Arctic at Risk
GIS, remote sensing aid in developing an ecological risk assessment process
By E. Terrence Slonecker, Peter Jutro, Deborah Mangis, Michael True, and Brian Orlick

In 1993, the United States and Russia, seeking to expand bilateral cooperation, formed a Bi-national Commission formally called the U.S./Russian Joint Commission on Economic and Technological Cooperation. Co-chaired by Vice President Gore and Prime Minister Chernomyrdin, the commission is more commonly known as the Gore-Chernomyrdin Commission, or GCC. The goal of the GCC was to expand cooperative efforts in business development, defense conversion, space, energy, health, scientific research, agriculture, and the environment.
     Environmental issues were a key theme in the GCC agenda because of the growing realization that environmental degradation is often a key factor in political and economic stability around the world. In May 1995, Vice President Gore and Prime Minister Chernomyrdin held talks on the post cold war uses of classified reconnaissance technology, termed National Security Systems, or NSS data, to study environmental issues. Underlying these talks was the belief that the intelligence assets of both countries' data represent one of the best sources of global environmental information available to study these problems. As a result, a new GCC environmental initiative was formed. The Environmental Working Group (EWG), representatives of U.S. and Russian scientists from various government agencies along with U.S. and Russian commercial oil and gas interests, was established to study the utility of using intelligence data to study several environmental issues including; 1) the health of critical forest ecosystems, and 2) the risks posed by oil and gas development in fragile Arctic and Subarctic ecosystems.
     To study the oil and gas issue, the EWG selected an area of on-going oil and gas development near the Ob River in the Russian Arctic. Remote sensing data from civil and classified sensors of both the U.S. and Russia were used to create unclassified data layers to be compiled into a Geographic Information Systems (GIS) database. This database is being used to establish the ecological risk associated with oil and gas development in accordance with the formal risk assessment process established by the U.S. Environmental Protection Agency.

Arctic Ecosystems
The Arctic environment is one of the most ecologically unique areas in the world. Indigenous human populations and a wide range of plant and animal life thrive in an often hostile environment of temperature and other climatic extremes. The behavior and distribution of sea ice, the existence of permafrost, permanently frozen ground layers, wide seasonal variations in sunlight, its susceptibility to perturbations in Subarctic ecosystems, and many other factors combine to make the Arctic one of the most unique, and fragile, ecosystems on the planet.
     The Arctic ecosystems have endured a long-term, world-wide attack from industrial pollution which naturally migrates with water and air movement or is a direct result of other anthropogenic activities within the Arctic circle. Thinning atmospheric ozone, pesticides, heavy metals, and even radio nuclides have been detected at significant levels throughout the Arctic food chain. Although these pollutants exist virtually everywhere on earth, the bio-accumulation is especially critical in this environment because the reduced sunlight and extensive cold slow the natural breakdown of these chemicals.
     Compounding the problem of existing anthropogenic pollution is the fact that the Arctic and Subarctic areas of the world also contain some of the most promising energy resources on the planet. The process of oil and gas exploration, extraction, and transport creates numerous additional alterations of the landscape and possibilities for ecosystem damage through the accidental release of contaminants. Rich oil and gas reserves have been a major and increasing source of energy for many Arctic nations, including the U.S. and Russia.
     For these reasons, scientific study and protection of Arctic resources have been the subject of much recent international concern. The Arctic Environmental Protection Strategy, signed by the Arctic nations in Finland in 1991, is testament to the urgency and significance of the Arctic ecosystem issues.

Intelligence Policy
Since the 19th Century, overhead imagery has been an integral part of intelligence collection and information policy among the countries of the world. Balloons, aircraft, and eventually satellite platforms have and continue to record a scientific treasure of high spatial resolution information about the world's surface. Although the immediate information purpose was military/intelligence in nature, such as mapping, order-of-battle, combat readiness, or defensive infrastructure, imagery inherently records data on environmental conditions such as vegetation pattern, extent and distribution of natural resources, topography and landscape alterations.
     However, the relaxation of security constraints on using the United States' classified imagery for environmental purposes has been a long, slow process. It began in the 1970s with the removal of some of the highest security compartments and recently culminated in executive order 12951, in which President Clinton authorized the declassification and release of over 800,000 images of previous classified global satellite imagery from the Corona, Argon, and Lanyard systems.

GCC
The U.S./Russian Commission on Economic and Technological Cooperation was established by U.S. President Clinton and Russian Federation President Yeltsin during the Vancouver Summit in April 1993. The original emphasis of the commission was to enhance cooperation in the areas of space and energy but was quickly expanded to include several other topics such as defense conversion, health, science, agribusiness, and the environment. The GCC also established two special working groups to investigate 1) the establishment of Russian capital markets and 2) the use of declassified intelligence data for environmental purposes, called the Environmental Working Group.
     The EWG agreed in 1995 that one of their primary efforts should be the study of the risks posed by oil and gas development in the fragile Arctic and Subarctic ecosystems. These areas are important natural resources for both countries and are under increasing pressure for economic development. Both sides agreed that the specific activities of the oil and gas subgroup should be focused on the information needed to ensure environmental security while exploring economic development.

REMOTE SENSING DATA SOURCES
The use of remotely sensed data was critical to the overall project and analytical processes for two primary reasons. First, the com- bined and peaceful use of a wide range of remote sensing systems was central to the Gore-Chernomyrdin philosophy. Second, the remote location of this area severely limited the availability of other data sets, making remote sensing data critical to the process. Civilian and NSS remote sensing systems both contributed critical input data to the GIS by identifying and locating oil infrastructure, outlining water bodies, characterizing vegetation, and delineating wetland and flood boundaries. The remote sensing systems utilized for this project include the following:

Landsat
Both the Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM), with their discrete multispectral bands, were major data sources for GIS development and risk analysis such as change detection. In particular, the Landsat spectral bands allow studies of changes in lake productivity to be performed. These lakes and corresponding wetland areas are critical habitats to numerous fish and other species and their continued health is fundamental to the ecological integrity of this region.

SPOT
The French SPOT satellite provided 10 meter (m) resolution panchromatic data and had sufficient resolution to detect oil production pads and pipelines in the developed regions. This system provided the highest spatial resolution data available from a commercial sensor.

AVHRR
The Advanced Very High Resolution Radiometer (AVHRR) has been a constant component of the U.S. National Oceanic and Atmospheric Administration (NOAA) weather satellites. The coverage is daily and the resolution is 1.1 kilometers (km). The Ob River floodplain is wide enough that it is resolved on the low-resolution AVHRR images. This sensor is capable of monitoring the ice-blocked northern region of the Ob which causes the extensive flooding at the Priobskoye location. The false colors from AVHRR bands 2, 5, and 7 are well-suited to revealing the vegetation (red) and flood conditions (dark blue).

National Security Systems
Vice President Gore and Premier Chernomyrdin agreed, early in the process, that one of the main purposes of the EWG was to examine the use of the national security data acquisition systems of both countries-space-based, airborne, oceanographic, or in situ-and derive unclassified GIS products from its data for environmental use. Because of the remote, inland location of the Priobskoye site, imaging sensors (both space-based and airborne) fulfilled the above directive for this project and provided high spatial resolution data to complement the spectral, but lower spatial resolution, data from the civil sensors.

GIS DATABASE DEVELOPMENT
Two general GIS databases were cooperatively compiled by both the U.S. and Russian teams using a variety of remote sensing and existing data sources including data compiled by Amoco in its oil exploration project. Overcoming technical and scientific language barriers, cartographic and technical differences were jointly edited by U.S./Russian teams of scientists, often working through interpreters. One database was compiled at a 1:250,000 scale for overall analysis and the other was compiled for Site 1 at 1:25,000 scale to show site-specific detail of the oil production infrastructure.

THE ECOLOGICAL RISK ASSESSMENT PROCESS
One of the primary goals of the EWG investigation was to develop a methodology for the risk assessment process and to show that this process could be utilized to make informed environmental decisions with respect to sensitive environments and economically valuable resources. By using GIS technology as a foundation for the risk assessment methodology, managers not only derive greatly improved emergency planning information, but also gain the tools necessary to balance economic and environmental factors during oil exploration, production, and decommissioning activities.

ANALYSIS and RESULTS
Three risk assessment examples were developed using GIS and remote sensing. Prioritized among the highlighted examples were economically-valued vegetation, wildlife, and especially food sources of the small indigenous population.

Oil Spills
Oil spills are perhaps the most "disaster-like" environmental problem associated with oil production activities. Even with all the safeguards developed by the regulatory and oil industries, the dynamics of major construction efforts, hostile climate, and water movement create a statistical chance for a spill to occur. It is the purpose of the risk assessment to point out the areas of maximum risk, which can then be reduced by design changes or the placement of cleanup equipment in close proximity to high risk areas.
     When a spill does occur, it has a strong negative impact on environmental conditions. Several factors have an impact on oil spills and the consequences of such oil spills. Some of the factors are related to oil composition, whereas other factors reflect natural conditions at the time of oil spills. Depending on the oil's grade and characteristics, an oil spill could cause dramatic consequences on the environment.
     Environmental conditions (including seasonal effects) in a particular area also provide significant impact on the dissemination of oil pollutants. Important parameters required for an assessment of oil spill dissemination include: landscape, vegetation, pipeline construction routes, direction and speed of rivers and streams, wind direction, and temperature. In addition, processes such as evaporation, dispersion, and emulsification are important for calculating the time that oil would remain in the environment.
     In the first example, simulated oil spills are analyzed at three points of existing and proposed pipelines. Then, results of extending the point calculations to the entire proposed pipeline are presented. The three oil spill sites correspond to three types of landscape conditions that are present in Test Site 1 of the Priobskoye oil field, i.e., river, floodplain, and terrace. The EWG have considered a hypothetical situation where a pipeline breaks presumably due to erosion, engineering processes (sagging, heaving), accidental mechanical breaks in airtightness of pipelines (off-road vehicle, grader, icebreaker), or increase in acceptable pressure levels in pipeline. The result is an uncontrolled oil spill with oil volume hypothetically reaching 500 tons (until the time of eliminating the source of an oil spill). Oil spill response, containment, and reclamation time is not determined. Such a hypothetical oil spill corresponds to a significant accident that would be an emergency situation on the regional level. This hypothetical situation is assessed for three seasons: winter, spring (flooding), and summer (dry). Point 1 is located in the area directly adjacent to the Ob River at a section of the proposed pipeline adjacent to the water surface. Point 2 is located in an area of the flood plain with a section of the proposed pipeline. Point 3 is located in the terrace area where a section of existing pipeline is adjacent to a road and a small tributary.

Road Construction
Road construction poses a serious threat to the environment. As a rule, road planning is based on economic effectiveness and safety concerns, comprised of a number of factors, such as ponding and drainage of terrain on both sides of the road, which leads to infringement on the hydrological and hydrogeological regime of the territory. Another factor is contamination of the territory during road construction and operation with construction and general waste and oil products that contain toxic and hazardous materials. Also, consideration must be given to the construction process itself, as it is an infringement on landscape integrity. Finally, there is the problem of new ecological risks that are related to construction of additional engineering facilities along the road, such as power lines, pipelines, etc.
     The road in Site 1 crosses the Ob floodplain and Maliy Salym river and runs through the terrace. The road, which includes road lanes, cushioning layer, drainage ditches, and adjacent territory, is 50m wide. In addition, the EWG reviewed affected areas on both sides of the road that are 1km wide on each side. The majority of birds can be easily dispersed, and the noise pollution covers large open areas in the floodplain. Forests and tall vegetation serve as noise absorbers, although the road at Site 1 crosses through sections of tall vegetation only after crossing over the Maliy Salym river where the developed territory begins. As mentioned earlier, the developed territory is under significant anthropogenic impact, therefore waterfowl do not inhabit such areas. As a result, ecological risk for waterfowl on the left bank of Maliy Salym is low. The risk increases in the areas where the road crosses sections of the waterfowl's preferred habitat.
     The above problems, as well as ecological risk, will be reduced if the road construction route is modified by introducing additional horizontal drainage systems and diverted to cross over high ground that is less susceptible to drainage effects. By employing classic GIS mapping and optimization techniques, road construction plans can easily be developed that minimize adverse environmental effects.

Oil Spray
Oil contamination of sensitive environments can also occur through the air during the drilling and production process. During drilling, a "blow out" of a highly pressurized field can lead to large releases of oil into the air and terrain. However, a more common scenario occurs during routine operations. After production begins, the pumping stations and other equipment can produce small leaks that produce aerosols that deposit oil on the landscape dependent on several factors including wind, oil type, pressure, and ambient temperature. This deposition of oil could have significant ecological impacts on nearby vegetation and aquatic resources.
     To assess the ecological risks of this oil spray deposition, two separate projects were undertaken. First, an algorithm of oil spray movement was developed based on characteristics of the native oil, wind patterns from Russian meteorological stations, and physical models of aerosol transport. The airborne contamination is at nearly ground level but the spray may have an upward component. In addition, there may be updrafts, which give another vertical component. Thus, the oil droplets become projectiles influenced by horizontal wind, air drag, and gravity. With a large uncertainty in the oil spray parameters, the extent of the oil spray plume and its resultant damage could potentially include a very large area. However, based on model simulation and GIS analysis, the medium and high risks to forest vegetation were shown to be relatively local to the pumping stations.
     A second project was undertaken, using spectral remote sensing data to determine if there was any impact, over time, of oil spray deposition on the biological productivity of the many lakes in the Priobskoye area. Multi-spectral remote sensing methods are based on the fact that phytoplanton, containing chlorophyll a, strongly absorbs energy in the blue and red regions of the electromagnetic spectrum, and reflects energy in the green part of the spectrum. By using a basic green/blue band ratio technique, many research applications have successfully correlated in situ measures of phytoplankton biomass with data from multispectral remote sensing systems. Successful applications have used data from several sensors including Landsat TM and Landsat MSS. However, these methods rely on simultaneous in situ phytoplankton measures for calibration. In the Priobskoye study area, this type of measurement was not performed at the time of the Landsat TM data collection. Therefore, two other techniques were used to assess potential differences in lake productivity in this area.
     The first technique used a simple 2:1 band ratio from 1984 and 1996 Landsat TM scenes that were acquired for this study. Since airborne oil deposition is not likely to travel long distances, it was assumed that oil effects on lakes would be restricted to areas surrounding the specific oil production sites. The Landsat TM scenes cover an extensive area of landscape, and represent before and after periods of oil production activity in the area. Green/blue band ratios from both the 1984 and 1996 data showed no significant differences in the band ratio signature from any lakes located throughout the Landsat TM scenes, except for areas where there was a significant haze problem in the 1984 imagery and one small lake in the southeast part of the scene.
     The second method utilized was a Change Vector Analysis (CVA) technique, which is a radiometric change analysis algorithm that uses multiple dates of geometrically registered and radiometrically corrected imagery. CVA utilizes n-dimensional multispectral imagery analysis to produce two fundamental statistics from the radiometric comparison of the multiple date images; change direction and change magnitude. These two statistics, when mapped on a Cartesian coordinate system, essentially reduce multiple bands and multiple dates of imagery into a two-dimensional 'change space.' This technique has the advantages of including all multispectral bands in the change determination and can detect changes in both the actual land cover, as well as in subtle changes in condition.
     This CVA technique was applied to the Landsat TM data in the overall region of the oil and gas study. Again, very few significant changes in the lake reflectance were noted throughout the greater oil and gas production area and the overall Landsat TM scene in general. One small lake in the extreme eastern section of the study area appears to have been impacted by sedimentation, most likely from adjacent pipeline and/or tank construction activities. This conclusion was based on the observation of new construction in the area and the fact that this was the only lake where any significant change could be detected.
     The combined use of GIS and remote sensing technology has utility for international risk assessment. Five key findings resulted from the final EWG report on oil and gas activities. First, high resolution (1-2m) remotely sensed imagery is an essential ingredient for reliable GIS-based environmental risk assessments.
     As a result of this GCC initiative, it was also determined that historical high-resolution imagery, often available only through National Security Systems, is essential to the development of accurate baseline information on ecological conditions.
     Next, the illustrated risk assessment scenarios showed the dynamic nature and ecological sensitivity of the Subarctic ecosystems; and thus, the importance of conducting ecological risk assessment prior to oil and gas development.
     Cooperative projects, such as the one demonstrated here between U.S. and Russian government agencies and oil companies, will significantly lessen the adverse environmental impact of oil and gas development.
     And, finally, GIS technology, as demonstrated by this project, is an excellent tool for managing, analyzing, and displaying the data essential to the risk assessment process in fragile Arctic ecosystems. Even when there are significant cultural, legal, and language barriers to the assessment process, GIS technology itself can serve as 'the language of international ecological risk assessment.'

REFERENCES
EWG. 1998. Environmental Risk Assessments of Oil and Gas Activities Using National Security and Civilian Data Sources. U.S. Russian Joint Commission on Economic and Technological Cooperation. Environmental Working Group Final Report March 1998.

Johnson, R.D. and Kasischke, E.S. 1998. Change Vector Analysis: A Technique for the Multispectral Monitoring of Land Cover and Condition. International Journal of Remote Sensing. 19(3): 411-426.

Keith, R.F. 1994. The Ecosystems Approach: Implications for the North. CARC Northern Perspectives. 22(1) 1-6. Lo, C.P. 1986. Applied Remote Sensing. Longman Scientific and Technical, 393 pages.

MacDonald, R.A. 1995. Opening the Cold War Sky to the Public: Declassifying Satellite Reconnaissance Imagery. Photogrammetric Engineering and Remote Sensing, 61(4):385-390.

Sater, J. E. A.G. Ronhovde and L.C. Van Allen. 1971. Arctic Environment and Resources. The Arctic Institute of North America, Washington D.C. 309 pp.

Twitchell, K. 1991. The Not-So-Pristine Arctic. Canadian Geographic, Feb/March 1991, pp. 53-60.

U. S. E. P. A. 1992. Framework for Ecological Risk Assessment. Office of Research and Development, Washington, D.C. EPA/630/R-92/001.

U. S. E. P. A. 1996. Proposed Guidelines for Ecological Risk Assessment. Office of Research and Development, Washington, D.C. EPA/630/R-95/002B.

ACKNOWLEDGEMENTS
Special recognition and many thanks go to our Russian collaborators on this project: Vsevlod V. Gavrilov, Oleg I. Komarov, Sergey N. Rybakov, and Oleg V. Zerkal of the Russian Federal Center for Geoecological Systems, and Sergey V. Ivanov of the Ministry of Defense of the Russian Federation.

NOTICE
The U.S. Environmental Protection Agency, through its Office of Research and Development, funded and performed the research described here. It has been subjected to the Agency's peer review and approved by the Environmental Protection Agency for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

E. Terrence Slonecker, Pert Juto, and Deborah Mangis are employed with the U.S. Environmental Protection Agency; Michael True is employed with the Environmental Research Institute of Michigan; and Brian Orlick is employed with National Imagery and Mapping Agency.

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