Oil spill sensitivity mapping
Image credit: NOAA Office of Response and Restoration
Oil spill sensitivity maps are tools supporting response strategy development, and are an essential part of contingency planning. Contingency scenarios are focused on areas where oil is handled or moved, or is likely to be transported by conditions present in a spill event. As a decision support tool, the maps primarily address strategic and tactical aspects of response planning; prioritization of effort to particular areas, and implementation of clean-up activities. Marine coastal areas are the prime concern of contingency planning, but lake and river areas are also addressed when in proximity to significant industry activity.
The Environmental Sensitivity Index (ESI) methodology is recognized internationally as an effective approach to oil spill planning (cf. IPIECA oil spill sensitivity mapping report, NOAA ESI page). Its core focus is on categorizing shoreline type to determine potential oil penetration, persistence time of oil on the shoreline, and biological sensitivity. Quantification of these factors can be addressed using EO methods.
Oil penetration depends on shoreline soil type, grain size and slopes. These factors are addressed by EO derived surficial geology, and slope products. Further, slope stability can be assessed, which can be a factor where oil spills result from extreme weather conditions (e.g., monsoon with potential slope failure).
Oil persistence time on the shoreline depends on penetration, but also exposure to wave action and tidal energy. Winds, wave and tidal motion can be monitored at a coarse scale from satellite altimetry systems (e.g., Jason-2). Bathymetry can be measured with good accuracy to approximately 10 m, and often as deep as 20 m or more. EO derived bathymetry would be especially useful for remote areas where there is a risk of oil being transported, but in which there is inadequate bathymetric information. Wave energy models can be created by combining these data. Further, assessment can be made of the spatial complexity of the coastline/shoreline, which will influence physical access for crews, and oil retention.
Biological sensitivity can be estimated at both coarse and finer levels. Ocean and foreshore primary productivity (photosynthetic activity) can be measured from multispectral EO data to capture general biological activity (e.g., ocean colour and vegetation biomass indices). EO derived land cover and habitat captures much more detail regarding the biological importance of an area. Information such as presence and extent of seagrass, tidal flats, mangroves and wetlands can be determined to evaluate biological risk. Proximity to freshwater bodies can also be measured.
Assessment of human risk factors and liabilities can also be supported by EO data. Proximity to infrastructure, parks and urban areas can be assessed, as well as proximity to and productivity of agricultural and forested lands.
Product delivers maps or vector digital files that delineate and identify ESI themes, such as:
Known restrictions / limitations
Lifecycle stage and demand
Exploration: Knowledge of risk potential during exploratory drilling.
Development: Knowledge of risk potential will influence development decisions regarding asset and infrastructure placement and emergency protocols.
Production: Health and safety, liability and environmental response will be affected by high quality contingency planning supported by oil spill sensitivity maps.
Decommissioning: Plans prepared for production will continue to be useful in case of emergencies during decommissioning.
Geographic coverage and demand
Demand and coverage is global. Areas with high wave energy, proximate to human populations or high value ecological systems will be of special concern.
OTM:032 Detecting ecosystem damages
OTM:040 Security of pipelines
Input data sources
Optical: VHR1 or VHR2 (bathymetry), HR1, HR2, MR1, MR2
Radar: HR1, HR2
Spatial resolution and coverage
0.5-10 m for assets/infrastructure
5-30 m for critical habitat
1 m or better for bathymetry
Minimum Mapping Unit (MMU)
Accuracy / constraints
Thematic accuracy: Land cover/land use, assets/infrastructure and water extent 80-90%.
Spatial accuracy: Dependent on input component products, but typically within 1 – 2 pixels.
Accuracy assessment approach & quality control measures
Statistical confusion matrix with user’s and producer’s accuracy for land cover/land use and water extent. In-situ measurements.
Frequency / timeliness
Observation frequency: Based on frequency of satellite imagery, but typically 2 – 20 days.
Timeliness of delivery: Delivery required prior to or at the start of the development stage.
On-demand availability for most component products from commercial suppliers.
New acquisitions can be requested globally.
Delivery / output format
Oil Spill Sensitivity Mapping
# of Pages:
Internal – Project consortium and science partners
External – ESA
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