thoughts on algorthmic approaches to reveal marine geomorphology as a proxy for habitat presentation...
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Thoughts on Algorthmic Approaches to Reveal Marine Geomorphology as a Proxy for
Habitat
Thoughts on Algorthmic Approaches to Reveal Marine Geomorphology as a Proxy for
Habitat
Presentation IT13B-012010 Ocean Sciences Meeting
Portland, OR
Presentation IT13B-012010 Ocean Sciences Meeting
Portland, OR
Dawn WrightDept. of Geosciences, Oregon State University
Will HeymanDepartment of Geography, Texas A&M University
Dawn WrightDept. of Geosciences, Oregon State University
Will HeymanDepartment of Geography, Texas A&M University
Primary Data Acquisition: Visual
Primary Data Acquisition: Visual
Hawaii Undersea Research Lab
NOAA CRED
Primary Data Acquisition: “Shallow”
Primary Data Acquisition: “Shallow”
Multibeam sonar, 200 m and shallower Ikonos, shoreline to 15 m
Portable, pole-mounted EM3000
Ikonos satellite(Image from SatMagazine)
R/V Acoustic Habitat Investigator w/ RESON 8101, NOAA
Primary Data Acquisition: “Deep”
Primary Data Acquisition: “Deep”
Multibeam sonar, regional scale,200 m and deeper
Image from Lost City Expedition (2003)
Algorithmic ApproachesAlgorithmic Approaches
Almost always quantitative, usually automatic or semi-automatic…
Allow the user to refine the classification at certain stages in the process based on visual
observation…
Subject to artifacts, but more repeatable, less expensive, and with resolution limited only by
the source data…
Algorithmic ApproachesAlgorithmic Approaches
What are the major tried and true algorithmic approaches for producing classifications?
What should be the habitat classification categories?
…for a particular region (shallow vs. deep) …sensor (satellite, acoustics at different
resolutions and in the subsurface)?
Is it feasible to move toward a standardization of algorithmic seafloor
classification approaches?
Broad scale
Fine scale
Shape: Bathymetric Position Index
Shape: Bathymetric Position Index
(from TPI, Jones et al., 2000; Weiss, 2001; Iampietro &
Kvitek, 2002)
Emily Lundblad, OSU Thesis
Zone and Structure Flow Chart
Zone and Structure Flow Chart
Structure Classification Decision Tree
Emily Lundblad, OrSt M.S. Thesis
http://dusk.geo.orst.edu/djl/samoa
http://dusk.geo.orst.edu/djl/samoa
Benthic Terrain Modeler
Ecosystem-Based Mgmt Tools Network
www.ebmtools.org
Ecosystem-Based Mgmt Tools Network
www.ebmtools.org
Roughness: RugosityRoughness: Rugosity Measure of how rough or bumpy a surface is, how
convoluted and complex Ratio of surface area to planar area
Graphics courtesy of Jeff Jenness, Jenness Enterprises, and Pat Iampietro, CSU-MB
Surface area based onelevations of 8 neighbors
3D view of grid on the left Center pts of 9 cells connectedTo make 8 triangles
Portions of 8 triangles overlapping center cellused for surface area
Benthic ComplexityBenthic Complexity
Ardron and Wallace, in Wright and Scholz, Place Matters: Geospatial Tools for Marine Science… 2005
Benthic ComplexityBenthic Complexity
Ardron and Wallace, in Wright and Scholz, Place Matters: Geospatial Tools for Marine Science… 2005
Ecological Habitat Modeling GLM, GAM, classification/regression trees,
etc.
Ecological Habitat Modeling GLM, GAM, classification/regression trees,
etc.
Iampietro, Kvitek et al., Marine Geodesy, 2008
Bayesian ApproachesBayesian Approaches
Simons and Snellen, Applied Acoustics, 2009
Classification Schemes: CMECS
Coastal and Marine Ecological Classification Standard
Classification Schemes: CMECS
Coastal and Marine Ecological Classification Standard
Madden et al., NatureServe, NOAA
EUNISeunis.eea.europa.net
EUNISeunis.eea.europa.net
EEA/European Environmental Information Observation Network
EUSeaMapEUNIS classification is a common language for habitat. Propose
modifications to EUNIS where appropriate (Baltic or Med)
EUSeaMapEUNIS classification is a common language for habitat. Propose
modifications to EUNIS where appropriate (Baltic or Med)
Natalie Coltman, JNCC, UK, www.jncc.gov.uk/EUSeaMap
EUSeaMap MethodologyEUSeaMap Methodology
Natalie Coltman, JNCC, UK, www.jncc.gov.uk/EUSeaMap
O2/POC/Chl
Ice cover
Geoscience AustraliaGeoscience Australia
Heap, Nichol et al., AAG, 2008
geohab.org
marinecoastalgis.netmarinecoastalgis.net
How best to move forward with marine habitat mapping & modelling?
Stay abreast of more than one community (e.g., GeoHab, EUSeaMap, etc.)
Entrain more than one specialist(marine ecologists, geologists, physical oceanographers,
GISers)
Decision tree or matrix depending on scale, species (e.g., CMECS, EUNIS)
Standard classification dictionaries, generic shallow-water dataset for all, w/testing tools
(interdisciplinary technical working groups)
“Semantic interoperability” of classification?
What should be on the resulting maps?
Concluding ThoughtsConcluding Thoughts
