Tracking the Great Whales:

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Tracking the Great Whales

• An Arc Marine Case Study

Brett K. Lord-Castillo1, Tomas Follett2, Andrew
Weiss2, Bruce R. Mate2, and Dawn J. Wright1 27th
Annual ESRI User Conference June 21, 2007 San
Diego, California 1 Department of Geosciences,
Oregon State University 2 Marine Mammal
Institute, Oregon State University
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Individual based information

• Satellite telemetry
• Day length-SST
• Fastlock GPS
• Pop up archival
• Genotyping

Mate, 1989 Mate et al. 2005 Shaffer et al.
2005 Block 2005 Block et al. 2005
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ARGOS Telemetry
NOAA Polar-orbiting Operational Environmental
Satellite
Adapted from Liaubet and Malardé, 2003
Austin, McMillan,and Bowen 2003
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Mate, Mesecar, and Lagerquist 2007
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Research Questions

• How can a geographic information system enhance
  the research advantages of satellite telemetry?
• How can the Arc Marine data model be applied to
  this primary research question?

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Specifications

• Retain all raw data, with relationships to
  derived results and processing choices.
• Archive data acquisition quality and other
  auxiliary information.
• Store operational information linked to the
  appropriate measured data.
• Create an analysis audit trail, but do not save
  analytic snapshots.
• Record hardware details are stored for future
  reference (tag components, manufacturers, raw
  data bit structure, etc.).

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Gathering your materials

• Documentation
• Arc Marine Schema
• Microsoft Visio
• UML to XMI Export tools
• Arc Marine Tutorial
• Visual Studio
• Python (2.4 or higher) IDE
• Python libraries

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http//dusk2.geo.orst.edu/djl/arcgis/diag.html
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Most important objects

• Whale locations
• Tags
• Whales

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LocationSeriesA sequence of point data
Marine ObjectsInstantaneousPoint
(GeometryTypeesriGeometryPoint) -TimeValue
esriFieldTypeDate -ZValue esriFieldTypeDouble -Su
rveyID esriFieldTypeInteger -SeriesID
esriFieldTypeInteger ltSubtypeFieldgt-PointType
esriFieldTypeInteger 1
Subtype
LocationSeries PointType esriFieldTypeInteger 4
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Inheritance

• ESRI ClassesObject
• OBJECTID
• ESRI ClassesFeature
• Shape
• Marine ObjectsMarineFeature
• -FeatureID
• -FeatureCode
• Marine ObjectsMeasurementPoint
• -CruiseID

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Is an animal just a series of locations?
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Telemetry Advantages

• Responsiveness
• Data relationships
• Autonomous profiling
• Continuous coverage

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Animal A type of vehicle
Marine ObjectsVehicle -VehicleID
esriFieldTypeInteger -Name esriFieldTypeString -C
ategory esriFieldTypeString
Child Class
Marine ObjectsAnimal -Sex Sex 3 -Genotype
esriFieldTypeString -SpeciesID
esriFieldTypeInteger -Social Social 1
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Specifications

• Archive data acquisition quality and other
  auxiliary information.
• Retain all raw data, with relationships to
  derived results and processing choices.
• Store operational information linked to the
  appropriate measured data.
• Record hardware details for future reference (tag
  components, manufacturers, raw data bit
  structure, etc.).
• Create an analysis audit trail, but do not save
  analytic snapshots.

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Other changes

• Which other core classes to use?
• What core classes to remove?

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Snowflake Schema
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Solving Multiple Point Types
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And more subdimensions
ObservationInfo Field observation (links to photograph files)
DerivedInfo Interpolated or derived location
GPSInfo FastlockGPS
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Other sheets

• Record hardware details for future reference (tag
  components, manufacturers, raw data bit
  structure, etc.).
• Create an analysis audit trail, but do not save
  analytic snapshots.

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Development considerations

• Platform
• Language(s)
• Programming to the core objects

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Python Recommendations

• WxPython (GUI)
• IronPython (.NET Implementation)
• Numpy (Statistical)
• Matplotlib (Matlab functions)
• Makepy/pywin32 (COM access)
• GeoEco (MGET Package)
• Use the community!

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References

• Austin, D., J. I. McMillan, and W. D. Bowen.
  2003. A three-stage algorithm for filtering
  erroneous ARGOS satellite locations. Marine
  Mammal Science. 19 371-383.
• Block, B. A. 2005. Physiological ecology in the
  21st century Advancements in biologging science.
  Integrative and Comparative Biology 45 305-320.
• Block, B. A., S. L. J. Teo, A. Walli, A.
  Boustany, M. J. W. Stokesbury, C. J. Farwell, K.
  C. Weng, H. Dewar, and T. D. Williams. 2005.
  Electronic tagging and population structure of
  Atlantic bluefin tuna. Nature 434 1121-1127.
• Boehlert, G. W., D. P. Costa, D. E. Crocker, P.
  Green, T. OBrien, S. Levitus, and B. J. Le
  Boeuf. 2001. Autonomous pinnipeds environmental
  samplers Using instrumented animals as
  oceanographic data collectors. Journal of
  Atmospheric and Oceanic Technology 18 1882-1893.
• Lagerquist, B.A., K.M. Stafford, and B.R. Mate.
  2000. Dive characteristics of satellite-monitored
  blue whales (Balaenoptera musculus) off the
  Central California Coast. Marine Mammal Science.
  16(2) 375-391.

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References

• Liaubet, R. and J. Malardé. 2003. ARGOS Location
  Calculation. Proceedings of the ARGOS Animal
  Tracking Sympsium. Annapolis, MD.
• Mate, B.R. 1989. Watching habits and habitats
  from Earth satellites. Oceanus. 3214-18.
• Mate, B.R., B.A. Lagerquist, M. Winsor, J.
  Geraci, and J.H. Prescott. 2005. Movements and
  dive habits of a satellite-monitored longfinned
  pilot whale (Globicephala melas) in the Northwest
  Atlantic. Marine Mammal Science, 21(1) 136144.
• Mate, B. R., R. Mesecar, B. Lagerquist. 2007. The
  evolution of satellite-monitored radio tags for
  large whales One laboratorys experience. Deep
  Sea Research Part II Topical Studies in
  Oceanography, 54(3-4) 224-247.
• McLeod, K. L., J. Lubchenco, S. R. Palumbi, and
  A. A. Rosenberg. 2005. Scientific Consensus
  Statement on Marine Ecosystem-Based Management.
  Communication Partnership for Science and the
  Sea. Online. Available http//compassonline.org/?
  qEBM, 04/10/2007.

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References

• Rodman, L. C. and J. Jackson. 2006. "Creating
  Standalone Spatially-Enabled Python Applications
  Using the ArcGIS Geoprocessor," Proceedings of
  the Twenty-Sixth Annual ESRI User Conference, San
  Diego, CA, August 2006.
• Sherman, L. 2006. Tracking the Great Whales.
  Terra. 1(2)2-8.
• Shaffer, S. A., T. Yann, J. A. Awkerman, R. W.
  Henry, S. L. H. Teo, D. J. Anderson, D. A. Croll,
  B. A. Block, and D. P. Costa. 2005. Comparison of
  light and SST-based geolocation with satellite
  telemetry in free-ranging albatrosses. Marine
  Biology 147 833-843.
• Tremblay, Y., S. A. Shaffer, S. L. Fowler, C. E.
  Kuhn, B. I. McDonald, M. J. Weise, C. Bost, H.
  Weimerskirch, D. E. Crocker, M. E. Goebel, and D.
  P. Costa. 2006. Interpolation of animal tracking
  data in a fluid environment. The Journal of
  Experimental Biology. 209 128-140.
• Wright, D.J., Blongewicz, M.J., Halpin, P.N., and
  Breman, J., "Arc Marine GIS for a Blue Planet,"
  Redlands, CA ESRI Press, 202 pp., 2007.

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Contact Information

• Brett Lord-Castillo
• Department of Geosciences
• Oregon State University
• Corvallis, OR 97331-5506
• lordcasb_at_science.oregonstate.edu
• Related web site
• http//oregonstate.edu/lordcasb/p1569.htm
• Financial support provided by the Education and
  Research Opportunities in Applying GIS and Remote
  Sensing in Coastal Resource Management program of
  the National Oceanic and Atmospheric
  Administration.
• (NOAA Grant NA04NOS4730181)