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Uncrewed Aircraft Systems, Machine Learning, and Polarimetric Imaging for Enhanced Marine Debris Shoreline Surveys
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2023
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[PDF-18.92 MB]
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Alternative Title:Final Project Report
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Corporate Authors:National Centers for Coastal Ocean Science (U.S.). Marine Spatial Ecology Division. ; NOAA Uncrewed Systems Research Transition Office. ; United States. National Ocean Service. Office of Response and Restoration. ; United States. National Ocean Service. Marine Debris Division. ; Oregon State University. School of Civil and Construction Engineering. ; ... More +
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Description:Marine debris is a pervasive and escalating environmental problem that poses health risks to both wildlife and humans, as well as degradation to our oceans and coasts. Detection and categorization of shoreline debris are currently conducted through field surveys that entail walking shoreline transects. Uncrewed aircraft systems (UAS), machine learning (ML), and polarimetric imaging (PI) are three rapidly emerging technologies with the capability to dramatically enhance marine debris shoreline surveys. This report presents findings and recommendations based on a NOAA Uncrewed Systems Research Transition Office–funded project conducted collaboratively by NOAA’s National Centers for Coastal Ocean Science (NCCOS), the NOAA Marine Debris Program (MDP), Oregon State University (OSU), and ORBTL AI. Specific outcomes from the project included: 1) operationally efficient field workflows for collection of true color and polarimetric imagery from UAS; 2) deployable algorithms for automatic marine debris detection from remotely sensed true color imagery; and 3) recommended operating procedures for collecting and processing UAS imagery and communicating the locations, types, and confidence scores of potential detections of marine debris to stakeholders. This report serves two primary purposes. First, it summarizes the project methods, results, and key findings. Second, it provides guidance to stakeholders and project partners on operational use of UAS and ML for marine debris surveys.
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Rights Information:CC0 Public Domain
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Compliance:Submitted
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