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

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Hajo eicken josh jones hyunjin choi druckenmiller andy mahoney

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)


Hajo eicken josh jones hyunjin choi druckenmiller andy mahoney

  • 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


Arctic maritime environmental security

Arctic maritime environmental security


Arctic maritime environmental security strategic vs tactical operational perspectives

Arctic maritime environmental security: Strategic vs. tactical/operational perspectives


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


Satellite coverage ice movement

Satellite coverage & ice movement


Satellite repeat rates

Satellite repeat rates

Coastal radar


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


Hajo eicken josh jones hyunjin choi druckenmiller andy mahoney

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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