, IPIECA
Document Change Record
Issue
Revision
Date
Reason for revision
1
0
22nd May 2014
First deliverable version.
1
1
11th May 2015
Corrected date in caption to Figure 6.
Frontispiece. Clockwise from bottom left: SpecTIR hyperspectral data covering 360 spectral
channels from the Gulf of Mexico oil spill, 6 July 2010 (courtesy Justin Janaskie, Spectir); Islander
aircraft used in oil spill response (courtesy Richard Blain, Aerospace Resources); the Aeryon Labs
Scout UAV in an oil spill response demonstration in Prince William Sound, Alaska, in 2011,
University of Alaska Fairbanks photo courtesy of Greg Walker; Responder in aircraft overlooking oil
on water, courtesy NOAA.
An Assessment of Surface Surveillance Capabilities for Oil Spill Response using Airborne Remote Sensing
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PIL-4000-38-TR-1.1
Table of Contents
Acknowledgements ...................................................................................................................... 1
Acronyms ..................................................................................................................................... 2
Executive Summary ...................................................................................................................... 3
1.
Introduction ........................................................................................................................ 5
2.
Objectives ........................................................................................................................... 5
3.
Scope .................................................................................................................................. 6
4.
Airborne Remote Sensing .................................................................................................... 7
4.1. Overview ............................................................................................................................. 7
4.2. Passive Sensing .................................................................................................................... 9
4.3. Active Sensing ..................................................................................................................... 10
5.
Application of Airborne Remote Sensing to OSR ................................................................. 11
5.1. Offshore Sensing of Oil Spills ................................................................................................ 11
5.2. Onshore OSR ....................................................................................................................... 16
5.3. OSR in low visibility and ice .................................................................................................. 18
6.
Methodology ...................................................................................................................... 20
6.1. Overview ............................................................................................................................. 20
6.2. Airborne Surveillance Analysis ............................................................................................. 20
7.
Oil Spill Response Requirements for Airborne Remote Sensing .......................................... 21
8.
Airborne Platforms for OSR ................................................................................................. 23
8.1. Manned Aircraft .................................................................................................................. 24
8.2. Unmanned Aerial Systems ................................................................................................... 29
8.3. Aerostats ............................................................................................................................. 41
9.
Airborne Sensors for OSR .................................................................................................... 43
9.1. Visual Observation ............................................................................................................... 44
9.2. Aerial Photography and Video .............................................................................................. 45
9.3. Multispectral Optical and Thermal Sensors .......................................................................... 47
9.4. Microwave Radiometers ...................................................................................................... 51
9.5. Hyperspectral sensors .......................................................................................................... 53
9.6. Laser.................................................................................................................................... 57
9.7. Radar................................................................................................................................... 60
9.8. Integrated Airborne Sensing Systems ................................................................................... 62
10. Some General Challenges for Airborne Remote Sensing ..................................................... 64
10.1. Positioning of Remote Sensing Imagery ................................................................................ 64
10.2. Environmental Considerations ............................................................................................. 66
11. Findings ............................................................................................................................... 69
11.1. General ............................................................................................................................... 69
11.2. Platforms ............................................................................................................................. 70
11.3. Sensors ................................................................................................................................ 71
11.4. Processing and Delivery ....................................................................................................... 72
12. Conclusions ......................................................................................................................... 73
Appendix A. Airborne Remote Sensing Platforms and Sensors ....................................................... 74
A1. Sensor providers ..................................................................................................................... 74
A2. Platform Providers .................................................................................................................. 76
Appendix B. References and Sources ............................................................................................. 81
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Acknowledgements
The author acknowledges the important and appreciated support and input from
several individuals and organisations, as follows:
Leadership, management and funding from Oil and Gas Producers Association
(OGP) - International Petroleum Industry Environmental Conservation
Association (IPIECA) Joint Industry Project, under contract OSR-JIP Polar 001,
managed by Rob Cox.
Technical direction from Richard Eyers (Shell Petroleum Development Company
of Nigeria) and members of the work package 2 steering committee, including
Roger Abel (Shell Exploration & Production), Louis Demargne (Fugro), Peter
Hausknecht (Woodside), Rob O’Brien (BP), Emma Hughes (Oil Spill Response
Ltd), Richard Hall (Statoil), Veronique Miegebielle and Dominique Dubucq
(Total) and Ola Grabak (European Space Agency).
Input from many satellite data vendors, remote sensing value-added
organisations, oil spill responders and researchers, many of whom invested
significant time in contributing to the workshop and responding to the
questionnaire and interviews.
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2
Acronyms
This table does not include the names of airborne platforms or sensors that are made up
of acronyms. Directions are indicated as follows: east (E), west (W), north (N) and south
(S) and combinations thereof (e.g. south-west, SW).
Table 1. List and explanation of acronyms
Acronym
AIS
AoI
API
ATC
CoP
Description
Automatic Identification System
Area of Interest
American Petroleum Institute
Air Traffic Control
Common Operating Picture
Acronym
MS
μm
m/s
MWIR
n/a
DEM
Digital elevation model
NASA
DIAL
Differential absorption lidar
NDVI
EM
Electromagnetic
NIR
ESA
European Space Agency
NOFO
ESI
environmental sensitivity index
O&G
FAA
Federal Aviation Administration
OGP
FLIR
FPSO
GHz
GIS
OPT
OSR
PAN
PMR
R&D
Research and development
RFI
RGB
SAR
SLAR
STC
SWIR
Request for information
Red green blue
Synthetic Aperture Radar
Side looking airborne radar
Supplemental type certificate
Shortwave Infrared
TIR
Thermal infrared
TUAV
Tactical UAV
UAS
Unmanned aerial system
UAV
Unmanned aerial vehicle
ITU
JIP
JPL
LFS
LWIR
m
Forward looking infrared
Floating production storage and offloading
Gigahertz
Geographic Information System
Global (Geographic) Navigation Satellite
System
Ground penetrating radar
Global Positioning System
High altitude long endurance (UAV)
Hour
Health, safety and environment
Hertz
The global oil and gas industry association
for environmental and social issues
Infrared
Inertial monitoring unit / Inertial navigation
system
International Organisation for
Standardisation
International Telecommunication Union
Joint Industry Project
Jet Propulsion Laboratory
Laser fluoro-sensor
Long-wave Infrared
Metre
Description
Multispectral
Micrometer
Metre per second
Mid-wave Infrared
Not Applicable
National Aeronautics and
Space Administration
normalised difference
vegetation index
Near infrared
Norwegian Clean Seas
Association for Operating
Companies
Oil and Gas
International Association for Oil
and Gas Producers
Optical
Oil spill response
Panchromatic
Passive microwave radiometry
UHF
USA
UV
VHF
VIS
VNIR
MALE
Medium altitude long endurance (UAV)
VTOL
mb/s
Megabit per second
WP
Ultra high frequency
United States of America
Ultraviolet
Very high frequency
Visible
Very near infrared
Vertical takeoff and landing
(UAV)
Work-package
GNSS
GPR
GPS
HALE
Hr
HSE
Hz
IPIECA
IR
IMU/INS
ISO
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Executive Summary
Oil spills have the potential to threaten human health and safety, the integrity of the
environment and the viability of local economies, and the oil and gas industry has a
responsibility to seek out and deploy all available technologies to both minimise the risk
of spills, and to deal effectively with them if and when they occur. In response to this,
OGP-IPIECA has funded an Oil Spill Response (OSR) Joint Industry Project (JIP) to
optimise the industry’s capabilities for oil spill response. This report forms part of work
package 2 within this JIP, and focuses on identifying capabilities and gaps associated
with surveillance monitoring from aircraft. It is complementary to a similar report
assessing surveillance capabilities of satellite sensors and platforms for oil spill
response [1]. Together, these reports cover remote sensing technologies and platforms
for oil spill response, and these are linked to recommendations from the American
Petroleum Institute (API) in their assessment of remote sensing for oil spill response [2].
Key findings are as follows:
The number of platform and sensor providers is very large, and the number
identified through this report, particularly platform providers, is limited. A
directory of this information would be very useful to the industry.
Exercises would help considerably in supporting the development of effective
airborne surveillance capabilities for oil spill response, for technology testing,
migration to operational capabilities, training, integration with the CoP, etc.
Effective oil spill response based on opportunistic availability of platforms (with
sensors) is not viable.
Given that oil spill surveillance using opportunistically available platforms and
sensors is not viable, there is a need to build surveillance capabilities around
local jurisdictions and physical environments for OSR.
UAS are clearly going to be important platforms for OSR in the future, with the
market likely to expand rapidly in the next 5 years. The industry should ensure
that it is ready to exploit this technology effectively, which requires keeping a
close eye on developments over the next few years, both technical and
regulatory.
Standard sensor packages on standby for deployment are potentially very useful,
but only if their deployment can be provided with necessary approvals in
advance (for example, export and import-compliant, and approvals for sensor
mounts).
A technology road map would be useful to identify critical technologies that the
industry needs for effective oil spill response. Important research topics include:
spectroscopy; full polarisation imaging radar; effective and practical deployment
of, and fusion of information from, multiple sensors and real time, or near real
time, data transmission.
Training is a critical part of effective airborne surveillance for OSR, particularly
as the complexity of sensors, and their greater use in combination (perhaps also
with multiple platforms), becomes more frequent.
Experience from Deepwater Horizon and elsewhere has demonstrated that
processing of data can delay ingestion of the information into the CoP. The drive
to develop new sensors and data analysis techniques should not obscure the
strong requirement to enable information to be available rapidly for responders.
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In order to achieve rapid processing and delivery times, on-platform processing
of data should be considered to reduce data volumes for remote delivery from
airborne platforms to decision-makers, and airborne platform external
communications capabilities should be considered central to the effective use or
remote sensing.
It will be very important for airborne surveillance to be compatible with the CoP
in terms of products. There may be implications for products from some sensors
in terms of metadata, time stamping, positioning accuracy, codes, symbology,
units, naming, delivery mechanisms and formats.
Remote sensing creates large data sets, which require proper management not
only for OSR itself, but for post-event analysis.
Synergies between airborne and satellite derived information have to be
established and relevant case studies prepared.
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1. Introduction
Oil spills have the potential to threaten human health and safety, the integrity of the
environment and the viability of local economies, and the oil and gas industry has a
responsibility to seek out and deploy, all available technologies to both minimise the
risk of spills, and to deal effectively with them if and when they occur.
The April 2010 Gulf of Mexico (Macondo) oil spill incident, and the Montara incident in
Australia which preceded it, have had far-reaching consequences in prompting the reexamination by industry not only of operational aspects of offshore operations, but also
of an operator’s ability to respond in the event of an oil spill incident or well blowout. In
response to this, the International Association of Oil and Gas Producers (OGP) formed
the Global Industry Response Group, tasked with identifying learning opportunities both
on causation and in respect of the response to the incident. Nineteen recommendations
were identified and these are being addressed via a three-year Joint Industry Project
(JIP) funded by sixteen oil industry members. The Oil Spill Response JIP (OSR-JIP) has
initiated discreet projects or provides support to projects initiated by other trade
associations in the nineteen subject areas resulting from the OGP Oil Spill Response JIP
project. The OSR- JIP is managed by IPIECA on behalf of OGP in recognition of its longstanding experience with oil spill response matters.
Airborne surveillance is one such key technology which has been evolving rapidly in
recent years, with many more platforms, a greater variety of sensors, and improving
operational capabilities. This document provides an assessment of the capabilities of the
technology for OSR, identifies gaps, and provides findings for enhanced use of the
technology by the industry. This work forms part of work-package 2 “Airborne
Surveillance” of the OGP joint industry project (JIP) 8 “Surface Surveillance and
Tracking” for OSR, established to enhance industry practices in connection with oil
spills. The report covers both surveillance platforms and sensors.
2. Objectives
The objectives of the surface surveillance work are:
A review of intrinsic technical capabilities of airborne sensors, incorporating
information from literature, workshop reports and direct from commercial
vendors;
An assessment of current and planned future capabilities of sensors and relevant
platforms in terms of actual response to oil spills in different global locations, to
include timeliness of response;
Identification of technology and surveillance gaps;
Suggestions for follow-on activities, including research, technology development
and improved infrastructures, to close gaps.
Coordination with work from the API and other JIP tasks.
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3. Scope
This report focuses on surveillance capabilities of airborne platforms and sensors for oil
spill response, considering both intrinsic capabilities and practical, operational
capabilities. It is complementary to a similar report assessing surveillance capabilities of
satellite sensors for oil spill response [1]. Together, these reports cover remote sensing
technologies and platforms for oil spill response.
These two reports are also complementary to the API report on Remote Sensing in
Support of Oil Spill Response [2]. The API report provides recommendations in terms of
how remote sensing is integrated into the overall OSR activity; how to involve remote
sensing using a 5 step process in terms of teaming, key individual roles and links to
specific applications within OSR, and how to select the most appropriate remote sensing
technologies and platforms via an assessment of their strengths and weaknesses. This
OGP report does not address issues related to teaming and application to the broader
OSR activity; instead, it focuses on some of the practical issues associated with airborne
data availability. There is some overlap between the two reports in terms of providing
information on intrinsic sensor capabilities, but the results of the two assessments are
consistent.
The scope of this report can be described as follows:
Surveillance of oil spills from airborne remote sensing only, with an emphasis on
commercial suppliers;
Focus on effective selection of, and access to, remote sensing data rather than on
value-added analysis or downstream application of the data. For the latter,
OGP/IPIECA JIP 8 WP 5 on GIS/Mapping and Common Operating Picture (CoP) is
relevant [3] as well as the work of the API [2];
Detection and characterisation of oil spills and not other parameters, except for
identifying these additional parameters when they are a potential by-product of
data acquisition for OSR;
Surveillance of offshore and coastal domains; land and polar domains are
addressed briefly.
Sampling of the top 25 metres of the ocean surface only (i.e. not covering
atmospheric or deep ocean sampling).
Consideration of technical and operational factors in relation to airborne data,
and not commercial factors.
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4. Airborne Remote Sensing
4.1. Overview
Airborne remote sensing has its genesis in the late 19th century (using carrier pigeons
and balloons), but became fully established with the development of manned flight early
the following century. Basic photography was superseded later in the 20th century, with
the advent of digital techniques and exploitation of broader areas of the electromagnetic
spectrum. Now, unmanned aerial systems (UASs) are becoming available and could well
revolutionise airborne remote sensing for OSR, building on manned aircraft which have
provided the platform of choice for oil spill surveillance for many years.
A key role of airborne remote sensing is in providing wider coverage observation of an
area than is available from in situ observations, while also offering greater flexibility in
terms of timing and coverage than is available from satellite observations1. Airborne
remote sensing therefore provides strong tactical support for oil spill surveillance and
response operations, but extends to both strategic surveillance in combination with
satellites, and close tactical support for smaller platforms (Figure 1).
Figure 1. Schematic of the role of airborne remote sensing in OSR. Satellites can
provide an effective synoptic overview of the spill and field of operations and
airborne assets can be used for targeted surveillance and tactical support.
Airborne remote sensing involves the use of instruments that measure properties of the
Earth from within the atmosphere. The remote sensors on board these platforms cover a
wide range of electro-magnetic wavelengths from short optical wavelengths (covering
visible and infrared) to long microwave wavelengths. The human eye can detect only the
visible portion of this spectrum, which represents a very small component (Figure 2)
While data collected in the visible part of the spectrum is intuitively interpretable to the
human eye, other parts of the spectrum offer great advantages, notably in terms of being
able to see through clouds (microwave) and being sensitive to absorption or refraction
by oil (IR, UV).
1
Satellite observations tend to be clustered at particular times of the day.
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Figure 2. The electromagnetic spectrum, courtesy of NASA ([4]).
There is an opportunity with remote sensing to use different parts of the
electromagnetic spectrum in a complementary fashion, notably to counter sampling
limitations and to resolve false target (oil spill) alarms from more restricted sensing.
Key spectral bands are identified below for both passive and active sensing.
As
well
as
measuring
properties of the Earth at a
wide variety of wavelengths,
sensors are also designed to be
either active (transmitting and
receiving radiation) or passive
(receiving
naturally
transmitted radiation). The
ability
to
sample
both
naturally occurring radiation
and specially configured manmade radiation from across
the electromagnetic spectrum
is a key strength of remote
sensing technology (Figure 3).
Figure 3. Schematic illustration of passive and
active remote sensing.
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4.2. Passive Sensing
Passive sensors can collect electromagnetic radiation from across the spectrum, but
because they depend on natural processes, there are limitations in terms of diurnal
sampling (some need daylight), sensitivity to weather (primarily cloud cover, fog or
mist, which can absorb or distort the radiation) and effective spatial resolution (because
the radiation cannot be configured to enable high resolution to be achieved through
signal processing and other techniques).
Visible (VIS) imaging involves the use of colour in detecting and characterising oil spills
and in the case of airborne observations has historically involved trained observers, but
now also involves a range of sensors that can support more data intensive and analytical
assessment.
Infrared (IR) extends from near IR (NIR) to short wave IR (SWIR). In this part of the
spectrum, outside the range of detection of the human eye, there are absorption
wavelengths associated with hydrocarbons which can be useful for detection, and
potentially other characterisation, including ~1.20, ~1.72, ~1.75, 2.37 and 3.3 m. The
SWIR is able to be used through thin cloud, haze and fog.
The thermal infrared (TIR) part of the spectrum responds to both the temperature and
emissivity of the target. The emissivity is the efficiency with which incoming radiation is
emitted by an object, the reference being the idealised case of a black body, in which all
incoming radiation is emitted and none absorbed by the surface or object. The thermal
properties of a surface can be observed during day or night, which is extremely useful
for a time critical application such as OSR.
Passive microwave radiometers (PMR) detect naturally occurring microwave radiation
and are also sensitive to the emissivity properties of the surface. Passive microwave
radiometers can also be used during day or night, as in the case for TIR sensors, but in
the case of microwave sensors, there is less sensitivity to weather conditions.
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4.3. Active Sensing
Active sensors, including radar and laser, are able to observe the Earth during day or
night, having their own source of energy for illumination. The energy source is able to be
configured to optimise sampling of the surface, focussing the energy to achieve high
spatial resolution, for example, or to minimise atmospheric absorption. Because of the
complexity of the technology, these sensors come with their own challenges in terms of
data processing and interpretation. Coherent imaging sensors, for example, have
“speckle” which is a form of radiometric noise that is present when the data are
analysed at their full spatial resolution.
Laser is coherently transmitted optical radiation. The coherence refers to the control
over the radiation wavelength and phase. Although laser can be used during day or
night, it is impacted by atmospheric attenuation of the signal, for example in conditions
of fog or cloud. Laser can be used in a variety of ways to “interrogate” conditions on the
target surface, for example by:
measuring distance to the target (via time of flight of the signal) which may be
used to estimate surface elevation and in this configuration is known as “lidar”.
Over land, lidar may be used to assess vegetation canopy height and over the
ocean, may be used to penetrate below the surface, depending on specific
wavelength.
stimulating a fluorescent response in the target from UV radiation (excitation of
the target producing a unique spectral response distinct from the transmitted
signal, laser fluorescence) which is then detected and analysed to identify the
target;
stimulating an acoustic response in the target that can then be used to infer
properties of the target (laser acoustics);
detecting absorption from compounds emitted from the surface that can then be
used to identify the target (laser spectroscopy).
Radar also involves the transmission of coherent radiation, but at microwave
frequencies, and is sensitive to the roughness and dielectric properties of the surface
being imaged, the latter being strongly influenced, for example, by moisture content.
Radar can be used to measure distance to the surface, in vertically configured form, or
can be used to generate images of the surface. Radars measure radiation at a range of
wavelengths which are sensitive to different scales of surface roughness (typically from
mm to decimetre scale), and some of the longer wavelengths are able to penetrate
vegetation or even dry ground. Although radar sensors are useful because they can
observe the surface during almost all atmospheric conditions, radars are particularly
complex to interpret because they are sensitive to very different surface conditions to
those of optical sensors and the human eye, and so are far from intuitive to understand.
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5. Application of Airborne Remote Sensing to OSR
Airborne remote sensing is an established technology for OSR, but there is much more
experience in the use of the technology for OSR offshore, than over land or ice. In this
section, the application of remote sensing to OSR is described in terms of how the
various sensors are used, in relation to offshore, onshore and ice-related OSR. The API
has provided an overview of the advantages and disadvantages of many of these remote
sensing instruments [2].
5.1. Offshore Sensing of Oil Spills
The traditional method of surveillance for offshore OSR has been the human observer,
on board an aircraft. The observer is skilled and able to make use of the impact of an oil
spill on the reflectivity of the water to detect an oil spill, but can also use colour to assist
with estimating oil thickness, where the thickness is less than about 50 m. Above this
thickness, the true colour of the oil is dominated by the absorption characteristics of the
oil and is insensitive to thickness, but below this, the colour is a function of other optical
effects including sky reflectance. The modified Bonn Agreement [5] provides a guide to
the use of colour in estimating oil thickness on sea water, as shown in Figure 4.
Code
1
2
3
4
5
Figure 4. Bonn Agreement Oil Thickness guide (from [5]).
Description / Appearance
Layer thickness
Litres per km2
interval (µm)
Sheen (silvery/grey)
0.04 to 0.30
40 – 300
Rainbow
0.30 to 5.0
300 – 5000
Metallic
5.0 to 50
5000 – 50,000
Discontinuous true oil colour
50 to 200
50,000 – 200,000
Continuous true oil colour
200 to >200
200,000 to >200,000
The difference in reflectance between oil and water is enhanced in the case of
shorter wavelengths and so detection may be improved by filtering out any response
above 0.45 μm and by using cameras oriented at the Brewster angle of water (i.e. at an
incidence angle of 53°), in conjunction with a horizontal polarising filter [45].
With thicker oil, the visible spectrum is more sensitive to air bubble entrainment and
the oil to water emulsion ratio and interpretation of oil spill conditions increasingly
depends on the shape and texture of spill as evident in the imagery. Aerial photography
and video is able to record observations from the observers, and to extend similar
observations to unmanned aircraft.
At the ultraviolet (UV) end of the spectrum, the refractive index of oil is particularly
strong compared to water, and this has been exploited by UV cameras, in order to
provide sensitivity to thin oil, down to less than 0.1 μm in thickness. However, these
sensors are insensitive to oil thicker than about 10 μm [6].
At the other end of the optical spectrum, thermal sensors and Forward Looking IR
sensors (FLIR) are able to exploit the fact that the oil absorbs more radiation than sea
water, and so has a lower emissivity and appears cooler than sea water at night (when
the temperature of the oil and sea water are the same). When there is incoming solar
radiation (during the day, and shortly afterwards), the oil will have a higher
temperature than sea water in part because of its lower emissivity and heat capacity.
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Figure 5. Optical spectra of oil
emulsion from the Gulf of
Mexico Deepwater Horizon oil
spill, sample collected May 7,
2010. At visible wavelengths the
oil is very absorbing and does not
change colour significantly with
depth. At infrared wavelengths,
both reflectance levels and
absorptions due to organic
compounds vary in strength with
thickness (from [7]).
Remote sensing achieves most value, in principle, when it involves the combination of
sensors operating at different parts of the electromagnetic spectrum. IR and UV
imagers can be used to estimate thickness from as little as 0.01 μm (UV) to >10 μm (IR).
Multispectral sensors extend imaging across the optical part of the spectrum. In some
cases, these include the IR region where there are a number of absorption features for
oil that can be compared to open water (Figure 5). By sampling a range of frequency
bands, multispectral sensors can be used to resolve false alarms and to extend sampling
(for example to dusk/dawn using SWIR). Hyperspectral sensors extend this concept
further, with enhanced spectral resolution recorded in a few hundreds of channels
across large parts of the optical spectrum, giving the sensors the ability to resolve the
unique spectral signatures associated with specific surface and atmospheric compounds.
While this is associated with greater complexity and challenges involved in processing
of the data, particularly in an operational environment, it can be simplified by the
selection of the most sensitive spectral bands and associated derived products.
Figure 6. The AVIRIS hyperspectral instrument was flown over the Gulf of Mexico
during the Deepwater Horizon oil spill in 2010. The hyperspectral imagery is shown as
a stack behind the visible image of the Gulf coast, with two atmospheric absorption bands
visible. Image courtesy JPL/NASA.
Microwave Radiometry (MWR) is capable of detecting and mapping oil layers
exceeding a thickness of a few tens of microns. They achieve this by detecting the impact
of the oil layer on upwelling emission from the ocean surface, which is absorbed more
by a thicker layer of oil (oil has a higher emissivity than water in the microwave band).
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These devices are capable of mapping oil layer thickness in the range from 50 to 3,000
m and are thus complementary to thin film thickness measurement techniques. The
principle of MWR is similar to that of thermal imaging. However, a thermal imager does
not ‘see’ the sea surface in the presence of clouds2 since IR radiation is absorbed by the
water droplets of clouds. Furthermore, the thermal emission of seawater measured with
a MWR Scanner is dependent on temperature and salinity, while the thermal imager
signal depends on temperature but is not sensitive to seawater salinity.
Laser is a particularly powerful technique for OSR, as it forms the basis for a number of
sensors that exploit a range of properties of the interaction of coherent light with oil and
water. Laser fluorometers send short laser pulses (5–20 nanoseconds) towards the
water surface, typically at UV wavelengths of 0.300-0.355 μm. The laser excites certain
compounds in the oil which are then detected in the return signal between about 0.400
and 0.650 μm, with peak response around 0.480 μm. The precise wavelengths at which
this excitation occurs can be indicative of the type of oil (light oils tend to fluoresce at
blue wavelengths and heavy oils at green wavelengths), and many naturally occurring
materials (such as chlorophyll) excite at different wavelengths thus creating fewer false
alarms than many other types of sensors (e.g. against biogenic and mineral oils, Figure
7). If timing information is recorded through range gating, it is possible both to exclude
direct laser backscatter from the signal, and to potentially distinguish surface and
subsurface oil. In systems with multiple excitation and response wavelengths, oil type,
condition and thickness (thin layers) can in principle be characterised. Laser
fluorometers are particularly important for offshore remote sensing of oil.
Figure 7. Fluorescence spectra
of different oil types upon
irradiation with UV light at
0.308 m wavelength, courtesy
EU SEOS project. The curves show
the intensity of the fluorescence
versus the wavelength between
0.320 m (UV) and 0.685 m (far
red). The curves are normalised to
the same total (i.e., integrated over
all wavelengths) fluorescence
intensity in order to highlight the
shape of the spectra. The absolute
fluorescence intensity of heavy oils
is much weaker than that of light
oils [8].
Laser fluorometry can also be used to estimate oil thickness via the subtle process of
Raman scattering, in which the UV radiation interacts with water molecules to create a
light emission that is a function of the vibrational frequency of the water molecules and
frequency of the incident radiation (Figure 8). The suppression of this signal is related to
the thickness of the oil layer [9].
2
Assuming that the sensor is located above clouds; some platforms could be operated below the
clouds.
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Figure 8. Raman scattering
from sea water, courtesy EU
SEOS
project.
Emission
spectrum of a water sample
from the North Sea illuminated
with ultraviolet light at 0.270
m wavelength. The narrow
peak at 0.300 m is Raman
scattering of water molecules.
Fluorescence of substances in
water is spectrally much
broader [8].
Laser acoustic sensors can be used to estimate oil thickness by exciting an acoustic
response from a pulsed IR signal. The acoustic response is modulated by the thickness of
the oil, which in turn is transmitted into the reflected laser signal in the form of a
Doppler shift.
Radar are deployed as forward-looking and side-looking radar systems (FLIR and SLAR,
respectively), with real apertures and therefore relatively coarse spatial resolution, or
synthetic aperture radar (SAR) systems that are able to use the motion of the platform
to generate high spatial resolution in the direction of the platform motion. The
microwave radiation interacts with the small scale roughness on the ocean surface
(wind generated capillary waves and short gravity waves) to generate backscatter. A
rougher surface generates more backscatter for imaging radar sensors. Because the oil
tends to dampen short surface waves, less backscatter is returned to the radar sensor
than from open water and so oil tends to appear as dark areas in imagery also
containing open water.
Figure 9. Principle of radar
scattering from an oil spill vs.
open water, courtesy EU SEOS
project. More backscatter is
returned to the aircraft from the
open water than from the oil spill,
because the latter dampens the
small scale surface roughness and so
acts somewhat like a mirror to the
incoming radar [8].
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Table 2. Overview of the application of airborne sensors to offshore OSR.
Sensor types
Human
observation
Photography
and video
UV sensors
Passive
Optical
Multispectral
optical and
thermal
Application
Ready deployment for
general reconnaissance (oil
mapping and other
characteristics)
Recording human
observations; mapping
coastal environments; preand post-spill impact
assessments
Detection and mapping of
thin oil
Integrated sensors that
combine different sensing
configurations to enhance the
range of surface sampling
conditions (e.g. night using
TIR), and compensate for
limitations of single
configurations (e.g. thin and
thick oil sensing from UV and
IR sensing respectively);
reduced false alarms by use
of multiple sensors.
Sampling
Requires clear
atmospheric
conditions and
daylight
Enhanced
sampling of oil
from combined
sensors. Daylight
only for VIS, but
extended to
night and day by
use of TIR.
Clear
atmospheric
conditions
required
Requires clear
atmospheric
conditions and
generally
daylight.
Hyperspectral
Laser
fluorosensor
Comprehensive observation
of oil (type and thickness);
sub-surface oil under certain
conditions
Requires clear
atmospheric
conditions.
Passive Microwave
Detecting and mapping of oil
in almost all atmospheric
conditions with non-extreme
metocean conditions,
including oil thickness.
Day and night,
through cloud,
fog and mist
Active
Microwave
(radar)
Detecting of oil (location and
extent).
Day and night,
through cloud,
fog and mist
SAR and
SLAR
HSE constraints,
tiredness,
interpretation
differences, false
alarms
False alarms
False alarms
Potential comprehensive
observation of oil (type and
thickness, perhaps condition)
Active
Optical
(lidar)
Limitations
Other constraints
Operational challenges
in terms of availability,
skilled operation and
interpretation, and
delivery times.
Not yet proven
operationally (large
data volumes and
complexity of
interpretation)
Limited availability and
operational complexity.
Does not detect thin oil
<50 m; constraints on
surface oil detection in
high winds and sea
states.
Constraints on surface
oil detection in high
winds and sea states;
no proven method to
obtain information on
thickness or other
properties.
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5.2. Onshore OSR
The detection of oil onshore, and in rivers and estuaries, is a complex challenge for
airborne remote sensing. There are three areas in which remote sensing can help with
onshore oil spill response as follows:
Direct detection of oil spills. Detection of surface oil in the onshore environment
has historically relied on airborne sensors. In an emergency, only direct
detection methods are appropriate, including such techniques as multispectral
and laser fluorescence. Thermal imagery may also be useful for heat detection
associated with (for example) pipeline breaches, or from the impact of spilled oil
on emissivity. Laser spectroscopy can be used to detect the presence of
particular compounds in the atmosphere such as ethane and methane emitted
from oil, through differential absorption on two or more transmitted
frequencies. Hyperspectral sensors also have potential over land. Reflected
energy from oil, even when mixed with soils, will respond to absorption features
that are an inherent property of oil. The background soils/materials help with
the detection of oil through absorption of the oil by the soils, leaving a residue
that may be detected for weeks or even months by hyperspectral sensors.
Indirect detection of oil spills. At its simplest, it is possible to use multispectral
imagery in an empirical fashion to be indicative of the presence of oil, or the
effects of oil, on the environment. In this case, time series of observations are
particularly valuable. If a release has been persistent for a period of weeks it
may also be detected from stressed vegetation. In these cases, the normalised
difference vegetation index (NDVI) may be useful, this being a simple
quantitative indicator of photosynthetic active biomass, which exploits the fact
that chlorophyll causes considerable absorption of incoming red light, whereas a
plant's leaf structure creates considerable reflectance in the NIR, leading to a
reduced NDVI value over time for degraded vegetation. NDVI can also exploit
radiation in the more specific wavelength range of 0.69 m to 0.74 m, the socalled red edge part of the spectrum, for enhanced sensitivity to vegetation
degradation, and some sensors sample this region specifically for this purpose.
Remote sensing can also be used to detect potential oil spill threats in the form
of third party encroachments (e.g. through the detection of vehicles) from
multispectral imaging.
Up-to-date information on local conditions to support OSR. Effective OSR
depends on the ability to access to an area (roads, landing sites, etc), the
availability and locations of facilities and buildings, environmental conditions
(land cover, the condition vegetation, coastal configuration, etc.) and the
presence of any hazards that might interfere with OSR. Remote sensing can
provide information on all of these, typically from multispectral imaging, and
in particular from very high resolution optical imagery.
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Figure 10. Left: example of oil on land. Right: graphic giving an example of how
NDVI is impacted by vegetation degradation (courtesy ESA). NDVI = (NIR — VIS)/
(NIR + VIS).
Baseline imagery is particularly important for onshore oil spills, in the form of an
archive of good quality baseline optical imagery in key areas, to support rapid
assessment of oil spills and local conditions from new imagery. This imagery would need
to be high spatial resolution, ideally with spectral frequencies that are sensitive to the
presence of oil or related conditions such as vegetation condition, that can be directly
compared to post-event data. Digital elevation models (DEMs) are also important for
effective use of remote sensing imagery onshore. A good quality DEM together with
accurate surveyed ground control relative to a known coordinate reference system is
required for accurate geocoding of imagery to remove topographic distortions in the
data, which can lead to significant positioning errors. Remote sensing data can provide a
moderate quality DEM in many areas, where one does not already exist. Again, this can
form part of the requirement for good baseline imagery.
Onshore and coastal environments are often served well by flexible airborne
platforms including helicopters, because of the need for flexible and low level flight
planning (dealing with topography, coastal configurations and pipelines, for example).
Onshore oil spill remote sensing remains an area that requires research to define the
best sensor configurations for detection and monitoring of oil spills, although
multispectral and hyperspectral sensors appear to be the most viable to date.
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5.3. OSR in low visibility and ice
The use of remote sensing for OSR in conditions of low visibility and ice is covered in a
separate JIP and so will not be covered in detail here. Instead, we summarise the main
results from that activity, in particular referring to [10].
In conditions of low visibility and ice, it is clear that passive optical sensors are more
restricted in their use. TIR sensors are less restricted as a result of their ability to be
used during night, but atmospheric conditions common in many areas such as fog and
low cloud (notably around the marginal ice zone of the Arctic) will impact on all optical
sensors.
Active sensors have more robust applicability to these environments. Active optical
sensors, such as laser fluorometers, may be used where atmospheric conditions are
clear, but darkness prevails (for example, during the long polar night). Laser in
particular has potential in conditions of ice, where detection of oil has been proven, even
in pack ice. Microwave sensors, including PMR, SAR and SLAR have value for detecting
oil under the entire range of low visibility conditions and have some potential for
detecting oil in ice too, but [10] indicates that there will be significant ambiguity in their
interpretation. Ground penetrating radar (GPR) at a lower frequency (typically <1GHz)
has potential to detect oil under snow and ice because it penetrates effectively into snow
and ice, so that it has the potential to “see” oil that is invisible to the eye, and has been
demonstrated from a helicopter platform at least for penetration beneath snow [11].
A key factor for detection of oil in ice lies in the ice concentration (percentage ice
coverage in open water) and in whether the oil is located on the sea-ice (or snowcovered sea ice) surface, or within or beneath the sea ice. In cases where the oil spill is
interspersed in ice that has an area concentration in open water of <30%, it is likely that
the spill will be detectable, albeit less easily, using similar methods to those described
for open water (although polar latitudes are very limited in terms of daylight for optical
sensing during winter months). When the ice concentration increases to between 30%
and 60%, the detection of the oil by airborne remote sensing becomes considerably
more challenging because of the ice floes masking or confusing the signature of the oil. If
the ice concentration is above 60%, then it becomes probable that the oil will be
entrained with the ice and will move in response to currents and winds, yielding fresh
oil the following spring. Because it may be difficult to detect this oil, it may also be
difficult to track the oil, although it is possible to track ice in remote sensing imagery, if
it is known a priori to be contaminated with oil.
Figure 11. Left: example of oil in sea ice (source: USGS/Creative Commons). Right:
schematic showing the pathways of oil in sea ice (from [12]).
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Remote sensing tends to sample the surface of sea ice, particularly saline sea ice, and so
any oil that is not present on the surface of the sea ice may not be detected by the
instrument. Even if the oil is between the ice floes, rather than underneath them, it may
be difficult to detect, because the ice signature may overwhelm and complicate the oil
signature, particularly as sea ice takes a wide range of physical forms from very young,
thin and smooth nilas ice (<10cm thick) to multi-year ice which can be several metres
thick.
Although the challenges for use of remote sensing in low visibility and (especially) ice
conditions are daunting, it is clear that some sensors have significant promise, in
particular hyperspectral, laser-based sensors and microwave radiometers. Laser
fluorometers may detect oil even in pack ice conditions. However, significant research is
required to determine the practical and operational capabilities of these sensors.
Another key limitation to airborne detection of oil in ice is the frequent remoteness of
the oil spill site from major airfields and associated aircraft and facilities. Availability of
aircraft maintenance and re-fueling facilities must normally be within close enough
range to allow an aircraft to fly for at least 1 to 2 hours over the affected site. if the oil
spill site is very remote, this can be a problem for airborne surveillance due to the
limited autonomy of aircraft, but also for reasons of safety (e.g. availability of alternative
landing sites in case of emergency). It is for reasons such as these that ice-prone areas
are strong candidates for the application of UAS platforms and it is likely that the Arctic
in particular will be an early testing ground for this technology, although this still
presents challenges as many UAS platforms require an operational team on the ground
in fairly close proximity to the surveyed site.
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6. Methodology
6.1. Overview
The source material for this assessment of airborne remote sensing capabilities for OSR
includes the following:
Open literature which (a) reviews experiences from oil spills and (b) reviews or
assesses specific remote sensing technologies for OSR (e.g. see [13], [14], [15],
[16], [6]).
A workshop held in Frascati, Italy, 18-19 February 2013 ([17]), with
questionnaires sent prior to the workshop. The workshop was sponsored by
IPIECA and hosted by the European Space Agency (ESA), and included both
invited presentations, vendor pitches and discussion sessions. The workshop
invited the participants to specify requirements for OSR and to identify current
capabilities and gaps, leading to a set of findings.
Post-workshop questionnaires sent to commercial airborne platform (total of
139) and sensor suppliers (43). The questionnaire solicited vendor suggestions
on which sensors are appropriate for OSR, the capabilities of the sensors and
platforms in terms of sampling and responsiveness, and suggestions in terms of
configurations and processing.
6.2. Airborne Surveillance Analysis
The analysis of airborne surveillance capabilities has been assessed with respect to eight
diverse sample areas (Figure 12). These sample areas are entirely theoretical, involve no
oil release, and have been selected to cover proximity to oil and gas activity, a range of
scenarios from exploration to production and transportation, and wide geographic
coverage.
Figure 12. Eight test areas used for assessing OSR capabilities (not linked to actual
oil spills).
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7. Oil Spill Response Requirements for Airborne Remote
Sensing
The requirements that apply to the use of airborne remote sensing in OSR are
summarised in Table 3, and derived from the work of the API [2]. The API report
provides guidance on the effective incorporation of oil spill remote sensing technology
into OSR.
Table 3. Airborne Remote Sensing Requirements for OSR, from [2].
Role
Information
lead time
INITIAL ASSESSMENT
SYNOPTIC MONITORING
Verification and quantification of
spill
Situational awareness at the
source;
Determination of the extent of the
release and other characteristics;
Support to selection of appropriate
recovery methods.
Monitoring spill and evaluating and
supporting response
Spill extent, location, tracking and
condition;
Identification of resources at risk;
Support to modelling / forecasting
Support to tactical operations
including: mechanical recovery;
application
of
dispersants;
controlled in situ burning; shoreline
assessments.
Logistical support, e.g. access to
coasts
Goal: 3 hours from spill alert, or other emergency request, to data acquisition;
Minimum requirement: 24 hours from emergency request to data available.
Information
latency
Goal: available for access (with quality control) <1 hour after acquisition
Revisit
Minimum requirement: daily (365 days per year)
Sampling
Goal: 100% of spill with spatial resolution << expected spill dimension.
Oil
parameters
Minimum requirement: oil extent;
Goal: concentration, type/condition, thickness distribution, depth distribution.
Other
parameters
Goal:
(a) Pre-spill baseline conditions (environment, infrastructure, etc.) for impact
assessment, elimination of false alarms, etc.
(b) Post-spill near real time conditions:
Nowcast and forecast meteorological, ocean, land and ice
environmental parameters as appropriate;
Hazard identification, locations and evolution;
Asset locations, condition and access.
Other critical
requirements
Minimum requirement: compatibility with Common Operating Picture (see
below).
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The Common Operating Picture (CoP) is being developed as part of JIP 11 / WP 5 of the
Oil Spill Response JIP [3]. This is critical as a source of requirements for surface
surveillance. The CoP has the goal of identifying the following:
•
•
•
•
What data need to be available?
Where does it come from?
What format should it be in, and to what spatial accuracy?
How should it be delivered?
The outcomes of WP 5 are to align with the Incident Command System (ICS) model. WP
5 is being conducted in close coordination with WP 1 - In-Water Surveillance as well as
WP 2 – Surface Surveillance of Oil Spills.
It is clearly necessary for both the planning of, and outputs from, remote sensing
technologies to comply with, and play a role in helping to define the CoP.
Figure 13. Illustration of the Common Operating Picture, highlighting geospatial
information (courtesy, Roger Abel).
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8. Airborne Platforms for OSR
Airborne platforms have traditionally provided the most effective platform for OSR,
being able to be deployed specifically for the task at hand. They are usually
manoeuvrable and potentially able to be deployed at very short notice to one or more
locations simultaneously. Some aircraft come with pre-integrated sensors that can be
used for OSR. Some of these, as well as others, can be used to host portable sensor
packages.
There is now a broad array of aircraft platforms. Traditional manned fixed and rotary
wing (helicopter) platforms are being augmented by unmanned aerial systems (UASs)
that are developing rapidly in terms of technology, cost and regulatory environment.
The wide and growing range of costs and capabilities of these platforms requires careful
and ongoing evaluation for OSR to ensure that decisions on deployed assets are not
based on outdated information.
The minimum requirement for aircraft is that they should have the following [17]:
Compliance with local and international aviation regulations (and associated
certification);
Flight permissions;
Supplemental Type Certificates (STC) that allows an airborne operator to install
and operate a given sensor on board a given aircraft platform (regardless of the
location where the aircraft is flying).
Flight plan that relates to oil spill observation requirements;
Good downward visibility for surface surveillance (manual and/or sensor);
Slow speed capability;
Effective communications with vessels or ground (robust, continuous and with
sufficient bandwidth, which might be direct or via satellite);
Adequately trained and equipped personnel, for operating the platform (in situ
or remote) and sensors and/or making manual spill observations;
Sensor suite incorporating a minimum of digital camera or video for recorded
observations of the spill, with positioning information and with data link to the
oil spill control centre;
High accuracy dynamic positioning system including GNSS (global navigation
satellite system), gyro and inertial sensors integrated with the sensor suite.
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8.1. Manned Aircraft
Overview
Traditional manned aircraft are able to cover large areas from a wide range of altitudes,
and so are well suited to offshore oil spills in open water. Most OSR sensors can be
deployed and operated from fixed wind aircraft, with ranges reported in the survey as
being from 900 to 3,000 km, and altitudes up to 10,700m [18]. Many are readyequipped for OSR with relevant sensors fully integrated, including high definition
electro-optical and infrared cameras and video. Common models include L-3 Wescam
MX-10 and 15, the Cloud Cap TASE 400 HD EO/IR, the Microsoft Vexcel Ultracam XP, the
Leica ADS40/ADS80, Intergraph DMC and the Optimare line scan systems. However,
many platforms contain more additional sensors that are more directly applicable to
OSR, including forward-looking infrared sensors (e.g. HRC Photon MWIR NIIRS 7.1),
side-looking airborne radar (e.g. SLAR-9000 from Terma), synthetic aperture radar (e.g.
Selex PicoSAR), microwave radiometry (e.g. Optimare MWR), laser fluorosensors and
hyperspectral sensors (e.g. from Advanced Coherent Technologies) [18]. Most of the
manned platforms included in the survey have significant capacity for portable sensors
over and above integrated sensors, ranging from 90 to 650 kg, allocated variously
between the interior, nose and belly pods.
Not all manned platforms are designed for near real time monitoring from sensors. A
significant portion use satellite communications or microwave links which can be used
by sensors, but others rely on hard drives or voice communication, the former with data
distribution (for processing and/or end user delivery) on landing. In some cases,
however, the sensors are fully integrated with the platform in order to benefit from the
flight management system and communications. Many models of some of the larger
sensors with significant power consumption can only be deployed on manned fixed
wing aircraft, including laser fluorometers and SLAR systems. This is also true of many
of the integrated sensor packages. However, with sensor miniaturisation, this situation
is changing.
There are always cases where unmanned platform observations (from satellites or UAS)
may need verification or augmentation by direct human observation. Given this, and the
mature regulatory environment for manned aircraft, manned aircraft remain the prime
response platform for OSR.
Figure 14. Left: the Islander BN2A-26. Right: the DA42 MPP that supplements the
Islander on longer loitering surveillance (both photographs courtesy Richard Blain,
Aerospace Resources Ltd).
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Figure 15. Heliwest BO 105 helicopter,
with a range of 250km, and a vertical
range of 5000m, courtesy Luke Aspinall,
Heliwest Group.
Manned aircraft operate in a mature regulatory environment, which is extremely
important for planning their deployment and being confident in their practical
availability, unlike the case for UAS. However, at the same time, this regulatory
environment can create significant delays in availability which need to be avoided at all
costs in an OSR event. Hence, pre-approvals and advanced planning are more often
required than with traditional platforms.
Availability
A survey of deployment times was carried out by approaching suppliers of aircraft
services. Of 13 manned aircraft suppliers who responded, 10 indicated availability of
aircraft within 96 hours for OSR in at least one of the eight test regions. Geographical
details of the response capabilities are shown in Figure 16 and Figure 17. The former
map shows the differences in rapid deployment capabilities even among the limited
sample of the survey while the latter map shows the estimated times for deployment to
the eight test areas from respondents ([18]). The response times do not reflect the use
of local aircraft providers, but rather the response time of a limited number of
international commercial providers. Despite the low sample number, some features
stand out such as the low deployment times in cases where the aircraft are already
available locally (and assumed on standby under contract, as in the case of Alaska, North
Sea and Gulf of Mexico). It is also notable that the deployment time is significantly worse
in an area like south of Asia (SW of Sumatra), where none of the respondents to the
survey have relatively accessible aircraft.
Figure 16. For each test region: the percentage of survey responders providing
manned aircraft that indicate the ability to deploy their platforms within 96 hours,
assuming regulatory approvals.
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Figure 17. Reported platform deployment times to the eight test areas in hours,
from the survey [18]. Deployment times are truncated at 96 hours.
Note that in some cases, aircraft available for dispersant application also have
surveillance capabilities with appropriate sensors (e.g. the Aberdair EMB-110 P1
'Bandeirante' based in Kenya).
Challenges
The various factors involved in the availability of airborne platforms for OSR are shown
in Figure 18. In the case of manned aircraft, in most cases the aircraft will have been
approved for air worthiness. However, the platform may not be available for rapid
deployment because there is no contractual vehicle in place to enable immediate
deployment. The platform may be deployed on another mission and even if it is available
opportunistically, then time will be spent placing a contract to support deployment. An
example is the Sundtair LN-KYV aircraft, which are under the control of the Norwegian
Coastal Administration for OSR, and would be available for OSR outside their
jurisdiction only with the NCA’s permission. There are several examples of platforms
equipped for OSR which are in this situation and would only be available by prior
arrangement or opportunistically. Availability is also determined by maintenance
schedules. These must be strictly adhered to. For example, it is common for twin-engine
aircraft to have engine or aircraft scheduled maintenances every 50 or 100 hours. This
maintenance can ground the aircraft for one or more days depending on the level of
maintenance required.
It is also critical to deployment whether the platform is already based in the local area
(defined in terms of local jurisdiction for airspace and communications). If the platform
is locally based, then it is assumed that it has all the necessary approvals for local
deployment for OSR, with the only limit being pre-flight approvals (in relation to
weather, air traffic control, etc.) and supplemental certification for any additional
sensors. In this case (and if the platform is available on standby), deployment times can
be as little as a few hours. The Diamond 42-OPP, based in Alaska, would be available
between 1 and 6 hours for an oil spill off Alaska, for example (subject to not being
involved in an alternate mission).
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Figure 18. Airborne platform availability factors.
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Where the platform is based outside the local airspace jurisdiction, then there are a
large number of approvals that need to be in place before deployment can take place,
including export and import licenses (where applicable), permission for flight
operations in the local jurisdiction, permissions for intermediate over-flights and
availability of communications bands (including for sensors where required). Approvals
for sensor mounts are often difficult to acquire for existing non-dedicated aircraft. In
some cases, importing airborne platforms can be very difficult and time consuming
(several days to several weeks, in many cases), to the point where it is practical only to
consider sourcing local aircraft. Where permissions are in place for remote deployment
of an aircraft (as well as the platform being available on standby), the deployment time
tends to be 24 hours upwards (depending on flight distance and autonomy of aircraft
and maintenance schedule, but in some cases flight time limitations for pilots). The
practical considerations of deployment include the availability of a suitable runway for
fixed wind aircraft, with local facilities, as well as suitable weather for the deployment.
There are restrictions on the platform operations associated with the distance to
maintenance and refuelling facilities.
There are many situations in which manned fixed wing aircraft are not ideal for OSR.
Although sensors may be able to be operated safely and effectively under most weather
conditions, manned platforms are always subject to weather limitations for deployment.
In many areas of the world, flight cancellations due to weather are quite common.
Manned aircraft are subject to rigorous constraints in terms of pilot health and safety
and fatigue can be a significant factor in OSR. Effective use of manned aircraft depends
on having available personnel, including back-up.
Finally, some potential locations for OSR can be limited in terms of base locations for
fixed wing aircraft with suitable runways and facilities and require the cooperation of
local authorities. Many of these challenges are mitigated by sourcing local aircraft.
Opportunities and Emerging Capabilities
Given the challenges associated with deploying aircraft to foreign jurisdictions and over
long distances, there is clearly a need to source local aircraft that already have the
necessary permissions in place for OSR. It is clear that there is a requirement for each
area of potential OSR to identify local platform providers and to ensure access to these
aircraft through an appropriate retainer agreement in the event of an oil spill. As a
minimum for rapid response, the platform should have some sensors already available
in the aircraft, including visible and IR imaging sensors. Ideally, a complete suite of OSR
sensors would be available, but if not, then it should be possible to fly these in for
deployment on the aircraft with as much pre-authorisation in terms of licensing already
in place.
Many sensors are available in a portable form (see Section 9) and with miniaturisation
of components, new offerings are likely to become available that are increasingly
suitable for deployment, even on smaller aircraft. Sensor technology is evolving very
rapidly, and every year new sensors appear on the market with significantly improved
performances over the previous year's sensors.
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8.2. Unmanned Aerial Systems
Overview
Unmanned aerial systems (UASs) have a proven recent history of use for military
applications, but are now being promoted increasingly for civilian purposes. Until
recently, the UAS market was relatively small. In the mid-1990s, for example, the market
was probably less than $100 million annually worldwide. It has expanded more than
ten-fold in less than a decade, and currently about $3 billion is spent annually
worldwide on UASs (source: Teal Group Corporation).
UAS have the potential to fill an important gap in surveillance capability extending from
scales traditionally associated with fixed wind aircraft down to almost in-situ (close
tactical) scales. Some can fly at very low altitudes, with high degrees of flight flexibility
and with no human exposure. They are therefore complementary to manned aircraft
and, indeed, to satellites.
UASs come in a range of classes, defined in terms of their endurance/range, their
vertical range of operations and their payload capacity. These are illustrated in Figure
19.
Figure 19. Range and payload capacities of different types of UAV (adapted from
Frost and Sullivan). HALE=high altitude long endurance; MALE=medium altitude long
endurance; TUAV=tactical UAV; VTOL=vertical take-off and landing; MUAV=mini & micro
UAV.
UAS have three components: the platform (UAV) with sensors, communications system
and ground control station. These components can range from backpack portability, to
large systems which require large vehicle transportation. Larger UAVs require satellite
communications via an onboard terminal as well as a GNSS link.
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Figure 20. The Aerial
Drones
Octocopter,
including
related
equipment (courtesy,
Steven Tisseyre, Aerial
Drones).
UAS represent a new technology in the civilian domain, and so it is worth outlining their
potential (but not necessarily realised) benefits as follows:
UAS cover a range of scales of application for OSR, from strategic (MALEs and
HALEs) through tactical (TUAVs) to close-tactical (MUAVs) and so can in
principle be matched to operational requirements, helping to form a hierarchy of
observation scales.
UAS have degrees of flexibility that are not available to manned platforms. They
are able to fly at low altitudes, under clouds for example; they are less restricted
than many manned aircraft in where they can be launched from in many cases
(for example, from vessels, or even by hand); they can fly in hazardous situations
where manned flight may be undesirable, for example in the Arctic, or in areas
which might require tight manoeuvring (as along some coasts). Flight patterns
can be pre-programmed in many cases using satellite positioning or more
complex dynamic automation.
Some UAS have endurance. They are able to be operated remotely by pilots who
can operate in shifts if necessary.
Some UAS have long operational lifetimes because they can be retrofitted with
new state of the art sensors on top of a short development cycle (typically 1-2
years). The Tetra Exa OctoExplorer takes 3 weeks to manufacture to
specification and 6 weeks for a new platform, for example (AscTec Falcon 8). In
many cases, the construction is modular, which assists both construction and
maintenance.
There are significant health and safety benefits to not deploying manned
aircraft in some areas, such as the Arctic. Pilots need less onerous training and
none of the health checks associated with pilots, although UAS still require the
deployment of a team of operators on the ground near the area to be surveyed to
launch and recover the UAS, and the operator team still require standards of
support to carry out their tasks, in sometimes remote locations.
Some UAS can be used as communications platforms as well as remote sensing
platforms.
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However, it is important to be note that these benefits do not apply to all types of UAS
and there remain key constraints such as in relation to the regulatory environment for
their operation and in providing launch and recovery under certain situations. The
technology is evolving fast, costs are reducing, and models and capability are, and will
be, overtaken by new developments. Many of the current models are in experimental or
otherwise pre-commercial form.
Larger UAV systems have similarities to manned aircraft in terms of their size and
other characteristics. Their engines are often piston engines, turbofan or two stroke and
there is a requirement to incorporate sense and avoid systems. Their payload capacities
can be excellent, supporting a suite of remote sensing instruments, including the larger
sensors such as laser fluorosensors, synthetic aperture radar and hyperspectral sensors.
In principle, larger UAS can be used for flexible and persistent (strategic) wide coverage
surveillance, and can operate well above the altitudes of local response platforms.
Medium Altitude / Long Endurance (MALE) UAVs tend to operate at altitudes up to
about 15,000m. Their fuel capacity allows them to carry out surveillance lasting many
hours, with resultant flight range of hundreds of kilometres.
Figure 21. The Insitu
Integrator, which has
an endurance of 24
hours, operating up to
5,944 m and can hold a
total payload mass of
about
37
kg.
Photograph courtesy of
Chesua
Purnhagen,
Insitu, Inc.
.
High Altitude / Long Endurance (HALE) UAVs can operate at altitudes up to about
20,000m. They are typically used for major scientific studies and are designed
specifically for long endurance. HALE systems tend to be used for large-scale scientific
programmes, as spearheaded by NASA in the 1990s.
Figure 22. The solar
powered
Airbus
Zephyr HALE. The
Zephyr successfully
completed an 82-hour
flight, reaching an
altitude of close to
20km during a trial in
2008. The wingspan
is 23m and the
platform
weights
50kg.
Image
of
courtesy Paul Brooks
© Airbus Defence and
Space.
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Tactical Unmanned Aerial Vehicles (TUAVs) fill the capability gap between the short
range mini-UAVs and the long range, extended endurance MALE and HALE UAVs,
combining the flexibility of the smaller platforms with the longer endurance of the
higher-end platforms.
Figure 23. The Flying Fish TUAV
from
the
University
of
Michigan,
an
autonomous
unmanned seaplane capable of
recharge from solar cells,
supporting
relatively
long
endurance “hop and drift” flights,
courtesy Ella Atkins, University of
Michigan ([19], [20]).
Smaller classes of UAVs, typically less than about 25kg in mass, can be used for tactical
and also close-tactical surveillance ([21]), being extremely flexible, often using electric
propulsion (and so are quiet and create no pollution) and do not ordinarily need to
comply with air traffic control. They are often provided with high quality digital camera
and/or video systems (often with IR for night). Their capacity for payloads is in some
cases very limited, but some can take miniaturised sensors, including FLIR,
hyperspectral, thermal and SAR sensors. They can be very useful for surveillance in
hazardous locations (where manned flight would be considered undesirable or
dangerous); areas where extreme manoeuvrability is required (e.g. coastlines);
situations in which near continuous loitering over small areas is required. They also
have uses which can relate to OSR such as wildlife surveillance (helped by low noise)
and search and rescue. Their close-tactical capabilities enable them to be useful for
support in dispersant application and follow-up, real time assessment of spill evolution,
detailed assessment of structures (e.g. pipelines) and air quality sampling (subject to
available sensor). They are also in most cases readily deployed from most locations,
from vessels, by hand, from the ocean surface or from vertical takeoff. On the other
hand, they tend to have low endurance (and therefore limited range) and limited
altitude due to battery life, regulatory limitations such as maximum flying height and the
need to remain within sight of the operator at all times, and so for OSR, there is an
argument for access to 2-3 platforms to support continuous operation.
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Micro and Mini UAVs (MUAVs). MUAVs are potentially able to be transported in
backpacks, weighing typically up to 6kg. They operate at low altitudes with limited
battery capacity leading to flight times in many cases of the order of 5 to 30 minutes,
sometimes more. These typically have colour video payload systems. Examples include
the Lockheed Sanders “Microstar”, AeroVironment “Microbat” and “Black Widow” and
Lutronix “Kolibri” systems. They operate manually or via pre-programmed flights based
on satellite communications (i.e. GNSS).
Figure 24. The ASCTEC Falcon 8 MUAV. This has a flight time of 20 minutes, and can
carry a payload of up to 750g. The system comes with GPS, altitude sensor, compass, IMU
and includes camera, mobile ground station, batteries, charger and transport case,
courtesy Ramona Spät, copyrighted by Ascending Technologies GmbH.
Vertical take-off and landing (VTOL) UAVs are particularly useful in areas where
takeoff or landing runs are impossible, and they are also portable. The high power
consumption for hovering flight tends to limit their flight duration (typically to one
hour, based on electric motors and rechargeable batteries), although the largest
platforms can accommodate larger fuel capacity. Control is typically via line-of-sight and
for a quick analysis. They are readily deployable using a one or two man crew from
vessels, and the most challenging onshore environments.
Figure 25. The Aibot X6
VTOL UAV. This has a 30
minute flight time and can
host up to 3kg of payload
(courtesy, Friederike Nielsen,
www.aibotix.com).
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Availability
Some 1424 UAS designs had been registered in 2011 with UVS International, a nonprofit society that promotes UASs, more than double from 2005, while the number of
suppliers of these systems had also doubled to 511 ([22]). About one third of these were
developed and built in the US, which has been driving much of the growth in UAS
technology, with other providers in France, the United Kingdom, Israel, Russia and
Germany each with between 6.42% and 3.85% of the market. Skrzypietz (2011)
indicates that between 2005 and 2010, the number of UAS used for civilian applications
quadrupled [22].
A small number of UAS suppliers responded to the IPIECA survey and are summarised
in Table 4. It is probably true to say that the respondents are suppliers that view OSR as
a target market for their technology. No HALE suppliers responded, but there were
contributors from each other UAS category.
Type of UAS
HALE
MALE and TUAV
VTOL
MUAV
Total
Number of suppliers in survey
0
9
5
5
19
Number indicating availability
in <96 hours for OSR
0
6
5
4
15
Table 4. Summary of rapid response capability for airborne platform suppliers, as
reported in the survey [18].
The geographic distribution of response times for the eight different test areas is shown
in Figure 26. Although the sample is very small, the distribution suggests a fairly rapid
response time is possible in some cases, of the order of 24 hours, although the average
for those that are able to respond within 96 hours, ranges from 18-80 hours. However,
critically, this assumes that flight permissions have been provided, as have all other
regulatory requirements including export/import controls, etc. In practice, this
assumption is generally invalid for larger UAS, except in a small number of special cases,
but may be valid for smaller UAS that operate in situations that do not require permits.
MUAVs are generally quicker to deploy than larger UAS. This reflects the fact that they
are (a) sometimes available “in stock” (unlike large UAS); (b) readily transportable; (c)
quicker to make flight-ready.
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Figure 26. Reported platform deployment times to the eight test areas, from the
survey [18]. Deployment times are truncated at 96 hours. These figures assume
regulatory permissions have been obtained for platforms, which is generally not the case.
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Challenges
Thus, there are now a wide range of UAS to choose from, but the growing number of
designs and range of capabilities does not translate into a mature market, as shown in
Figure 27.
Figure 27. Airborne platform availability factors. The red boxes are particularly
critical for unmanned platforms.
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First, there are limited UAS available for rapid deployment, for the following reasons:
Many UAS are one-off experimental, or pre-production systems. The Flying Fish
UAS, for example, from the University of Michigan, is not available commercially
and would take perhaps 3 months to manufacture if ordered. The timing for
manufacture varies significantly from perhaps a few weeks for MUAVs to
months or longer for MALES. In the case of large UAS, ordering may be expected
(and recommended) to include customisation for OSR, which would add
additional time in the form of design as well as manufacture.
UAS units available in limited numbers are in most cases fully deployed and
therefore only available for OSR on an opportunistic basis. Availability for OSR
has been assessed by survey respondents on the basis that existing units have
already been purchased [18].
Apart from these supply factors, the challenges of UASs are significant and distinct from
those of manned aircraft, and reflect the lack of maturity of the technology for
operational uses ([22]).
In terms of airspace regulations, UAVs are in many jurisdictions fundamentally
prohibited from airspace, at least in cases where they are outside line of sight and/or
above a minimum mass. General integration of UAS technology into commercial airspace
depends on effective deployment of sense-and-avoid technology. In the USA, for
example, the Federal Aviation Authority Modernisation and Reform Act of 2012 has set
in motion progress towards integration of civilian UAS in US airspace by the end of
September, 2015. Similar developments are occurring in European airspace, but in many
other jurisdictions, there are no such initiatives. It is thus necessary to investigate local
regulations wherever the UAS will be needed, well in advance. Some suppliers are
already pre-approved for operations in particular jurisdictions, and it is worth
compiling a list of these.
There are challenges in relation to the allocation of the electromagnetic spectrum for
UAS communications. There are two issues here. First, some bands are pre-allocated and
therefore not available. Allen and Walsh point out that about 6MHz of bandwidth is
required between 0.4 and 3GHz to support smaller UAV and reasonable quality video
downlink operations [21]. The second issue is that non-allocated frequencies (which do
not required licenses) are not protected and, if used without protection, could result in
interference. In short, there is a need for the commercial UAS operations to have
frequency bands allocated for their use on an international basis, wihch would need to
be addressed via the International Telecommunication Union (ITU).
Export regulations are likewise restrictive, with the degree of challenge tending to
depend on the size of the UAS. Those platforms that have a range in excess of 300 km,
and a payload in excess of 500 kg, fall into the category of “complete delivery systems”
for the Missile Technology Control Regime (with 34 signatory countries), for example,
while if the payload is less than 500 kg, the platform falls into the category of “other
delivery systems”) and is easier to obtain export license. Key components of UAVs fall
under ITAR control, including GNSS units and inertial navigation systems. Export
controls prevent the ability to respond internationally with UAS without a pre-existing
license, most notably (but not exclusively) in terms of using commercial United States
UAS systems outside the USA.
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UASs potentially have to operate in inhospitable areas involving extreme operating
conditions (indeed, this is a potential key selling point for the technology). In these
cases, UASs may be required to operate in:
total darkness (in winter time at high latitudes);
in extreme temperatures (from -40°C in the Arctic or cold continental climates to
50°C in hot climates);
in challenging atmospheric conditions from spray icing (wing icing) and snow
and ice to dust and sand storms.
In some cases, these prove problematic. Solar-powered UAVs will not be able to operate
effectively in winter in high latitudes. UAVs that land on water, such as the Flying Fish,
will not be able to operate safely in ice-prone waters, and so the range of useful UAV
designs will depend on the location and environmental conditions of the area of interest.
It is also important to consider that many UAS still require the deployment of a team of
operators on the ground near the area to be surveyed to launch and recover the UAS.
Access to the site and safety must be taken into account in any such deployment, but
may also be a restriction in the case of extreme conditions and remoteness of site.
There are also political and societal challenges, which relate to data protection and
safety of the technology. For oil spill response, this is clearly less of an issue because
there is general public support for the use of UAS in emergency response (82% of the
German public supported the use of UAS for disaster relief, [22]).
High development and procurement costs also constrain the market. Depending on
the class of the UAS, this translates into a price of between a few $tens of thousands and
a few $M [23]. However, these are expected to reduce over time as UAS become
integrated into civilian airspace and the market becomes more competitive.
There is a distinction between larger and smaller UAS in relation to operational costs
including training of pilots and maintenance. Larger UASs require particular training
and skills to operate, based on simulators and significant logistical support (the InSitu
Integrator needs 4 people to operate, for example). Maintenance of smaller systems is in
many cases straightforward based on a modular design for ease of assembly and
replacement of components, with a short training course covering safety, but larger
systems can be reliant on custom components.
Many of the payload sensors and components are not designed or optimised for UAS
deployment. Many are simply too large or heavy, or require excessive power
consumption. Satellite communications terminals need to be small, where possible. On
MUAVs, the basic nature of some observations needs to be taken into account, for
example in some cases not being very accurately geo-referenced because of coarse
attitude information. It is important that the observations meet minimum standards for
the COP.
Finally, it has been suggested that there are “almost no quantitative studies” comparing
costs of UAS and manned platforms, which makes a cost-benefit analysis very difficult
[22]. Such a comparison would need to be updated frequently given the expected
rapidity with which UAS costs are likely to change over the coming years.
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Opportunities and Emerging Capabilities
UAS systems are not yet, as a category of platforms, operationally deployable for oil spill
response. Nevertheless, this will change over the coming few years. With this in mind,
the following table provides an indication of which types of UAS may be appropriate for
different types of OSR requirement.
Type of UAS
Endurance
Range
MUAV
2 hrs
80km
VTOL
8 hrs
~400km
TUAV
>24 hrs
~400km
MALE
>24 hrs
~5000km
Altitude
~800m
~5000m
~5000m
~3-15km
Lack of manned or
satellite observations
Faster tasking than
manned A/C or satellite
Very high resolution
(close-tactical)
mapping
Advanced sensors
High flexibility, near
real time flight plan
Continuous observation
required
HALE
>24 hrs
Global
~1220km
Parts of the day when no satellites overhead
Hazardous manned flight conditions (e.g. Arctic)
Lack of takeoff and landing
facilities
Low altitude surveillance under cloud
cover
Hazard assessment
Initial investigation of smaller spills
Infrastructure assessment (e.g. pipelines)
Logistics assessment
Detailed
Wildlife assessment (e.g. turtles,
mapping at
cetaceans)
distance
Coastal mapping
(e.g. Arctic)
Detailed environmental mapping
Detailed mapping of oil spill
Observations from micro-hyperspectral,
etc., for enhanced spill or impact
assessment
Intricate surface feature mapping (coasts,
rivers, etc)
Wildlife activity; spill development; spray impact (e.g.
hovering)
Table 5. Potential application of UAS to oil spill surface surveillance.
For longer term planning, UAS can be considered as part of the response for oil spills,
with smaller classes of UAS (MUAV, VTOL) being used for scales of observation
intermediate between that of in-situ monitoring and manned flight. The MUAV and
VTOL systems are very flexible, easily deployed and in many ways complementary to
manned aircraft. Larger UAS, which will become integrated into civilian airspace in the
next 2-3 years in key jurisdictions, are likely to serve specialised circumstances, such as
long range surveillance in cases where manned flight is hazardous or unavailable, such
as in the case of the Arctic. It is important to start planning now for how UAS should
become used in OSR.
In terms of UAS technology, there is a recognition that UASs need to be designed
carefully to provide backup systems and capabilities, and this needs to be taken into
account in any platform selection. A UAV can incorporate $100,000 worth of payload
(e.g. from a hyperspectral sensor and satellite communications terminal alone). For the
purposes of insurance, and health and safety, the following features are desirable in any
UAS ([24]):
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Multiple, independent, electrical power supplies;
Separate safety autopilot, able to land the UAV in the event of failure of the main
controller;
Distributed, on-board sensor network to provide early detection of potential
failures, so measures can be taken before a more serious condition develops;
Dual rudder as part of a dual redundant safety system;
Dual elevator as part of a dual redundant safety system;
Twin engines are a safety requirement in some cases.
There are also some benefits to designing automated take-off and landing capabilities to
minimise the potential damage from human error and these are being investigated.
Continued rapid evolution in platform capabilities are likely in terms of
endurance/range, power and even smaller sizes (with implications for portability and
cost and implications also for the variety of sensors that UAS will be able to operate in
the future).
UAS are evolving rapidly not just in terms of technology, but also in terms of the
commercial and legal landscape, with many opportunities. Allen and Walsh ([21]) have
reviewed the potential of UAS for oil spill response. Evolving capabilities for the use of
UAS include the following:
The regulatory environment for UAS is currently being developed in both
North American and Europe. In the USA, where the FAA is responsible for UAS
regulations, commercial UAS activities have effectively been prohibited to date,
although this is in the process of changing (expected in 2015). In the USA,
Conoco Phillips received approval to use UAS to monitor for oil spills and
observe wildlife off the Beaufort Sea coast in the Arctic Circle. This is the first
approved commercial use of UAVs in the U.S. by a private company (2013). In
Europe, there are also plans to integrate UAS into commercial airspace by 2016
following a adopted by the European Commission on 20 June 2013. These
developments are being supported by the development of sense and avoid
technology for UAV systems that share commercial airspace.
The costs of UAS are likely to reduce significantly over the coming years as
the market becomes more competitive. The doubling of the number of suppliers
over the period 2007-11 is an early indication of this. Costs are already coming
down for smaller UAS as off-the-shelf components are being incorporated into
the technology. Operating costs can also be higher for large UAVs than for
manned systems, based on the required logistical support.
The UAS market will mature as the UAS become integrated into commercial
airspace and supported by a clear regulatory regime (which will happen at a
varying rate in different areas of the world). A service sector is likely to evolve
offering consultancy in this area, and availability of leasing and on-demand
flights.
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8.3. Aerostats
Aerostats are tethered balloons (or other lighter-than-air craft) that gain lift though the
use of buoyant helium gas, deployed from mobile platforms or permanent
emplacements. They can therefore be considered either as airborne or in situ remote
sensing platforms. They are capable of being deployed to an altitude of up to 6,000m and
so can provide excellent tactical support to an area of operations, potentially covering a
few hundred km. Dependent upon their configuration, aerostats are capable of
providing 360° un-restricted sampling; such systems may also permit immediate
download to multiple users, thereby minimizing data latency and turnaround time.
These platforms can take significant sensor payloads, potentially up to 2,500kg.
Communications can be wireless and used to control the sensors as well as to receive
the observations, or in some cases may be via a wire to enhance capabilities.
Figure 28. The OceanEye aerostat, courtesy Vegard Evjen Hovstein, Maritime
Robotics AS.
Aerostats have the advantage of being both very cost effective and providing near
continuous observations at the close tactical level. The primary costs are often the
sensors rather than the platforms ([2]). They are also able to be deployed from marine
vessels or from land, and deployment can be rapid. The range of observations from
aerostats is necessarily limited, and they do not have the flexibility of UAS, but they have
a clear niche within OSR. An aerostat deployed with camera and IR sensor from vessels
at an altitude of about 130m is considered by some ideal for supporting oil recovery and
dispersants (NOFO, [17]). In addition, they are deployable with surveillance radars and
UHF/VHF radio & TV transmitters or repeaters.
Aerostat technology has developed significantly over the last two decades and is
currently used extensively by the military in both tactical (tens of cubic metres) and
operational (hundreds of cubic metres) applications. Comparative to fixed & rotarywing UAVs, aerostats are often subject to fewer flight operation & weather restrictions.
They are not generally subject to airspace regulations, although they can be subject to
regulations concerning visibility, altitude and other features (for example, under FAA
regulations in the USA, permits are not required subject to altitude ceiling of 500’ (150
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m) and operation at least 5 miles (8 km) from an airport, [1]. They can also be operated
with a minimum of training, personnel & maintenance, and are capable of remaining
aloft for extended periods of days to weeks or months, with 24/7 operation and real
time data transfer from sensors at full resolution (e.g. hyperspectral or radar sensors).
Relative to vessel bridge positions, aerostats provide an elevated height-of-eye and
extended visual-range, benefitting containment & recovery operations through an
enhanced encounter rate with spilt oil. The winch-operation of aerostats also provides a
practical solution to the recovery of unmanned aerial vehicles to a vessel at sea,
reducing the risk of potential loss. Aerostats can be used in response or monitoring
modes to augment existing aerial capabilities, however this dual-use assumes an
additional importance in SAR emergencies. Other specific applications of aerostats
include permanent deployment at identified vulnerable key assets such as off-loading
piers and FPSOs operating in isolation offshore.
Availability
As many as 32 companies are involved in the design or manufacture of more than 100
commercially available airships and aerostats in Europe, Asia, and North America [25].
Challenges
Aerostats cannot be used in strong winds, and so in some areas this might prove a
frequent limitation. The endurance of aerostats is normally limited by the helium
supply, in which case two aerostats may be used in rotation. Aerostat systems need to be
designed as lightweight but durable and resistant to weather. Stability is an issue for
positioning of data, particularly where no surface reference points are visible.
Emerging Opportunities
Aerostats are being improved with focus in the following areas.
Research is being carried out into materials and aerodynamic designs that can
enable aerostats to have reduced sensitivity to strong and/or variable winds.
Research is also underway into attitude control systems for aerostats.
As sensors become miniaturised further, and payload capacities increase for
aerostats, the capabilities of aerostats are likely to improve as platforms for OSR
surveillance including, for example, radar.
Aerostats may be used as communications platforms, as well as remote sensing
platforms.
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9. Airborne Sensors for OSR
Airborne oil spill remote sensing is normally divided into two different modes of
operation: far-range detection and near-range monitoring. Far-range detection often
uses airborne imaging radar systems, which usually cover swaths of several tens of
kilometres and are insensitive to weather or natural illumination. Suspicious structures
detected by airborne radar are subsequently investigated on-site using near-range
sensors. Near-range monitoring of oil spills includes mapping of relative and absolute oil
layer thickness, as well as classification of the type of oil. This mode of operation is
typically limited to swaths of several hundreds of metres at flight altitudes in the range
of 300–1,000 metres. There are a number of well-established near-range sensors, such
as infrared (IR)/ ultraviolet (UV) sensors, visible sensors, camera systems, microwave
radiometers (MWRs) and laser fluorosensors (LFSs). The API have provided an
overview of the advantages and disadvantages of many of these remote sensing
instruments [2].
It is also important to note that there are a number of additional surface observations
that can be made by remote sensing that are not directly related to oil spills, but are still
important for OSR, for example measurement of surface currents (Foley, [17]), sea
surface temperature and hazards that may be impacting on response (for example, sea
ice in some areas).
In this section, the sensors types are reviewed in terms of their availability, their
challenges in being used for OSR, and emerging opportunities (in terms of technology in
particular).
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9.1. Visual Observation
Overview
Much of the value of visual observation lies in the sophistication that can be applied to
the process, based on training and guidelines for interpretation. Unlike non-human
sensors, analysis is genuinely real time, incorporating visible signatures, shape and
texture, and other factors such as met-ocean conditions. Observers can also provide
critical ancillary information (e.g. other hazards, positions of vessels). The key
requirement lies in the quality of training, and the availability of guidelines and
standards.
Visual observation also normally comes
with a method of direct communication,
technical guides, GNSS and digital camera
or video. Guidelines on observation are
now available such as the modified Bonn
code (2009, [5]), but others exist.
Figure 29. Oil spill observer (NOAA).
Availability
Visual observation can be readily deployed, as long as a trained observer is on stand-by
and an aircraft is available. Otherwise, it may be necessary to bring in an observer.
Environment
Offshore
Onshore
Ice
Platform
Sensor
constraints
Lighting
Atmosphere
Surface wind 2-14
m/s (ideally 3-10)
Sea state < 2m
Clear: little or
Vegetation
Training required
Daylight
no cloud or fog
obscuration
Ice cover < 30%
(ideally)
Manned low flying aircraft required with flight permissions and appropriate flight
weather.
Table 6. Restrictions on the use of visual observation.
Challenges
Human observers are subject to a range of self-evident challenges that are not applicable
to man-made sensors, such as varying skill levels, human weaknesses, and subjectivity,
although these constraints are offset by many irreproducible abilities of human
observation.
Offshore
Onshore
Ice
False alarms
Operation
Analysis
Algal bloom, seaweed, wind
shadow, biogenic oil, kelp beds,
fish sperm, cloud shadow
Numerous (e.g. shadow, manmade materials, still water,
etc.)
Young ice types
Offshore false alarms
Personnel tiredness
and illness
Strict HSE rules on
personnel
Training requirements
Need for continuity of
observers
Subjective
Table 7. Challenges for the deployment of human observers.
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9.2. Aerial Photography and Video
Overview
Aerial photography and video provide important support to human observers and can
be used in conditions under which a human observer is not available. The sensors are
often easy to operate and have a relatively low cost. Guidelines on the use of
photographic and video imagery are provided by IPIECA [27]. Cameras come with a
range of qualities now that are expected, including the following [27]:
Very high resolution (>10 megapixels);
Video/still switch;
Capability for high speed (depending on platform, from 1/500° to 1/2000°);
Aperture f.8 to f.16 for maximised depth of field (focusing across the oil spill);
Moisture resistant;
Dust resistant;
GNSS tagged for location (either from the aircraft or separately);
Time and date tagged and other metadata provided;
Polarising filter to assist with visualisation of thin oil layers;
Anti-UV filter;
200 or 400, or even 800 ISO for poor visibility conditions;
A live feed.
As light diminishes below a certain level, some cameras can automatically switch to
night mode to make use of near infrared (IR) light to deliver high-quality, black and
white images. During the day, the camera filters out IR so that it does not distort the
colours of images as the observer sees them. As well as some cameras providing the
ability to collect photography in NIR, some cameras are used for photogrammetric
applications and collect stereoscopic imagery (with sufficient overlap between frames).
However, photogrammetric cameras usually have no live feed capability and require
several hours of post-processing before they can be exploited.
The requirement is to provide a detailed record of the spill, vertically if possible, at an
altitude of less than 300m, along with a record of any vessel acting as source for the
spill. Depending on the flying height, digital cameras can collect imagery with a pixel
resolution on the ground ranging from a 5 to 50 cm, which provides a high level of
detail.
Figure 30. Left: Sony NEX-7 with 24.3 megapixels, deployed with the C-Astral
Bramor, an MUAV. Right: Nikon D-800, with 36.3 megapixels, available with the
manned or unmanned Diamond DA42 MPP [18].
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Sensor constraints
Lighting
Atmosphere
Surface wind 2-14 m/s
(ideally 3-10)
Sea state < 2m
Vegetation obscuration
Ice cover < 30%
No restrictions on
operation; handheld
Daylight,
Clear: little or
or mounted; use of
except with
no cloud or fog
operator. Some
IR
(use higher
sensors have limited
ISO)
operational life.
Readily available on many manned, and nearly all unmanned, platforms.
Onshore
Ice
Platform
Table 8. Restrictions on the use of aerial photography.
Availability
Visible sensors are offered by nearly all UASs and many manned platforms and so are
broadly available. They are integrated with many MUAVs such as the C-Astral Bramor
and the Prioria Robotics Maveric [18]. Otherwise, on other platforms they are readily
integrated or, in the case of manned platforms, deployed with an observer. All major
camera manufacturers provide models that meet many of the specifications identified
above.
Challenges
The challenges are similar to those from human observers.
Offshore
Onshore
Ice
False alarms
Operation
Analysis
Algal bloom, seaweed,
wind shadow, biogenic
oil, kelp beds, fish sperm,
cloud shadow
Numerous (e.g. shadow,
man-made materials, still
water, etc.)
Young ice types
Offshore false alarms
Hand-held
models
are
dependent on the skill of the
operator; on UAS, the device can
be remotely controlled and is
more sensitive to the platform
control in terms of performance
(e.g. stability);
In general, the
analysis
is
visual; in some
cases, raw data
can be provided
for
digital
analysis
if
required.
Compatibility
with CoP
Data positioning using GPS link.
Table 9. Challenges for the deployment of aerial photography.
Opportunities and Emerging Capabilities
Light field cameras have possibilities to extend the diurnal sampling range of the
sensors and to support flexible post-shot processing to focus to the spill (called
plenoptic processing). Cameras separately record the colour, intensity and
vector direction of all the light rays reflected towards them. It is then possible to
manipulate the image after the photo has been taken via an algorithm that
operates on all the data, so that the user can choose between having the
foreground, middle, or background subjects in focus, or they can select all three
together. Light field technology also allows pictures to be taken in lower light
(because all of the light is used), shutter lag is greatly reduced (because the
camera doesn't have to focus), and both 2D and 3D images can be obtained from
the same shot.
There are also developments taking place in terms of using robotic mounts to
generate impressive "sweep-panorama" imaging at high resolution.
Finally, video glasses from companies such as Google may become useful for oil
spill observers, depending on the performance and are worth monitoring.
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9.3. Multispectral Optical and Thermal Sensors
Overview
Multispectral sensors generate images of the surface at several discrete optical
wavelengths (typically 3 to 7, sometimes more). They are not limited to the visible part
of the electromagnetic spectrum, and so often record at NIR and sometimes SWIR as
well. Thus, as well as generating “true colour” images, they are able to generate “false
colour” images. These sensors provide digital imagery in various spectral bands at
ground sampling distances that can vary between a few centimeters and 1 or 2 meters
(depending on the platform altitude and lenses used).
Some sensors are used for digital photogrammetry and collect stereoscopic imagery in
each of the spectral bands - usually visible (RGB) and near-infrared bands. This allows
us to develop digital elevation models and ortho-photography in coastal areas, which
can help in modelling and mapping applications. Typical ground sampling distances for
these cameras are 5-30cm, depending on the flying height and the focal length of the
lens used. This provides mapping scales ranging from 1:500 to 1:5000 (with appropriate
ground control).
The advantages of multispectral sensors are as follows:
They help to remove false alarms in cases where a larger number of spectral
bands are available (by identifying differences between oil spill and false alarm
signatures).
They extend the range of applicability of surveillance across environmental
conditions or valid measurement ranges (e.g. extending observations into dusk
in case of SWIR), or detecting thinner (<10 μm) and thicker oil.
They can often provide additional environmental information that supports
OSR, such as sea surface temperature from TIR.
Figure 31. Multispectral sensing
systems. Left: the Icaros IDM600
sensor (courtesy, Robert Carroll,
Icaros) and right: the Optimare
VIS line scanner (courtesy Nils
Robbe, Optimare).
Visible sensors record true colour imagery, but as in the case of aerial photography,
they are useful for recording oil spill identifications by observers and distributing this
information to relevant parties. They can also be used to support enhanced
quantification of basic oil spill parameters including location and extent.
UV sensors are sensitive to very thin sheens of oil (as little as 0.01μm in thickness,
though dependent on sea surface conditions) because of strong refractivity at these
frequencies. The contrast increases as oil thickness increases. Some UV sensors have a
bandwidth that may include violet (0.390-0.450 μm) and blue (0.450-0.480 μm) that
increases their sensitivity to solar induced fluorescence from crude oils, but reduces the
sensor's ability to detect very thin oil. There is some capability also to detect emulsified
oil.
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VIS-UV
Environment
Offshore
Surface wind 2-14
No restrictions on
m/s (ideally 3-10)
Clear: little or
operation; some
Daylight (UV
Sea state < 2m
no cloud or fog
self-calibrating
requires direct
Vegetation
(below the
systems, others
sunlight)
obscuration
sensor).
external
Ice cover < 30%
Installation on larger UAV or manned (fixed or rotary wing) platform; normally
but not always involving installation design (some are portable); connection to
aircraft GNSS/IMU, power source and suitable configuration.
Onshore
Ice
Platform
Sensor
constraints
Lighting
Atmosphere
Table 10. Restrictions on the use of VIS-UV multispectral systems.
Thermal IR (TIR) sensors are useful for detection of oil during day and night and for
classifying oil thickness >10μm. The ability of thermal sensors to detect oil depends on
its thickness, type, degree of emulsification and time of day, and will not be effective
during rough weather. Some sensors (such as the Itres TABI 1800 system) have high
spatial and thermal resolution (sub-meter / 0.05 deg Kelvin), allowing for the
determination of subtle variations in sea surface temperature that are related to surface
oil. As well, any materials on or at the surface of the water / land with a large enough
difference in emissivity will also be apparent even if they hold the same apparent
temperature. The system is designed for large-scale area coverages and can operate
day/night under clouds or clear skies. TIR sensors tend to be poor with oil-water
emulsion (as there is little temperature difference), although there are indications of
sensitivity to emulsions containing water content up to 60% ([26]). TIR sensors are also
useful for measuring sea surface temperature, mammal activity and search and rescue.
Thermal sensors are available as cooled (cryogenic) or un-cooled sensors. Cooled
sensors depend on the availability of liquid nitrogen which limits their operational life
to several hours ([10]); newer systems are based on gas expansion which gives them a
longer operational life, and un-cooled systems are becoming available in smaller models,
with easier maintenance and operation, [27]. Thermal sensors can be divided into nadir
(TIR sensors) sensors or forward-looking infrared (FLIR sensors). Detection is better
suited to the latter, while quantitative mapping is more appropriate for the former.
TIR
Offshore
Onshore
Ice
Platform
Environment
Sensor constraints
Lighting Atmosphere
Not rough seas; no
submerged oil
Clear: no fog or
Mammals, freshwater
No restrictions on
haze; typical
sources; outflows;
operation;
None
operating
upwelling
External calibration
range: -15°C to
Other heat sources
often advised
+40°C
Overlying snow and ice
absorbs thermal signal.
Installation on larger UAV or manned platform; normally but not always involving
installation design (some are portable); connection to aircraft GNSS/IMU, power
source and suitable configuration.
Table 11. Restrictions on the use of TIR systems.
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Figure 32. The Itres TABI-1800 thermal imaging systems and sample night-time
data (courtesy, Jason Howse, Itres).
UV-IR sensors are now standard tools for oil spill response, being used typically to
generate a thematic map of oil thickness categories. They combine the benefits of the UV
and TIR bands for detecting a wide range of oil thickness. The two sensors are normally
as follows:
Optical UV detector, in the range of 0.32 to 0.38 μm;
A TIR detector in the range of 8 to 12 μm.
Basic mapping of local characteristics of oil spills is normally carried out using UV-IR
sensors. These devices are bi-spectral cross-track scanning sensors that are capable of
mapping relative oil thickness within a swath of about 500 metres at a platform altitude
of 330m. In the thermal IR, oil spills can be detected if the oil layer thickness exceeds
approximately 10 μm, and in the near-UV the lower limit of detection is approximately
equal to 0.01 μm.
Figure 33. The UV-IR scanner concept, from [8] and the UV-IR line scanner from
Optimare (courtesy, Nils Robbe).
Availability
Systems are available in some aircraft, but these are generally for existing customers
and so would be available only on an opportunistic or otherwise collaborative basis. It is
necessary to purchase these systems, which may involve an installation design and then
supplemental type certificates (STCs) for flight operations (responsibility of client).
There are a wide range of commercial available sensors that are designed for general
surveillance or applications such as search and rescue or vessel tracking that have
applicability to OSR. The TABI-1800 broadband midwave IR, for example, is available
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from ITRES Research, in 0.5-3m pixels. Optimare have scanner systems available which
they offer as part mof their Medusa integrated system, and this includes VIS and IR/UV
sensors. The Icaros IDM 600 system includes VIS, NIR and TIR multispectral capabilities.
The TABi-1800 system has an internal IMU for rapid deployment.
Deployment times for sensors are generally driven by deployment times for platforms
with sensors already integrated: in general, a platform with dedicated installation
provisions would need to be available on site.
Challenges
Some multispectral sensors are able to generate information in real time from the data
(e.g. “hot spots” in TIR data from the TABI-1800), but in most cases value-added analysis
of the data needs to be carried out using post-flight data on the ground. This creates a
delay in the application of the data to OSR which can be significant. This includes the
analysis of multispectral information to resolve false alarms, as described below.
VIS-UV
Offshore
Onshore
Ice
False alarms
Operation
Analysis
Wind
slicks,
foam,
sunglint,
cloud
reflections,
biogenic
material.
Numerous (e.g. shadow,
man-made materials, still
water, etc.)
Young ice types
Offshore false alarms
Instrument operation is
not
particularly
demanding
(modest
training requirements),
but where sensor forms
part of an integrated
system, can be more
demanding.
Processing is carried out
either onboard the platform
and on the ground, or just
on the ground. High level
analysis of the data is
carried out post-flight.
Compatibility with CoP
Table 12. Challenges for the deployment of VIS-UV airborne sensing systems.
TIR
Offshore
Onshore
Ice
False alarms
Operation
Analysis
Kelp beds, boat wakes, river
outflows, upwelling.
Man-made thermal signatures,
geothermal sources.
Ice insulates underlying water;
therefore
complicates
the
thermal signal (leads can appear
as hot spots).
Some
training
required to operate
and interpret the
data. Where sensor
forms part of an
integrated
system,
additional
sensorspecific training can
be required.
Some
real
time
processing to detect
hot
spots,
but
otherwise processing
is carried out on the
ground.
Compatibility
CoP
with
Table 13. Challenges for the deployment of TIR airborne sensing systems.
Opportunities and Emerging Capabilities
Investigations are underway to explore the extent to which multispectral
sensors can be used to improve oil thickness estimates, for example by filtering
out signal at bands that are insensitive to oil thickness in terms of reflectivity
(i.e. above 0.45μm), using horizontal polarising filters, and restricting the
reflection to the Brewster angle (53°).
Detection of oil on sand is a promising application for UV-IR sensors (Optimar,
[28]).
Development of software to automate extraction of key information from multispectral data, has potential, in particular with regard to speeding up delivery of
operational information from the sensors.
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9.4. Microwave Radiometers
Overview
Microwave radiometers are very useful in being able to map oil thicknesses greater than
about 0.05mm. Airborne MWR Sensors are mounted to the lower side of the aircraft.
The parabolic scan antenna, protected by a dome-shaped cover, has a free field of view
in nadir direction. The scan mechanism provides a sinusoidal scan line on the ground.
The radiation collected by the antenna is fed through the horn into the receiver where it
is amplified and filtered, to extract the desired frequency.
While airborne MWR systems operate in principle between about 1 and 100 GHz, in
practice airborne systems tend to operate at particular frequencies including 18GHz, 36
GHZ and 89 GHz. These are complementary, and have differing spatial resolutions and
oil thickness sensitivities, ranging from sensitivity to relatively thin (~50 m) oil at
higher frequencies (89 GHz) to enhanced spatial resolution at lower frequencies (18
GHz).
Figure 34. The microwave radiometer
concept, from [8].
The OPTIMARE MWR measures the upwelling microwave emission of the sea surface at
three different microwave frequencies. Based on a radiative oil spill model the measured
brightness temperatures are used to calculate the oil spill thickness in the range
between 0.05 mm and 3 mm, with the output being maps of oil thickness. The oil volume
can then be calculated within the sensitivity range of the MWR (50 to 3000 μm
thickness).
Figure 35. The Optimare Microwave
Radiometer System.
Environment
Offshore
Onshore
Ice
Platform
Sensor
constraints
Lighting Atmosphere
Not rough seas
Training required
Many false alarms
to operate and
All
Presumably in ice<30%, but
interpret the data
investigation needed.
Require dedicated aircraft to accommodate antenna [6].
Some sensitivity
at higher
frequencies
(~89GHz)
Table 14. Restrictions on the use of microwave radiometry systems.
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Availability
Delivery time for the Optimare MWR is 10 months if it is not already in stock [28].
Challenges
In practice, there is complexity involved in using the micvrowave brightness
temperature to estimate oil thickness through the impact of absorption on upwelling
radiation. There are interference effects imposed on the upwelling radiation by the
interfaces between the oil and water and oil and air. Multiple scattering of the signal
between these two interfaces acts to set up a process of constructive or destructive
interference in the signal, creating an ambiguity in the thickness estimation.
Offshore
Onshore
Ice
False alarms
Operation
Analysis
Kelp beds, boat wakes, river
outflows, biogenic materials,
etc.
Many potential false alarms
Young ice types
Offshore false alarms
Costly
In some cases, the
processing is on the
ground. Needs a skilled,
trained a analyst.
Compatibility with CoP
Table 15. Challenges for the deployment of microwave radiometry systems.
Opportunities and Emerging Capabilities
Multi-frequency microwave radiometers have been proposed to remove ambiguity in
the oil thickness estimation imposed by interference effects from the oil-water and oilair interfaces. [29]. The use of polarimetric information has also been proposed for the
same purpose [30].
Figure 36. Interference fringes from
microwave radiometry over oil on
water ([8]). Brightness temperature of
oil given in absolute temperatures
(Kelvin scale) as a function of the oil
film thickness in millimetres, shown for
three frequencies in the microwave
range. The angle of incidence of the
radiometer field of view on the oil
surface is 41° (5 GHz), 54° (17 GHz),
and 50° (34 GHz). Use of data from the
3 frequencies can in principle be used
to resolve oil thickness [8].
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9.5. Hyperspectral sensors
Overview
Some imaging sensors are able to sample a very large number (>100) of spectral
wavelengths across the optical part of the electro-magnetic spectrum, typically
extending well into the IR band. These hyperspectral imaging sensors have typical
surface resolutions of 0.5-12m, depending on altitude. The advantage of these sensors is
that the spectral resolution is high enough to enable the unique signatures of particular
compounds to be matched to reference library signatures, leading to the possibility of
using hyperspectral sensors not only to detect oil, but to characterise the oil in terms of
type and condition. These sensors can also be used for oil spills in coastal environments
and on land, where their ability to extract unique spectral signatures is useful in
compensating for the more complex backgrounds against which oil needs to be detected.
In general, hyperspectral sensors can be used with all types of oil, except very light oils3.
Observations in the SWIR are useful in order to resolve hydrocarbons from other
organic matter identified in the VNIR. Spectral signatures can be compared to library
signatures for the identification of unique compounds.
Figure 37. The SpecTIR ProSpec TIR VIS system and image from the Deepwater
Horizon oil spill (courtesy, Justin Janaskie, SpecTIR).
Hyperspectral sensors can potentially cover all three diagnostic absorption features of
hydrocarbons in the IR, with the depth of the absorption features being used to estimate
the thickness on an oil spill although this can be a relative rather than absolute measure
(Janaskie, [17]). Hyperspectral data from the SWIR can be used for thicker oil thickness
(up to a few mm), while thinner oil thickness can be estimated using VNIR (to a few tens
of μm), Lennon [9]. There are some indications that hyperspectral data can be used to
assess oil type in terms of heavy, medium and light. More detailed information on ice
type and condition is the subject of research.
Hyperspectral
Offshore
Onshore
Ice
Platform
Environment
Sensor
constraints
Sunglint; high sea states (white
Significant
caps); not submerged oil
training
Helpful if there is soil to
required
absorb and retain
(can last
hydrocarbons
several
Ice and snow covering oil will
weeks)
reduce the detection
Manned aircraft and UAVs (VTOLs in particular)
Lighting
Atmosphere
High solar
radiation is
required; in some
cases 2 hours of
local noon (and
seasonally
dependent too)
Cloud, fog,
dust and rain
all degrade
the
performance
Table 16. Restrictions on the use of hyperspectral systems.
3
Classifications used here are based on API gravity as follows: light> 31.1° (<870 kg/m3), medium
22.3° to 31.1° (870 to 920 kg/m3); heavy <22.3° (>920 kg/m3).
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Availability
There are several hyperspectral systems available on the market.
The SpecTIR ProSpec TIR VIS system utilizes the Specim AisaEAGLE (VNIR from
0.4 – 0.970 μm) and AisaHAWK (the SWIR range from 0.970 to 2.5 μm) sensor
heads, with all other components being customized and/or proprietary to
SpecTIR. Galileo Group also provide the AisaEAGLE system from various fixed
wing aircraft.
The Hyspex VNIR 1600 and SWIR 320 systems are offered by both Fugro-LADS
and SAS Actimar. These are hyperspectral sensors that combine 160 channels in
the VNIR with 256 from the SWIR with high spatial resolution.
Headwall photonics Micro-Hyperspec systems are designed as very small,
lightweight, robust hyperspectral imaging spectrometers for UAS and small
manned platforms operating in harsh environments. The Micro-Hyperspec
imaging spectrometer is available in two models: the Micro-Hyperspec VNIR (0.4
to 1 μm) and NIR (0.9-1.7 μm).
AVIRIS is a NASA system providing calibrated images of upwelling spectral
radiance in 224 contiguous spectral bands with wavelengths from 0.4 to 2.5 μm.
Although not available commercially, AVIRIS nonetheless extensively mapped
the region affected by the Gulf of Mexico oil spill during 456 flights conducted
between May 6 and October 4, 2010, at the request of NOAA.
Hymap system, from Hyvista, available for deployment within 48-72 hours in
Australia where the supplier is based. Products are available within 1-2 hours of
landing, and the system has been used successful for oil seep mapping [31].
Other providers include Specim, Resonon, Cubert Gmbh and Surface Optics, the latter
providing hyperspectral sensors suitable for UAVs. Platforms which have hyperspectral
sensors installed include Cessna (multiple variants), Piper Seneca, Beechcraft Queen Air,
Aztec, Navajo, Twin Otter (DHC-6), King Air 90, Convair 240, DC-3, Partenavia (P-68),
DA42, C-130, VTOL UAV Octocopter and others.
Figure 38. Headwall Photonics
micro-Hyperspec system deployed on
a custom UAV including GPS, optional
LiDAR, and controlling software,
courtesy Christopher Van Veen,
Headwall Photonics, Inc.
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Deployment times were quoted in the survey [28] as being a minimum of 24 hours, but
in most cases >96 hours. This assumes that a platform is provided with the sensor
already integrated, with necessary approvals in place for deployment and a contractual
vehicle to enable short notice deployment of the platform and sensor (e.g. a retainer).
The deployment time of 24 hours is applicable in the case of platform and sensor being
locally available (with necessary approvals) with the ultimate limit being personnel
transport if platform is on standby.
In practice, to achieve OSR deployment times, it would be necessary to source and install
a hyperspectral sensor on a platform in advance. The typical requirement would be a
mounting Plate, Sensor (IMU), Data Acquisition Computer and GNSS Feed. Sensor sizes
reported in the survey range are a few tens of cm in each dimension, with 1 KW
maximum power. The range of weights from the survey is between 12 and 50kg [28].
Challenges
Some key challenges for the use of hyperspectral sensors are identified in Table 17.
False alarms
Operations
Analysis
False alarms in
principle
removed by use
of
sufficient
spectral
information at
high
spectral
resolution. More
potential false
alarms on land
than elsewhere.
Specialist skills required for
sensor.
Manufacturer typically provides custom
software for data acquisition and
processing (e.g. Hyspex, Spectir).
May not detect
light oils
Significant data acquisition
(20
Mb/s
for
Spectir
hyperspectral sensor). Near
real time data delivery not
standard; some on-board
processing
required
to
reduce
data
volumes;
satellite link for data volumes
could be extremely costly.
Calibration
can
require
involvement
of
the
manufacturer.
Significant specialist processing, including
atmospheric correction.
Near real time spectral signatures are
available on-board the aircraft, but
generally processing is carried out postflight. Can be time-consuming and delay
results until out of scope of OSR.
Compatibility with CoP
Table 17. Challenges for the deployment of hyperspectral systems.
Critical constraints are as follows:
In many cases, the availability of the sensor is limited by solar illumination
constraints at the target location. This would particularly apply to the North Sea,
West Greenland and North Alaska, for example, in effect making the sensor
unavailable for these locations for some part of each year.
The application of the sensor also requires skilled personnel. Sensor operator
training is typically a few weeks through classroom and on-the-job training. In
some cases, it is possible to provide skilled operators as part of a response effort
(e.g. SpecTIR).
The high data rates combined with complex processing mean that hyperspectral
sensors have historically had limited value for OSR. The cost and practical side of
using these data has to be addressed before the sensors can be used for OSR in a
non-experimental manner.
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Opportunities and Emerging Capabilities
There is significant research and development being carried out on hyperspectral
sensors, with key opportunities and evolving capabilities in the following areas:
Research into techniques that exploit spectral libraries to optimise processing of
hyperspectral data are likely to result in the basis for operational, near real time
processing techniques. To be practical, these will almost certainly need to be
implemented on board the aircraft to minimise delays and to reduce data
downloads.
Use of thermal and hyperpectral information in combination may enhance oil
thickness mapping.
Hyperspectral imagers will continue to be developed for UAVs, as already
demonstrated by Hyspex, Cubert Gmbh and Surface Optics.
Hyperspectral has potential value for OSR over land.
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9.6. Laser
Overview
Light Detection and Ranging (Laser, or “Light Amplification by Stimulated Emission of
Radiation”) sensors are widely used for topographic and bathymetric mapping
applications, but some have been adapted for OSR. They are designed to exploit very
short optical wavelengths to detect not only surface materials, but also atmospheric
constituents, which can be indicative of oil spills. In principle, lidars can also detect
submerged oil within the penetration depth of the radiation. Over land, lidars can be
used to generate digital elevation models, which can support OSR. The use of lidars in
near real time, however, has yet to be fully proven. Laser fluorometers (LFS) use a
more sophisticated method of hydrocarbon detection involving the transmission of a UV
signal towards the surface and recording of the return signal in the visible range. The
analysis is typically carried out on the aircraft. These are the only sensors that can
discriminate between oil types. Most sensors operate in the 0.3 to 0.355μm range.
Figure 39. Illustration of the
laser measurement concept
[8].
LFS systems can also be used to classify oil type. In the case of the Optimare LFS, the
typical classification categories might include various types of crude and levels of oil
refinement (as well as sea water and algae, hence providing a clear identification of
pollution compared to potential false alarms detected using other techniques). As a byproduct, lidar systems can also potentially provide other hydrographic observations
such as turbidity.
Laser Raman spectroscopic systems can also be used to quantify the suppression of
Raman scattering signal by oil to estimate the oil thickness for oils between 0.5 and
10μm in thickness ([32]). The conversion to thickness depends on knowledge of the
absorption coefficient of the oil at the relevant frequencies, and this depends on the type
of oil. These systems can also be used to detect compounds indicative of oil such as
ethane/methane.
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Availability
There are a range of laser systems available, for example the Optech ALTM Orion C300
from Opten, the Trimble AX60 from BSF Swiss Photo and the Riegl LMS Q680i. There are
fewer LFS systems, as they are costly to operate, require a dedicated aircraft with open
belly hatch and depressurized cabin, as well as expertise to operate. LFS are not
designed as portable sensors, so there is a necessity to either arrange access to an
existing platform with the sensor already integrated, or to order a sensor for integration
into a platform.
Figure 40.
fluorosensor
Optimare).
The Optimare laser
(courtesy, Nils Robbe,
The Optimare LFS is a nadir-looking non-scanning laser that includes both LFS and
Raman spectroscopic capabilities. The Optimare Imaging Airborne Laser Fluorosensor
System (IALFS) is a scanning system that has especially been designed to meet the
requirements of different tasks of maritime surveillance. The Laser Fluorosensor Light
(LFS Light) is the lightweight relative of the IALFS. The LFS Light is a nadir-looking (nonscanning) fluorescence lidar. The instrument is compact and reliable and has especially
been designed for space-saving installation. The LFS Light has been deployed on EADSCASA CN-235 aircraft and, in modified form, on a helicopter of type BO 105 [28].
The Optimare Time-Resolved LFS (TRFLS) system has range resolved observation in
nadir (non-scanning) configuration, which is additionally useful, supporting
fluorescence decay time analysis and information on the vertical distribution of
fluorophores and attenuating substances in the water column (most LFS systems
integrate the signal over time).
SSC also offer an LFS system as part of their MSS 6000 suite of maritime surveillance
sensors.
Environment
Offshore
Onshore
Ice
Platform
Rough ocean
surface can reduce
the fluorescent
backscatter.
Sensor
constraints
Sensor is large and
not readily
portable;
Limited coverage
(narrow beam&
low altitude)
Lighting
Atmosphere
Any
LFS systems are
sensitive to moisture
content and so are
unable to be used
effectively in conditions
of fog and other
inclement weather.
Limited penetrating
capability into oil
under snow/ice
Requires dedicated aircraft with open belly hatch and depressurised cabin.
Lidars too too heavy for many UAVs and too high power consumption. Low
altitude may be required.
Table 18. Restrictions on the use of laser fluorometer systems.
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Challenges
Power limitations mean that LFS systems generally need to be operated below about
500m altitude. More powerful lasers will be able to operate at higher altitudes. Coverage
is also limited to relatively narrow swaths, so the technology needs to be deployed
efficiently. The number of pulses is also limited by power consumption, so resolution on
the ground tends to be fairly coarse. An LFS having consuming 5 kW of power can
feasibly consume 50% of the total electric power available aboard the aircraft.
Offshore
Onshore
Ice
False alarms
Operations
Analysis
Fewer false alarms
because than many
other sensors.
Sensitive to strong
ocean backscatter.
Numerous.
Young ice types
Offshore false alarms
High cost of
maintenance;
Skill
level
required
for
operation.
Principle
component
analysis
to
extract
compounds; oil absorbance
is needed for thickness.
Compatibility with CoP
Table 19. Challenges for the deployment of laser fluorometer systems.
Opportunities and Emerging Capabilities
Differential Absorption Lidar (DIAL) is an active sensor that detects the
spectrum of surface liquids or evolving gasses. The sensor projects laser light at
a wavelength absorbed by specific hydrocarbons and a second laser at another
wavelength that is not absorbed. The differential comparison of the signal
indicates the presence of species of interest (Ball Aerospace, [28]). This system
is under development and planned for availability in 2015.
Tunable Diode Laser Systems. This sensor scans the absorption frequencies
associated with methane and ethane (and in principle, other frequencies) and
has been suggested as a suitable technique for oil spill detection in ice [10] .
Laser acoustic systems. These are experimental and have been developed by a
consortium including Imperial Oil, Environment Canada, and the US Minerals
Management Service. A test unit has been flown and the technique appears to
have promise for the estimation of oil thickness in open water or low
concentration sea ice [10].
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9.7. Radar
Overview
Imaging radar can be deployed to detect oil spills some distance away, through off-nadir
imaging at significant angles. They are therefore useful as a wide coverage, initial
response airborne sensor. Imaging radars are able to observe the surface during day and
night, and during poor weather conditions. As such, its operation is limited only by
conditions that might restrict deployment of the platform (e.g. very poor weather)
rather than to operate the sensor.
Side-looking airborne radar (SLAR) uses a relatively long antenna to obtain good spatial
resolution in the direction of movement of the platform. Synthetic aperture radar (SAR)
achieves high spatial resolution by using the motion of the aircraft to synthesize a large
antenna in the direction of travel, thus enabling the use of smaller antennas. Thus, it
combines the ability to observe the surface during day and night, and during poor
weather conditions, with the ability to resolve the surface in great detail. VV is generally
considered the best polarisation, and the most experience is with C band.
Figure 41. Geometry of SLAR operation
and resolved surface area. The SLAR
antenna (shown in red colour) with length
“l”; is mounted to the lower side of the
aircraft at flight altitude H. In the case of a
SAR, the forward motion of the aircraft is
used to synthesize a long antenna in the
direction of motion, enabling the spatial
resolution in the direction of motion to be
improved significantly [8].
Availability
There are a wide range of commercial, military and R&D airborne SAR and SLAR
systems available globally, though not all are designed or used for OSR applications. The
majority operate from fixed-wing manned aircraft and are not portable from one
platform to another (e.g. Fugro's GeoSAR system; Intermap's Star 3i). Some are installed
in the larger MALE UAVs, though these are still restricted to the defense/military
domain. Elta Systems provides a multi-mode X band imaging radar (ELM-2022) which is
suitable for detecting oil spills at sea.
Environment
Offshore
Onshore
Ice
Platform
Sensor
constraints
Lighting
Atmosphere
Surface wind 2-14 m/s (ideally
SAR produces
3-10) Sea state 0.2-1m
speckle, which
Any (except
Vegetation obscuration, except
can complicate
Any
very heavy
perhaps at lower frequencies,
analysis if close to
precipitation)
and limitations in steep terrain.
spatial resolution
of the sensor
Ice cover < 30%
Platforms can operate at high altitude, and so produce better coverage; challenge
to obtain data in spatially restricted areas (coastal, etc.)
Table 20. Restrictions on the use of imaging radar systems.
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Challenges
Imaging radar systems do not discriminate between different thicknesses of oil, and
provide very little information on the oil itself, at least from single polarisation signals.
They are also subject to many potential false alarms in all environments.
Imaging radar is extremely difficult to interpret, requiring significant expertise in all
environments. Given challenges in relation to false alarms, it is also important to have
ancillary information available that can help with identifying false alarms.
Imaging radar involves significant image processing and data quantities. Given this and
the challenges identified above, it can be difficult to use SAR effectively in near real time
without significant advance planning.
Offshore
Onshore
Ice
False alarms
Operations
Wind
shadow,
seaweed,
vessel
wakes, etc.
Numerous
Young ice types
Offshore false alarms
Requires
analyst;
Sensors
available.
Analysis
skilled
readily
Required
ancillary
information to reduce
false alarms.
Compatibility
CoP
with
Table 21. Challenges for the deployment of imaging radar systems.
Opportunities and Emerging Capabilities
Exploitation of polarimetric information from radar. Using data from the
Deepwater Horizon incident, it was shown that if the full polarisation matrix is
available, then polarimetric parameters such as the major eigenvalue of the
coherency matrix ([30]), can be used to enhance detection of oil in water, and
perhaps provide other information related to oil viscosity and concentration.
Very low frequency ground penetrating radars operate on the principle that
radiation at <1 GHz is effective at penetrating snow and ice, though this depends
on the temperature of the ice, its salinity content, its surface reflectivity and
other conditions. A controlled field experiment was able to use GPR to detect oil
between sea ice and overlying snow, with the oil being 2cm thick, the reflection
being reduced by the presence of the oil. There is potential for significant
improvements in GPR capabilities based on radar technologies, including
frequency modulated continuous wave systems, which can transmit variable
frequencies tailored to ice and oil target conditions.
UAV-based SAR sensors are now a reality and have been used for detection of
oil in coastal environments (see [33]). Elta Systems are developing a lightweight
SAR (ELM-2054) suitable for unmanned TUAVs, VTOLs or larger UAVs, and
manned aircraft based on low weight (12 Kg), modest power consumption
(250W at 28Vdc) and small volume.
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9.8. Integrated Airborne Sensing Systems
Overview
A number of suppliers are now offering integrated airborne sensing systems, to provide
end users with the following:
The ability to use multiple sensors together to identify false alarms because
false alarms are not normally present across the electro-magnetic spectrum, and
to provide a more complete set of oil spill and ancillary observations (no one
airborne sensor provides all the oil spill information that is required);
To provide the ability to extend the range of applicability of surveillance
diurnally or across environmental conditions or valid measurement ranges (e.g.
extending observations into night, or detecting a wider range of thicknesses of
oil).
To offer integrated communications across sensors, for example via satcoms;
To enable a single ground station to be used for processing and distribution;
To support the potential for multiple sensor data fusion to enhance the quality
and range of oil spill products from airborne sensors.
Availability
Two particular integrated systems are available. Medusa from Optimar integrates
multiple remote sensors and mission system components into a single network-based
data acquisition and processing infrastructure. The sensors includes SLAR, Laser
fluorometer, UV-IR scanner, VIS line scanner and microwave radiometer. Medusa
supports acquisition, real-time display and post-flight processing of data from the
various sensors, the latter including automated image analysis, pollution classification
and GIS export.
The MSS 6000 Airborne Maritime Surveillance System from the Swedish Space
Corporation has comparable aims, integrateing data from SLAR, UV-IR scanner, cameras,
AIS and potentially FLIR and microwave radiometer. The infrastructure includes a
mission management framework based on GIS (Geographical Information System)
technology, and the available information is presented against a backdrop of a digital
nautical chart. The information from on board sensors and external inputs is presented
live to the operator and also recorded digitally for later analysis.
Environment
Sensor
constraints
Lighting
Atmosphere
Mixture of sensors
All
environments enables most
Platform
Significant
training required
Some sensors
Daylight only and
environments to be to operate the
impacted by
day and night
sampled with at
integrated system
atmosphere,
sensors
least some success
involving multiple
others not.
by the sensor suite. sensors
Deployment of fully integrated system requires significant size UAV and/or
manned platform.
Table 22. Restrictions on the use of integrated airborne sensor systems.
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Challenges
Challenges for the use of integrated sensors packages are shown in Table 23. The use of
data from multiple sensors is clearly an advantage for oil spill response, but has
associated challenges in terms of combining the data effectively in near real time, so the
integration implies significantly more than providing access to different sensors on a
single platform. Effective integration requires skill to operate the sensor package, a
suitable custom software environment, communications and effective physical
integration (e.g. shared components where appropriate). In addition, it is important that
the configurations of the sensors are suitable for oil spill response and there should be
knowledge about how best exploit and present the data in combination, so that the
potential of the multiple observations is fully realised.
All environments
False alarms
Operations
Analysis
Many fewer false
alarms because of
multiple
sensor
observations
Full implementation
can be very costly.
Effective exploitation
of integrated sensor
systems
requires
significant post-flight
processing, which can
delay
information
being provided to the
CoP.
Complexity
in
planning
optimum
sensor suite and data
acquisition for OSR
(dependent
on
environment
and
operational factors).
Table 23. Challenges for the deployment of integrated airborne sensor systems.
Opportunities and Emerging Capabilities
There is a recognition that the use of multiple sensors provides a more complete and
reliable surveillance capability for oil spills, and integration of multiple sensors will be
supported by further miniaturisation. If the industry is able to provide clear guidance on
what combination of observations is required, then this will provide strong impetus for
suppliers to support this capability.
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Some General Challenges for Airborne Remote Sensing
Airborne remote sensing has particular challenges in the areas of data positioning and
environmental conditions for effective oil spill surveillance, and these are reviewed
briefly below.
10.1. Positioning of Remote Sensing Imagery
The correct positioning of remotely sensed data is critical to its effective use, and with
high manoeuvrable airborne platforms this can present challenges ([34]). The
positioning of the sensor can be obtained from GNSS, which depends on a receiver either
built-in to the sensor or physically linked (with appropriate calibration for the sensor
mounting). It is often a requirement for the sensor to be positioned to a centimetric level
of accuracy rather than a metre level of accuracy, and this can be achieved using real
time kinematic GNSS techniques, which involves analysis of the phase of the GNSS
carrier wave rather than more conventional GNSS signal processing. Once the
positioning of the sensor is achieved sufficiently accurately, then data can be geo-tagged
with this information in the metadata.
The positioning of the sensor needs to be augmented by information on the orientation
of the sensor in order to identify the location of the data on the Earth’s surface (Figure
42).
Figure
42.
Measurements required
to support effective
positioning of remotely
sensed
data.
These
include the position of the
sensor (X0, Y0, Z) and the
orientation of the sensor
(from the pitch, roll and
yaw of the sensor).
The orientation of the sensor can be obtained from an Inertial Measurement Unit (IMU),
which includes an accelerometer and a gyroscope (and when combined with electronics
and computer, is referred to as an Inertial Navigation System, or INS). The
accelerometer provides information on acceleration due to gravity (static component)
and acceleration due to motion of the platform (dynamic component). The gyroscope
provides information on angular velocity. Together, data from these two instruments
can be used to calculate the orientation of the sensor. (The IMU may also include a
magnetometer providing orientation with respect to magnetic north). The INS may be
able to provide updates on the 3D orientation of the sensor at a rate of 100 hz or more.
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The IMU/INS is also useful for cases where there are intermittent dropouts of the GNSS
signal, for example where topography obscures the GNSS signal. In this case, the INS
may be used to extrapolate the positioning of the sensor as well as the orientation,
although the accuracy of this degrades as a function of the length of the dropout of the
GNSS signal(s).
Once the positioning and orientation of the sensor is established to sufficient accuracy
and precision, the configuration of the sensor (e.g. angular view from antenna boresight) can be used to define the field of view on the Earth’s surface. Although for many
purposes, the positioning of the remotely sensed data may at this point be adequate,
there are several cases where post-processing, carried out on data after being
transmitted to the base, may be required, as follows:
If the positioning of the remotely sensed imagery is insufficient for the
application, for example as a result of a lack of real time kinematic GNSS, then
processing of data may need to be carried out at the base, quite probably
including the use of ground control points where available (accurately and
precisely positioned fixed features on the ground).
The atmosphere can create distortions in the signal that translate to positioning
errors (e.g. from refraction).
In areas of significant topography, a digital elevation model will be required to
map the remote sensed data to the actual surface.
It is important to ensure that the positioning of remotely sensed data is adequate for oil
spill response. In offshore areas, positioning errors may not be noticed until too late.
Therefore, full use should be made of real time kinematic GNSS, integrated with INS with
appropriate rapid and automated post-processing for precise positioning where
required and all relevant information should be available via the metadata of the
imagery.
10.2. Radiometric Calibration of Remotely Sensing Data
Calibration is required to convert data into useful correct absolute measurements. With
more complex and/or experimental sensors, it can be a challenge to be able to fully
calibrate the data in a timely fashion, particularly in response to emergency requests for
data. Data that has not been adequately calibrated can result in the data being biased
towards low or high values, and the scale may vary across the measurement range. This
then creates difficulties in interpretation or algorithmic analysis. A particular danger is
that an oil spill product may be produced, but contain systematic errors that are not
recognised by the responder. It is therefore extremely important that remotely sensed
data is fully calibrated, or failing this, a lack of calibration and its potential impact on any
interpretation is clearly identified.
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10.3. Environmental Considerations
The effectiveness of many of the sensors described in previous sections depends on
environmental conditions. To illustrate some of this variability, key conditions are
described here in relation to the eight sample areas identified in Section 6.
The availability of effective SAR and SLAR data for offshore OSR depends not on cloud or
daylight, but to first order on the presence of open water and surface wind speeds that
are, ideally, between 3 and 10 m/s (to afford backscatter contrast between open water
and the spill), or at least between 2 and 14 m/s (Figure 43). Optical imaging is also
impacted by surface wind speed. For oil spill detection using VIS and NIR, the optimum
surface wind speed is < 10m/s, or at least < 14 m/s.
Figure 43. Surface winds statistics for the eight sample areas [35].
Open water is reduced by the presence of sea ice, which above an area concentration of
about 30%, tends to dampen the oil-water contrast and to directly mask the oil
signature. Ice cover is a challenge in some areas. Note that for both Harrison Bay, Alaska,
and West Greenland, ice can occur in any month of the year (Figure 44), compromising
oil spill detection and monitoring (some types of young ice can appear similar to oil
spills in SAR imagery).
Figure 44. Sea ice statistics for the sample areas affected by ice [36].
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It is clear from that daylight impacts are optical data are significant, even in summer. In
many of the eight sample areas, one of the two daily sampling periods are lost due to
lack of natural light. Other areas, such as Alaska, are able to be optically imaged at any
time of day during mid-summer, although conversely Alaska has complete darkness
during mid-winter (Figure 45). Unlike VIS and NIR bands, SWIR is able to image during
dawn and dusk, and TIR can image during day and night, so there is value to checking
whether TIR in particular is available for night-time imaging.
Figure 45. Maximum daily duration of darkness for the eight sample areas.
The potential of optical data is affected by cloud, and very few regions of the Earth do
not suffer from significant cloud cover at least during part of the year. Infrared
frequencies are able to see through some minor cloud (e.g. SWIR can image through
haze and fog), but thick cloud is opaque to all optical frequencies, and so limits the
effective optical revisit times substantially in many areas. Cloud statistics exist which
can be used, in principle, to estimate the potential revisit capability for optical sensors in
particular areas. Many airborne sensors have the ability to fly underneath cloud cover,
but this option is not always available, depending on the type of platform and type of
cloud or fog.
Figure 46. Global mean cloud cover fraction from 28 years of AVHRR [37].
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Figure 47. Cloud cover statistics for the eight sample areas.
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Findings
11.1. General
The complexities of accessing airborne remote sensing for oil spill response are
substantial, but would be mitigated to significant degree by good preparation
and up-front investment in access to capabilities.
A regional approach to planning and operations, through regional JIPs, would be
most efficient for airborne remote sensing, given the regional nature of
environmental conditions, regulatory environments and infrastructure and
logistics support.
The number of platform and sensor providers is very large, and the number
identified through this report, particularly platform providers, is limited. At the
very least, for each potential oil spill response region, there should be a directory
of local providers (e.g. for platforms), but it would also be useful to have
available a regularly updated directory of international suppliers.
Exercises would help considerably in supporting the development of effective
airborne surveillance capabilities for oil spill response [26], through the
following benefits:
o
For helping to test the technical capabilities of new sensors
o
For helping to test the operational capabilities of sensors and platforms.
Many sensors and platforms are experimental;
o
For training of personnel in the effective deployment, use and
exploitation of sensors and platforms for OSR;
o
To generally identify issues that have not been recognised through
“paper” studies or past oil spill events, for example in relation to local
logistics.
A technology road map would be useful to identify critical technologies that the
industry needs for effective oil spill response.
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11.2. Platforms
Rapid deployment of platforms (within 24 hours) is often not possible, reflecting
import/export issues, certification, flight permissions and logistical and
contractual constraints. Therefore, effective oil spill response based on
opportunistic availability of platforms (with sensors) is not viable.
Access to platforms for OSR needs to be planned in advance, in terms of
committed availability from suppliers, regulatory permissions, etc. The goal
should be for availability within 24 hours, but if this is not possible, it is
important to plan for committed availability within 72 hours.
Given that oil spill surveillance using opportunistically available platforms and
sensors is not viable, there is a need to build surveillance capabilities around
local jurisdictions and physical environments for OSR in which necessary
licensing, permits and contractual arrangements have been put in place for
effective and immediate OSR. There is, and will be, very different regulatory
environments for use of airborne platforms and sensors depending on location,
particularly as UAS become integrated into some, but not all, national airspaces
in the next 2-5 years. Therefore, this will be driven by local regulatory and
physical environments rather than global plans, and articulated through Field
Development and Emergency Response Plans. Listings of suppliers based in, or
close to, local oil spill jurisdictions could be an important component of this.
It is important to connect platform availability for OSR with sensor availabilities
and to be able to establish which portable sensors can be hosted on available
platforms and to ensure that platforms that are available for local OSR are
equipped, or available to be equipped, with a suitable sensor suite for OSR either
individually or in combination.
UAS are clearly going to be important platforms for OSR in the future, with the
market likely to expand rapidly in the next 5 years. There are a number of
challenges with regard to their effective incorporation into OSR, which the
industry should actively address. These include issues related to OSR
requirements for UAS (which drives their design); integration of UAS into
airspace for jurisdictions of relevance to OSR; allocation of communications
frequencies and development of sense and avoid technologies. The industry
could play a role in supporting or lobbying for developments in these areas, but
at the same time be ready to build into plans UAS technologies (which may be
restricted classes of UAS) as they become tried, tested and commercially
available.
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11.3. Sensors
Standard sensor packages (and frames) on standby for deployment are
potentially very useful. However, the necessary approvals will be needed in
advance (for example, export and import-compliance, and approvals for sensor
mounts). This would be particularly useful for more advanced sensors which
may not be able to be manufactured in significant numbers and widely deployed,
perhaps for reason of cost. If portable sensors are to be useful, the portability
will need to be planned very carefully in advance in relation to both platforms
(aerostats, manned and unmanned platforms) and sensors.
Important research topics include the following:
o
Spectroscopy, linking oil and gas company laboratory research on
fingerprinting to broader academic research and link to practical
experiments, with a view towards effective use of precise spectral
information, design of optimised sensors and processing of data.
o
Full polarisation information from imaging radar, and its potential for
providing information beyond oil detection (e.g. oil condition, etc.).
o
Assessment of which combinations of sensors may be deployed in
combination for effective OSR
o
Effective and practical fusion and visualisation of information from
multiple sensors.
The effective use of airborne remote sensing requires training of personnel,
particularly as some new sensors are complex to analyse and interpret and as it
becomes increasingly recognised that observations from multiple sensors are
required for oil spill surveillance.
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11.4. Processing and Delivery
Information is ideally needed in near real time (<1 hour) to be most useful.
Experience from Deepwater Horizon and elsewhere has demonstrated that
processing of data can delay ingestion of the information into the CoP, with the
result that its value is at best severely reduced and at worst a distraction from
more valuable data. The drive to develop new sensors and data analysis
techniques should not obscure the strong requirement to enable information to
be available rapidly for responders.
In order to achieve rapid processing and delivery times, the following issues are
important:
o
On-platform processing of data should be considered to reduce data
volumes for remote delivery from airborne platforms to decisionmakers. Downloading raw data from aircraft is not generally feasible for
many OSR sensors. Some create particularly large quantities of data (e.g.
hyperspectral sensors).
o
The airborne platform external communications capabilities are very
important to the effective use or remote sensing. This is more of a
challenge in some areas than others (the Arctic for example).
It will be very important for airborne surveillance to be compatible with the CoP
in terms of products. There may be implications for products from some sensors
in terms of metadata, time stamping, positioning accuracy, codes (e.g. [5]),
symbology, units, naming, delivery mechanisms and formats (e.g. [3]). This will
need to be communicated to airborne sensor suppliers.
Remote sending creates large data sets, which require proper management not
only for OSR itself, but for post-event analysis [38], [39].
An Assessment of Surface Surveillance Capabilities for Oil Spill Response using Airborne Remote Sensing
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12.
73
11th May 2015
Conclusions
Airborne remote sensing from manned platforms is now an accepted and integral
component of effective OSR with the ability to host a range of sensors. However, it is
clearly not viable to base OSR on opportunistic availability of platforms and sensors and
there is a pressing need to ensure that, at a regional level, there is effective preparation
and planning for OSR (i.e. through Field Development and Emergency Response Plans).
This involves identifying the appropriate platforms and sensors and operating
conditions for each region, dealing with the associated availability of platforms and
sensors and addressing regulatory, contractual, logistics and training issues in advance.
Traditionally, airborne remote sensing has been carried out from manned aircraft using
trained observers and supporting sensors. However, remote sensing technology,
whether it is sensors or UAS, is developing at a fast pace. Lasers and digital cameras, for
example, can nowadays become superseded by more advanced models within 1 year
rather than the more traditional 3 years. Many of the main sensor developers are
working on miniaturised, UAS versions of their laser and imaging sensors. Given this
rapid pace of change, there is a strong case for the information in this report to be
updated on a regular basis, perhaps every year.
UAS represent a new technology in the civilian domain, with a number of potential
benefits, including coverage of a range of surveillance scales, flexibility of operation
(launch from vessels, etc.), endurance, long operational lifetimes and HSE benefits
(remote piloting). However, it is important to be note that these benefits do not apply to
all types of UAS and there remain key constraints such as in relation to the regulatory
environment for their operation and in providing launch and recovery under certain
situations. The technology is evolving fast, costs are reducing, and models and capability
are, and will be, overtaken by new developments. Many of the current models are in
experimental or otherwise pre-commercial form, but the regulatory environment, at
least in Europe and North America, is moving towards access to airspace for UAS in or
soon after 2015. The industry should keep a close watching brief on this technology.
Traditional photographic sensors are now being augmented by a range of additional
sensors that have their own sets of strengths and weaknesses for OSR. Laser
fluorometers are potentially very powerful, but have operational limitations at present.
Radar is very useful as an all-weather surveillance technology, but suffers from a limited
ability to provide information on oil beyond detection, and can suffer from significant
false alarms. Other sensors have key strengths and weaknesses. It is therefore
increasingly being recognised that airborne remote sensing instruments need to be
available as (single or multiple platform) packages that can be used to coordinate
observations in such a way as to minimise false alarms, enhance sampling (e.g. day and
night) and optimise quality. Some integrated sensor packages offer this ability. With the
right combination of observations, it is possible to generate maps of oil extent with GIScompatible categories of oil thickness [26], with the potential to extend this to oil type
and condition.
This document has identified some key findings based on a workshop held in February
2013 and post-workshop surveys with platform and sensor providers. It is hoped that
this can form the basis for considering recommendations to the industry for developing
more effective airborne surveillance for OSR.
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74
Appendix A. Airborne Remote Sensing Platforms and Sensors
This appendix provides a list of those organisations which were contacted with the RFI survey, and those which responded.
Organisation
Airborne Hydrography AB, Klubbhusgatan 15, 553 03 Jönköping, Sweden
AirborneHydroMapping GmbH, Technikerstr. 21a, A-6020 Innsbruck, Austria
Riverview, A17 Embankment Business Park, Heaton Mersey, Stockport, SK4 3GN UK
1550 Crystal Dr, Suite 703, Arlington, VA 22202-4135, USA
1600 Commerce St., Boulder, CO 80301, USA
Via Cremonese 35/a, Parma 43126,Italy
1910 University Dr, Boise, ID 83725, United States
Dorfstrasse 53, Regensdorf-Watt, Zurich 8105, Switzerland
72 Lyme Road, Hanover, New Hampshire 03755-1290 , USA
DLR, Microwaves and Radar Institute, SAR Technology, Oberpfaffenhofen-Wessling, Germany
100,Yitzhak ha Nassi, Ashdod, 77102, Israel
Lungotevere Thaon di Revel, 76 - 00196 Rome , Italy
U.S. EP, Ariel Rios Building (5104A), 1200 Pennsylvania Avenue, NW, Washington, DC 20460, USA
3120 Buffalo Speedway, Houston, TX 77098, United States
FLIR Systems Australia Pty Ltd - Head Office 10 Business Park Drive Notting Hill VIC 3168 Australia
Fugro EarthData, 7320 Executive Way, Frederick, Maryland 21704, USA
7 Valetta Road, Kidman Park, S.A. 5025, Australia
100 Rialto Place, Suite 737, Melbourne FL 32901, USA
601 River Street, Fitchburg, MS 240, USA
Unit 11 / 10 Gladstone Rd, Castle Hill NSW 2154, Australia
Icaros, Inc. Headquarters, 1445 Research Boulevard, Suite 150, Rockville MD, 20850, USA
ITRES Corporate Head Office, #110, 3553 - 31st Street N.W., Calgary, Alberta, Canada, T2L 2K7
Carl-Zeiss-Strasse 1, 07739 Jena, Germany
1-146 Colonnade Rd S., Ottawa, ON, K2E 7Y1, Canada
Address
Anders Ekelund
Frank Steinbacher CEO
J. McCarthy / David Campbell
Steven P Anderson
Philip C. Lyman
A. Cavazzini / D. Mendel
John Bradford
Anna Somieski
Leonard Zabilansky
Ralf Horn
Simon Menicovici
Dr Roberta Fantoni
Mark Thomas
T Nedwed
Thomas A. Surran
Ed Saade
Craig Williams
Michael Frank
C. Van Veen / D. Bannon
Peter Cocks
Rob Carroll
Jason Howes
Achim Zimmermann
Alexandre Vorobiev
Contact name
A1. Sensor providers
Airborne Hydrography AB
AirborneHydroMapping GmbH
Apem Limited
Arete Associates
Ball Aerospace & Technologies
Blom CGR
Boise State Univ
BSF Swissphoto
CRREL
DLR
Elta Systems
ENEA
EPA
Exxon Mobil Upstream Research Co
FLIR Systems Australia Pty Ltd
Fugro EarthData, Inc
Fugro LADS Corporation Pty. Ltd.
Galileo Group
Headwall Photonics Inc.
Hyvista Corporation
Icaros
Itres
Jenoptik
Laser Diagnostic Instruments Int’l
Survey
Response
PIL-4000-38-TR-1.1
McPhar International
Metasensing
Norsk Elektro Optikk
NovaSol
Ocean Imaging Corp;
Odin Wave LLC
Optech
Opten
Optimare
PraEis Ltd.
Raytheon
Riegl USA
Sander Geophysics Ltd
SAS Actimar
Sentient
Specim
SpecTerra Ltd
Spectir
Spectral Cameras
SSC Airborne Systems
The Aerospace Corporation
Univ. Oldenburg
11th May 2015
An Assessment of Surface Surveillance Capabilities for Oil Spill Response using Airborne Remote Sensing
75
36 Ash Street Uxbridge, Ontario L9P 1E5 Canada
Space Businesspark, Huygensstraat 44, 2201 DK Noordwijk, The Netherlands
Hyspex, Solheimsveien 62A, P.O.Box 384, N-1471 Lørenskog, Norway
12675 Danielsen Court, Suite 406, Poway, CA 92064
201 Lomas Santa Fe Drive Suite 370, Solana Beach CA 92075 USA
1649 Neptune Drive, San Leandro, CA 94577, USA
Optech Incorporated 300 Interchange Way Vaughan, Ontario Canada, L4K 5Z8
3, Scherbakovskaya st., Moscow, 105318, Russia
OPTIMARE Sensorsysteme GmbH & Co. KG, Am Luneort 15a, D-27572 Bremerhaven
6801 Brecksville Rd. Ste. 206, Independence, OH 44131, USA
Raytheon Company, 2000 East El Segundo Boulevard, P.O. Box 902, El Segundo, California, 90245 USA
7035 Grand National Drive, Suite 100, Orlando, FL 32819, USA
260 Hunt Club Road, Ottawa, ON, K1V1C1, Canada
36 Quai de la douane, Brest 29200, France
PO Box 135, Port Melbourne, 3207 Victoria, Australia
Teknologiantie 18 A, 90590 Oulu, Finland
SpecTerra Services Pty Ltd, Suite 4, 643 Newcastle Street, Leederville 6007, Western Australia
SpecTIR International & Commercial Sales, 9390 Gateway Drive , Suite 100, Reno, NV 89521, USA
Channel Systems Inc., W.B. Lewis Business Centre, S2-24 Aberdeen Ave., Pinawa, MAN, R0E 1L0, Canada
SSC Group, P.O. Box 4207, SE-171 04 Solna, Sweden
The Aerospace Corporation, 2310 E. El Segundo Blvd., El Segundo, CA 90245-4691, USA
Fakultät 5: Mathematik und Naturwissenschaften Carl von Ossietzky Universität Oldenburg, Postfach 2503,
26111 Oldenburg, GERMANY
Timothy R. Bodger, President
Elisabetta Carnelos
Peter Kaspersen
Rick Holasek
Jan Svejkovsky
Brent
P. LaRocque/ Michel Stanier
Gennady Stepanov
Dr. Nils Robbe, CEO
Thomas Kerr
Jerry Powlen
James Van Rens
Malcolm Argyle
Marc Lennon
Paul Boxer
Aappo Roos (President)
Andrew Malcolm
Justin Janaskie
TBD
Olov Fäst, President
sylvia.s.shen
Juan Jose Trujillo Quintero
PIL-4000-38-TR-1.1
An Assessment of Surface Surveillance Capabilities for Oil Spill Response using Airborne Remote Sensing
Contact name
11th May 2015
Address
Chris Anderson
Rex Hayes
Brett Johnson
Adrian Wilcox
Marc Lennon
Rémi Bouchard
Christos Mavrakis, Director
Steven Tisseyre
N/a
Steve Laming
N/a
Fred Hagman
Todd Dunow
Peterson Martinski
Rex Hayes
Richard Blain
N/a
Matthew Ziska
Juan Manuel S
Marni McVicar
Marc Stromberg
Adriano Kancelkis
Marcel Dumeier
Kieran O'Toole
Wolfgang Grumeth, Ing.,
Fabio Fea
David Yoel
T. Carville / David Campbell
Bård Hall
Neil Dyer, CTO
76
Organisation
7170 Convoy Ct., San Diego, CA 92111
124 Industry Lane Hunt Valley, MD 21030 USA
Australia
3rd Floor,Lengai House, Wilson Airport, PO Box 705-00517, Nairobi, Kenya
36, quai de la Douane, F 29200 Brest
Action Air– Aérodrome de Cuers – 83390 Cuers – France
4, Krystalli Steet., PC1101, Nicosia, Cyprus
RD
2 The Downs, Harlow, Essex CM20 3 , United Kingdom
Trackair Services Ltd, Hut 28, Wycombe Air Park (EGTB), Booker, SL7 3DP UK
P O Box 302 072 North Harbour Auckland 0751 New Zealand
R. MICHIGAN, 561, BROOKLIN PAULISTA, SÃO PAULO - SP, 04566-000, Brasil
Airport Business Center, Luchthavenlei 7a, 2100 Deurne, Belgium.
59, King William Street, Kent Town, Adelaide, SA 5067
Rua Dr. Manoel Pedro, 785, Curitiba - Paraná, 80035-030, Brasil
Unit 1 585 Blackburn Road Notting Hill, VIC 3168 Australia
Bridge House, Brighton Road, Belmont, Surrey SM2 5SU, United Kingdom
AEROSYSTEMS, PO Box 766, Murray Bridge, South Australia 5253
900 Enchanted Way, Simi Valley, CA 93065, USA
Mikeletegi Pasealekua, 2 - Parque Tecnológico, 20009 SAN SEBASTIAN - SPAIN
Aeryon Labs Inc. 60 Bathurst Drive, Unit 1 Waterloo ON N2V 2A9 Canada
Warendorfer strasse 190, D-59227 Ahlen
R. Bruno Ruggiero Filho, 649, Jd. Parque Santa Felícia, São Carlos, SP 13562-420, Brazil
Ludwig-Erhard-Strasse 14, Kassel, Hessen, 34131 Germany
Control Tower, Daedalus Airfield, Lee on Solent, Hampshire, PO13 9YA, UK
Viktor Lang Straße 8, Flugplatz Ost, 2700 Wiener Neustadt, Austria
Unit 510 Level 5 BK Building , 72 Ladprao Road Bangkok 10900 Thailand
1279 Gulph Creek Drive,Radnor, PA 19087, USA
Bay 3&4, Aviation Park, Flint Rd., Hawarden Airport, Saltney Ferry, CH4 0GZ UK
PO Box 6405, N-9294 Tromsø, Norway
EAME (Head office), Newton House, Cambridge Business Park, Cowley Road, Cambridge, CB4 0WZ
A2. Platform Providers
3Drobotics
AAI Corporation
AAM Group
Aberdair Aviation
Actimar
Action Air
Aditess Ltd
Aerial Drones
Aerial Survey
Aerial Surveys Limited
AEROCARTA S.A.
Aerodata International Surveys
AEROmetrex
AEROSAT
Aerosonde Pty Ltd.
Aerospace Resources Ltd
Aerosystems Australia PTY LTD
AeroVironment Inc
AEROVISION VEHÍCULOS AEREOS
Aeryon Labs Inc
Agrarflug Helilift
AGX Technologia
Aibotix gmbh
Airborne Surveillance UK Ltd
Airborne Technologies GmbH
Alliance LP Drones
American Aerospace Advisors Inc
Apem Limited
Aranica AS
ARKex Ltd
Survey
Response
PIL-4000-38-TR-1.1
Ascending Technologies GMBH
Asia Air Survey
Australian Aerial Surveys
Beechcraft Corporation
Bell Geospace, Inc.
Blom CGR
Boeing Insitu
CAE Aviation
C-Astral Aerospace
Cobham Surveillance Australia Pty
Credent Technology
Cyberhawk
Delft Dynamics
Design Intelligence Inc
Diamond Airborne Sensing
DLR
Dragonfly Pictures, Inc.
Dynamic Aviation
Dyncorp International
Engefoto S/A
Engemap – Geoinformação
EON Geosciences
ESTEIO
Exxonmobil
Firefly Aviation Ltd
Fly-n-Sense
FotoTerra
Fugro Airborne Surveys
Fugro EarthData, Inc
Fugro Geospatial B.V.
Fugro LADS Corporation Pty. Ltd.
Fugro Malta
Fugro Spatial Solutions
Gatewing / Trimble
General Atomics Aeronautical
Systems Mariner
An Assessment of Surface Surveillance Capabilities for Oil Spill Response using Airborne Remote Sensing
Jan Link
Kazuo KAWAMURA
N/a
Jack Buckman
Scott Hammond
A. Cavazzini / D. Mendel
David Anderson
Hugo Zeler
Nejc Trost
Anthony Patterson
Lee Hon Chuan
Malcolm Connally
Arnout de Jong
James L Grimsley
Anita Kohlweg
Andreas Mueller
Michael W. Piasecki
Steve Scates
Steven Gaffney
N/a
Robson Augusto
Khaled Moussaoui
Carlos Valério A. da Rocha
Wolfgang Konkel
Bruce Evans, President
N/a
Luís Antônio de Lima
Louis Demargne
Ed Saade
Louis Demargne
Hugh Parker
Robert Hoddenbach
Michael DeLacy
Peter Cosyn
11th May 2015
Konrad-Zuse-Bogen 4, Krailling, Bayern 82152, Germany
Shinyuri 21 Building, 1-2-2 Manpukuji, Asao-ku, Kawasaki City, Kanagawa Prefecture, 215-0004 - Japan
Hangar 273, Rearwin Place, Bankstown Airport NSW 2200, Australia
10511 E. Central Avenue M/S B099-A01, Wichita, KS 67206-2557, USA
400 North Sam Houston Pkwy E Houston, TX 77060, United States
Via Cremonese 35/a, Parma 43126,Italy
118 East Columbia River Way, Bingen, WA 98605, USA
Luxembourg Airport, L-1110 Luxembourg
Gregorciceva 20, Ajdovscina, SI-5270, Slovenia
National Drive, Adelaide Airport, SA, 5950, Australia
85 Science Park Drive, #02-01 The Cavendish, Singapore 118259
Alba Innovation Centre, Alba Campus, Livingstone, EH54 7GA, UK
Molengraaffsingel 12, Delft, Zuid-Holland, 2629 JD, The Netherlands
PO Box 5839, Norman, OK, 73070, USA
Ferdinand Graf von Zeppelin Strasse 1, 2700 Wiener Neustadt, Austria
DLR Oberpfaffenhofen, Münchner Straße 20, 82234 Weßling, Germany
600 West Second Street, Delaware County, Essington, PA 19029, USA
1402 Airport Rd, Bridgewater, VA 22812, United States
3190 Fairview Park Drive, Suite 900, Falls Church, VA 22042, USA
Rua Frei Francisco MontAlverne, 750, Curitiba - Paraná, 81540-400, Brasil
Rua Santos Dumont, 160, Assis - São Paulo, 19806-060, Brasil
2021 Côte-de-Liesse, St-Laurent,QC, H4N 2M5
Dr. Reynaldo Machado, 1151, Prado Velho, Curitiba - 80215242, 8052430, Brasil
1545 Rt 22 East LG 340, Annandale, NJ 8803, USA
Springbank Airport, Unit 4, 550 Hurricane Dr, Calgary, AB T3Z 3S8, Canada
25 rue Marcel Issartier - BP 20005 33702 Mérignac CEDEX - France
Rua Traipú, 509 – Pacaembu 01235-000 - São Paulo – SP, Brasil
Fugro Head Office, Veurse Achterweg 10, 2264 SG, Leidschendam, the Netherlands
7320, Executive Way, Frederick, MD 21704
Dillenburgsingel 69, Leidschendam, 2263 HW, Netherlands
7 Valetta Road, Kidman Park, S.A. 5025, Australia
Malta International Airport, Gate P1, B Centre, Apron 1, Luqa
18 Prowse Street, West Perth, WA 6005, Australia
Gatewing NV, Buchtenstraat 9/1, 9051 Gent - Belgium
Jonny King
77
Tower 42, Level 23, 25 Old Broad Street, London EC2N 1HQ
PIL-4000-38-TR-1.1
Geo Data Solutions
Geoid Ltda.
Geosan LLC
Geotech Ltd.
Goldak Airborne Surveys
GPX Surveys Pty Ltd
GroundProbe Geophysics
Hangar18
Havariekommando
Heli Holland
Heli Service Belgium
Helica S.R.L.
Heliwest Group
Horizon SI
HyVista Corporation
IAS Airspace
Icaros, Inc.
IMAO
K8aranda Geophysique Inc.
Kestrel Maritime
Keystone
L'Avion Jaune
Luxcopter
Marine Spill Response Corporation
MaritimeRobotics
McElhanney Consulting Services Ltd
McPhar International
11th May 2015
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Head Office, Unit #14 - 25 Valleywood Drive, Markham, Ontario, L3R 5L9, CANADA
4402 Louis-B. Mayer, Laval, Québec, Canada H7P 0G1
Rua Rio Grande do Norte, 1560 - 3º andar, FUNCIONÁRIOS, Belo Horizonte - Minas Gerais, 30130-131,
Brasil
Sukhbaatar district, 6th khoroo, Baga toiruu, University street-8, Ulaanbaatar-210646a, Mongolia
245 Industrial Parkway North, Aurora, Ontario, Canada L4G 4C4,
2 Hangar Rd, Saskatoon, SK, Canada, S7L 5X4
4 Hehir St, Belmont, WA 6104, Australia
1/288 Victoria Road, Perth, Malaga, WA 6090, Australia
11004 W Greenspoint, Wichita, KS 67205 USA
Am Alten Hafen 2, D-27472 Cuxhaven, Germany
Kanaal B ZZ 3, 7881 NB Emmer Compascuum, The Netherlands
Gaasbeeksesteenweg 140 - B 1500 Halle
via F. LLi Solari 10, 33020 Amaro, Udine, Italy
Jandakot Airport 2 Harvard Road, Jandakot WA 6164, Australia
27 Akeman Close, Yeovil, Somerset, BA21 3QS UK
Unit 11 / 10 Gladstone Rd, Castle Hill NSW 2154, Australia
18 Point Street, Larne, Antrim, BT40 1TU, UK
4100 Monument Corner Drive Suite 520, Fairfax, VA 22030, USA
81 Avenue Aéroport, 87100 Limoges, France
1015 Rue Chef-Max-Gros-Louis, Wendake, QC GOA 4VO
2/95 Salmon St, Port Melbourne VIC 3207, Australia
Keystone Aerial Surveys, Inc., PO Box 21059, Philadelphia, PA 19114
1, Chemin du Fescau, F 34980 Montferrier sur Lez, France
295, rue de Luxembourg, L-8077 Bertrange, Luxembourg
220 Spring St, Herndon, VA 20170, United States
Maritime Robotics AS, Brattørkaia 11- Pirterminalen, 7010 Trondheim, Norway
Suite 100 780 Beatty Street, Vancouver, BC V6B 2M1, Canada
36 Ash Street Uxbridge, Ontario L9P 1E5 Canada
José de Figueiredo Street, 320, Unit 35, Condominium Office House, Barra da Tijuca, RJ, Brazil, CEP 22793170
MPX Geophysics Ltd.
Houston Headquarters, 10350 Richmond Ave, Suite 550, Houston, TX 77042, USA
Unit 1, Stand 98, Tijger Vallei Office Park, Silverlakes, Pretoria, South Africa
195 Clayton Dr. Unit 11, Markham, Ontario, L3R 7P3, Canada
Vassbotnen 1, 4313 Sandnes, Norway
Microsurvey Aerogeofisica Ltda
Neos Geosolutions
New Resolution Geophysics
New-Sense Geophysics Limited
NOFO
Mouhamed Moussaoui
Mario Oscar de Souza Lima
N/a
N/a
Ben Goldak
Katherine McKenna
Steven Johnson
Jimmy Prouty
N/a
Ted Heinen
Walter Vlerick
Federico Facchin
Luke Aspinall
Jake Memery
Peter Cocks
Angela Dickenson
Robert Carroll
Damien GIOLITO
Bertrand Simon, Director
N/a
Mary Potter
Michel ASSENBAUM
Siemon Smid
Judith Roos
Vegard Evjen Hovstein (MD)
Daniel J S Tresa
Timothy R. Bodger, President
José Divino Freitas Barbosa
Daniel J. McKinnon,
President
Jim Hollis, President and CEO
Ollie Wright, CEO
Dr W. E. S (Ted) Urquhart
Jorn Harald S. Andersen
PIL-4000-38-TR-1.1
Northrop Grumman
NOVATEM Inc.
Ocean Imaging Corporation
OSRL Ltd
Outline Global
Oxford Blue Systems
Pasco Corporation
PDG Helicopters
Precision Geosurveys
Prioria Robotics
Provincial Aerospace
Prospectors A. S.
PT Surtech Utama Indonesia
Quantum Spatial
Remote Aerial Detection Systems
RVL group
Sander Geophysics Ltd.
SECON Aries Aerial Surveys (SAAS)
senseFly SA
SkyTEM ApS
Softmapping - Engenharia Ltda
Southern Mapping Company
SpecTerra
Spectrem Air
SpillConsult Ltd
Summit Aviation Inc.
Sundt Air
Swiss UAV AG
Tasuma UK
Terraquest Ltd.
Terratec AS
Texas A&M Univ. Corpus Christi
Thomson Aviation
UAVVision
University of Michigan
11th May 2015
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2980 Fairview Park Drive, Falls Church, VA 22042, USA
1087, Chemin de la montagne, Mont-Saint-Hilaire, Québec, Canada, J3G 4S6
201 Lomas Santa Fe Drive, Suite 370, Solana Beach CA 92075
Lower William Street, Southampton SO14 5QE, UK
Level 1, Building B, 661 Newcastle Str, Leederville, WA 6007
17 Cratlands Close, Stadhampton, Oxfordshire, OX44 7TU, UK
1-1-2 Higashiyama, Meguro-ku, Tokyo 153-0043, Japan
The Heliport, Dalcross, Inverness, IV2 7XB
520-355 Burrard Street, Vancouver, BC, Canada V6C 2G8
606 SE Depot Ave, Gainesville, FL 32601, USA
Hangar 1, St. John's Intl Airport, St. John’s, Newfoundland, Canada, A1A 5B5
Rua Santa Alexandrina, 1011 – Castelinho, Rio Comprido – Rio de Janeiro 0 RJ, Brasil, CEP: 20261-235
Satmarindo Building Jl.Ampera Raya No.5 Jakarta 12079
4020 Technology Parkway, Sheboygan, WI 53083, USA
4 Wilder Drive #7, Plaistow, NH 03865
Building 21, Anson Road, East Midlands Airport, Castle Donington, DERBY, DE74 2SA
260 Hunt Club Rd, Ottawa, ON K1V 1C1, Canada
147, 7B Road, EPIP Whitefield, Bangalore - 560066, India
Route de Genève 38 (Z.I. Châtelard Sud) 1033 Cheseaux-Lausanne SWITZERLAND
Dyssen 2, DK-8200 Aarhus N, Denmark
Rua Francisco Derosso, 603, Curitiba - PR, 81710-000 Brasil,
39 Kingfisher Drive, Fourways, Sandton, Johannesburg, South Africa
SpecTerra Services Pty Ltd, Suite 4, 643 Newcastle Street, Leederville 6007, Western Australia
c/o Anglo Operations Ltd., 44 Marshall Street, Johannesburg, 2001, South Africa
SpillConsult Limited, Unit 16, Basepoint, Andersons Road, Southampton, Hampshire, UK, SO14 5FE
4200 Summit Bridge Rd, Middletown, DE 19709 USA
PO Box 31, N-2061 Gardermoen, Norway
Bachmatten 2a, CH - 4435 Niederdorf
UNIT 11, UPLANDS WAY, Blandford, Dorset DT11 7UZ UK
2-2800 John Street, Markham, Ontario, Canada L3R 0E2
Pb. 513, 1327 Lysaker, Norway
Science and Engineering Department, 6300 Ocean Drive, Corpus Christi, Texas 78412
PO Box 8133, Griffith East, NSW, 2680
UAV Vision Pty Ltd, 2/10 Uralla Street, PORT MACQUARIE, NSW 2444
500 S. State Street, Ann Arbor, MI 48109 USA
N/a
Dr Pascal Mouge, Geo.,
Jan Svejkovsky
Emma Hughes
Ross Lewin
Philip Gibbs
Yuji MESAKI
Ian Innes
Harmen J. Keyser, President
Bryan da Frota
Derek Scott
N/a
Greg Neubecker, President
Terry Keating
Abe Ash
David Connor
Luise Sander
N/a
Antoine Beyelerr
Flemming Effersø, CEO
Marcio Polanski
Norman Banks, CEO
Andrew Malcolm
Lazarus Zim
Stuart Gair
Michelle Susi
Tor Bratli, CEO
Mr. Philippe Niquille
W H Longley
Howard Barrie (President)
Lennart Flem
David Bridges
Ed Dowling, MD
Jason Clifton
Dr Ella M Atkins
PIL-4000-38-TR-1.1
Unmanned Aerial Systems Australia
URSUS-AIRBORNE
USGS
VDOS LLC
Xcalibur Airborne Geophysics
11th May 2015
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14 Grays Road, Gaythorne, Brisbane, QLD Australia
LEERTENDIJK 8, 7683 SE DEN HAM, THE NETHERLANDS
Box 25046 Denver Federal Center, Denver, CO 80225, USA
230 SW 6th St, Corvallis, OR 97333, USA
42 LEBOMBO ROADASHLEA GARDENS 0081, South Africa
Phil Swinsburg
Marc Goossens CEO
Roger Clark
Patrick J Burke, Seth Johnson
Simon Bosch Commercial
An Assessment of Surface Surveillance Capabilities for Oil Spill Response using Airborne Remote Sensing
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11th May 2015
Appendix B. References and Sources
[1]. OGP/IPIECA, An Assessment of Surface Surveillance Capabilities for Oil Spill Response
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