Integration of remote sensing technologies into Arctic oil spill response

Dissertation (Ph.D.) University of Alaska Fairbanks, 2020 Identifying the tools and pathways to successful integration of landscape level science into decision-making processes is vital for quality environmental stewardship. Remote sensing information can provide critical facts to decision makers th...

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Bibliographic Details
Main Author: Garron, Jessica I.
Other Authors: Meyer, Franz, Trainor, Sarah, La Belle-Hamer, Nettie, Lee, Olivia, Mahoney, Andrew
Format: Doctoral or Postdoctoral Thesis
Language:English
Published: 2020
Subjects:
Online Access:http://hdl.handle.net/11122/12397
Description
Summary:Dissertation (Ph.D.) University of Alaska Fairbanks, 2020 Identifying the tools and pathways to successful integration of landscape level science into decision-making processes is vital for quality environmental stewardship. Remote sensing information can provide critical facts to decision makers that historically were only available via manned airplane flights and ground truthing expeditions. Remote locations like the Arctic are well suited for monitoring with remote sensing tools due to the lack of transportation infrastructure and communications bandwidth. Remote sensing tools can be valuable when monitoring specific Arctic targets like ocean going vessels, sea ice, coastal erosion, off-shore resource development infrastructure, and oil spills. This dissertation addresses how to mount a more efficient and informed response to Arctic oil spills by capitalizing on available RS tools. I posed three research questions to frame this work, 1) What remote sensing tools are currently available, as compared to those currently used in the Incident Command Structure of an oil spill response? 2) Are there barriers to additional remote sensing tool use for oil spill response support? 3) What process changes can improve or increase remote sensing data use in oil spill detection and response? I conducted a four-phased, exploratory sequential mixed methodological study to examine current remote sensing capacity and solutions to expand remote sensing use in support of oil spill response. Phase One defined the remote sensing tools available to support oil spill response, identified how those tools are being used in support of oil spill response actions, and was used as the foundational research to inform the following phases of the study. Phase Two used cloud-processing resources to establish an automated oil detection pipeline. Phase Three addressed human-driven barriers to remote sensing tool use identified in phase one through remote sensing tool training, knowledge coproduction, and remote sensing data integration into ...