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Integrated coastal radar system for Arctic waters: Monitoring of maritime coastal traffic and support of disaster response and mitigation. Hajo Eicken, Josh Jones, Hyunjin Choi Druckenmiller, Andy Mahoney Geophysical Institute, University of Alaska Fairbanks, [email protected]

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slide1
Integrated coastal radar system for Arctic waters: Monitoring of maritime coastal traffic and support of disaster response and mitigation

Hajo Eicken, Josh Jones, Hyunjin Choi Druckenmiller, Andy Mahoney

Geophysical Institute, University of Alaska Fairbanks, [email protected]

  • Arctic maritime environmental security, critical data & their acquisition
  • Integrated coastal radar system
  • Decision-support through automated motion and event tracking
  • Integrating the radar with response efforts & other systems
  • Next steps

NSIDC.org

project status 10 jan 2011
Project status, 10 Jan 2011
  • Algorithms for automated extraction of hazard information developed & validated
  • Paper to technical journal to be submitted in Jan 2011
  • Programs for automated analysis and decision-support undergoing testing, completed by summer 2011
  • Radar design study completed, components for complete system ordered, to be installed spring/summer 2011
  • Review & framework for environmental security in ice-covered waters (strategy to tactics)
  • Paper to be submitted to MTS Special CIMES Issue
  • Dialog with USCG and other DHS-CoE continues (seminar series on Defining Risk in Offshore Resource Development, informal exchange)
slide3
The Arctic Ocean is opening up: Ice retreat, increased economic activity, growing maritime traffic
  • Environmental security: Response & mitigation of hazards & disasters in extreme environments (e.g., oil spill in ice)
  • Tracking & forecasting at relevant space & time scales: Address key gaps (sub-satellite scale) through integrated coastal observing system

National Snow and Ice Data Center

maritime environmental security in the us arctic
Maritime environmental security in the US Arctic

Map: A. Gaylord, Nunatech based on AK-DNR & BOEMRE & NSIDC data

improving cold regions maritime domain awareness through an integrated coastal observing system
Improving cold-regions maritime domain awareness through an integrated coastal observing system
  • Remote sensing* (km-scale): Coastal environments & infrastructure, ice hazards
  • Coastal radar (sub-km scale): Vessel & ice tracking, ice dynamics & potential disaster response
  • Aerial surveys, ice & sub-ice sensor systems*
  • Local knowledge*: Potentially important role for disaster response
  • Integration of data streams, GIS-based decision support systems

* Leveraged through integration & assimilation of existing ocean observing system resources (AOOS.org) and partnering with Arctic Observing Network

radar specifications and design
Radar specifications and design

Current system:

  • Furuno X-band FR7112, 10kW, 1.6m open array, 22m a.s.l.
  • Xenex 2000 A/D converter/controller (4-bit dynamic range)
  • Problems: Icing & wind drag (custom-built de-icer), range 10-20 km, low effective dynamic range
radar specifications and design1
Radar specifications and design

Current system:

  • Furuno X-band FR7112, 10kW, 1.6m open array, 22m a.s.l.
  • Xenex 2000 A/D converter/controller (4-bit dynamic range)
  • Problems: Icing & wind drag (custom-built de-icer), range 10-20 km, low effective dynamic range
considerations for improved system
Considerations for improved system

Ordered system:

  • Furuno X-band FAR2127, 25kW, 2.4m open array, 22m a.s.l.; heavy-duty commercial de-icing unit
  • Digital data stream: Russell Technologies Signal Processor
  • Challenges: Furuno’s migration to all-digital systems; custom-install of de-icing system (delivery now at May 2011)
decision support automated detection of ice motion hazard events surface vessels
Decision-support: Automated detection of ice motion, hazard events & surface vessels

Goals:

  • Analysis of radar image sequences to extract quantitative information about velocity fields and trajectories of individual features & ice pack
  • Automated detection of hazardous events (break-outs, ice shoves, etc.)
  • Automated delineation of stable/unstable zones

Collaboration with University of Delaware, Dept. of Computer & Information Sciences

Dr. Chandra Kambhamettu, Director – Video/Image Modeling & Synthesis Lab ([email protected])

Rohith MV, Ph.D. candidate ([email protected])

decision support automated detection of ice motion hazard events surface vessels1
Decision-support: Automated detection of ice motion, hazard events & surface vessels

Challenges:

  • Complex occlusions
  • Low signal-to-noise ratio
  • Signal strength highly sensitive to position & orientation of reflectors
  • Inhomogeneous distribution of features
  • Non-rigid body motion
motion field feature tracking
Motion Field: Feature tracking
  • Sparse motion fields: Feature tracking (Lagrangian velocity vectors)
  • Lucas-Kanade tracker (edge/point detection based on eigenvalues of time-shifted radar return signal)
  • Movement
  • of points
  • linearized
  • Least-sq.
  • solution
motion field feature tracking1
Motion Field: Feature tracking
  • Sparse motion fields: Feature tracking (Lagrangian velocity vectors)
  • Lucas-Kanade tracker (edge/point detection based on eigenvalues of time-shifted radar return signal)
  • Movement
  • of points
  • linearized
  • Least-sq.
  • solution
motion field feature tracking2
Motion Field: Feature tracking
  • Sparse motion fields: Feature tracking (Lagrangian velocity vectors)
  • Lucas-Kanade tracker (edge/point detection based on eigenvalues of time-shifted radar return signal)
  • Movement
  • of points
  • linearized
  • Least-sq.
  • solution
motion analysis stable regions
Motion Analysis: Stable Regions
  • Velocity potential field (hourly-daily mean) defines contours between stationary and moving ice
  • Contour refined from smoothness & potential constraints
  • Compares well with manual & SAR data, more accurate due to higher sampling rate
motion analysis break out detection
Motion Analysis: Break-out detection
  • Early, automated identification of break-outs (hazard mitigation)
  • Hidden Markov Model approach: Statistics of radar backscatter used to estimate state & trajectory of system (velocity & backscatter variations associated w/ break-out)
motion analysis break out detection1
Motion Analysis: Break-out detection
  • Early, automated identification of break-outs (hazard mitigation)
  • Hidden Markov Model approach: Statistics of radar backscatter used to estimate state & trajectory of system (velocity & backscatter variations associated w/ break-out)
motion analysis break out detection2
Motion Analysis: Break-out detection
  • Early, automated identification of break-outs (hazard mitigation)
  • Hidden Markov Model approach: Statistics of radar backscatter used to estimate state & trajectory of system (velocity & backscatter variations associated w/ break-out)
motion analysis detecting tracking anomalous motion
Motion Analysis: Detecting & Tracking Anomalous Motion
  • Automated tracking of individual ice floes
  • Detection of anomalous motion (non-linear acceleration/deceleration), e.g., grounding ice
integration with observatory components
Linkage to ice based wire-less sealevel & temperature sensors

Integration with remote sensing data & local trail information

Use as decision-support tool

Integration with observatory components

2008 Barrow Ice Trails -

Map produced by

Matthew Druckenmiller and collaborators

slide24

Jacob Adams Crew Trail, 2008

2008 Barrow Ice Trails -

Map produced by

Matthew Druckenmiller

Photo: Craig George

safety on the ice i upiaq knowledge environmental observing systems safety engineering
Safety on the ice: Iñupiaq knowledge, environmental observing systems & safety engineering
  • Local expertise: specific role of local, indigenous knowledge (LIK) in regulation and planning still being discussed
  • Value & primacy of LIK with respect to safety mostly undisputed
  • Example of Escape, Evacuation, Rescue (EER)

Based on ISO 19906 - DRAFT

integration into ir needs next steps
Integration into IR: Needs & next steps
  • Meet needs of USCG & response teams
  • Integration with remote power module & ocean radar
  • Integration with local expertise
  • Arctic maritime environmental security: Training & discourse w/ USCG, industry & stake-holders – Nx2020 Risk Seminar Series, further continuing education offerings?

Based on Alaska Clean Seas, Tech. Manual & FEMA Handbook

  • Building capacity: Link with DHS Disasters, Coastal Infrastructure & Emergency Management (DIEM) Center at UNC
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