The Integration of Remote-Sensing Detection Techniques into the Operational Decision-Making of Marine Oil Spills
Abstract
Remotely-sensed data collected from satellites, airplanes and unmanned aerial systems can be used in marine oil spills to identify the overall footprint, estimate fate and transport, and to identify resources at risk. Mandates for the use of best available technology exists for addressing marine oil spills under the jurisdiction of the USCG (33 CFR 155.1050), though clear pathways to familiarization of these technologies during a marine oil spill, or more importantly, between marine oil spills, does not. Similarly, remote-sensing scientists continue to experiment with highly tuned oil detection, fate and transport techniques that can benefit decision-making during a marine oil spill response, but the process of translating these prototypical tools to operational information remains undefined, leading most researchers to describe the "potential" of these new tools in an operational setting rather than their actual use, and decision-makers relying on traditional field observational methods. Arctic marine oil spills are no different in their mandates and the remote-sensing research undertaken, but are unique via the dark, cold, remote, infrastructure-free environment in which they can occur. These conditions increase the reliance of decision-makers in an Arctic oil spill on remotely-sensed data and tools for their manipulation. In the absence of another large-scale oil spill in the US, and limited literature on the subject, this study was undertaken to understand how remotely-sensed data and tools are being used in the Incident Command System of a marine oil spill now, with an emphasis on Arctic implementation. Interviews, oil spill scenario/drill observations and marine oil spill after action reports were collected and analyzed to determine the current state of remote-sensing data use for decision-making during a marine oil spill, and to define a set of recommendations for the process of integrating new remote-sensing tools and information in future oil spill responses. Using automated synthetic aperture radar analyses of oil spills in a common operational picture as a scientific case study, this presentation is a demonstration of how landscape-level scientific data can be integrated into Arctic planning and operational decision-making.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFMPA11A0204G
- Keywords:
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- 0815 Informal education;
- EDUCATION;
- 1632 Land cover change;
- GLOBAL CHANGE;
- 1880 Water management;
- HYDROLOGY;
- 6630 Workforce;
- PUBLIC ISSUES