Polar Synthesis: Analytical Components Mapping and Visualization Team

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Polar SynthesisAnalytical ComponentsMapping
and Visualization Team

• Ben Best
• Patrick Halpin
• Jason Roberts
• Ei Fujioka
• Ben Donnely
• Jesse Cleary

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Polar Synthesis Macroscope Team Duke University
NC 26-28 Oct 2008
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Partners Other Visualization Experts

• Xianhua Liu / David Kidd (NESCent National
  Evolutionary Synthesis Center)

GeoPhyloBuilder
Reference Kidd, D. M. and M. G. Ritchie (2006).
"Phylogeographic information systems Putting the
geography into phylogeography." Journal of
Biogeography 33 1851-1865.
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Google Earths Oceans - Octopuses
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Antarctica exports oxygen-rich cold bottom water
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Geo/Phylo/Hab Workflow
3Dgeophylo
extent
points
Get Observations
GeoPhyloBuilder
taxa
phylogeny
Calculate Species Richness
diversity grid
Fit Model
Get Environment
variable
environment grid(s)
Predict Model
model
prediction
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Oceanographic Data Online

• Pointers CoMLmaps.org gt HowTo gt Layers and
  Resources

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OceanWatch LAS
http//las.pfeg.noaa.gov/oceanWatch/oceanwatch_saf
ari.php

• Formats
• txt
• netcdf
• kml
• OPeNDAP

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OPeNDAP

• Open-source Project for a Network Data Access
  Protocol
• OPeNDAP form (.html .dds .das)
  http//oceanwatch.pfeg.noaa.gov/thredds/dodsC/sate
  llite/MB/chla/8day.html
• MATLAB commandloaddods('http//las.pfeg.noaa.gov
  /OceanWatch-FDS/LAS/MB/chla8day?MBCHLA10331033
  003218337945584760')
• Python pydap

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Modeling habitat
Probability of occurrence predicted from
environmental covariates
Presence/absence observations
Multivariate statistical model
Sampled environmental data
Binary classification
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What is MGET?

• A collection of geoprocessing tools for marine
  ecology
• Oceanographic data management and analysis
• Habitat modeling, connectivity modeling,
  statistics
• Highly modular designed to be used in many
  scenarios
• Emphasis on batch processing and interoperability
• Free, open source software
• Written in Python, R, MATLAB, and C
• Minimum requirements Win XP, Python 2.4
• ArcGIS 9.1 or later needed for some tools
• ArcGIS and Windows are only non-free requirements

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MGET interface in ArcGIS

• Drill into the toolbox to find the tools
• Double-click tools to execute directly, or drag
  to geoprocessing models to create a workflow

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Interoperability
MGET tools are really just Python functions
with input and output parameters
def DoSomething(input1, input2, output1)
Python programmers can call MGET functions
directly. To facilitate interoperability, MGET
exposes these functions as COM Automation objects
and ArcGIS tools.
COM-capable program C / C / C, Visual
Basic, R, MATLAB, Java, etc.
ArcGIS geoprocessing tool
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Integration
The Python functions can invoke C, MATLAB, R,
ArcGIS, and COM classes.
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Typical observation data
Fishery catch and bycatch records
Surveys
IATTC Olive Ridley Encounters 1990-2005
Argos satellite tracks
Figure courtesy of Scott Eckert
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Typical workflow
MGET includes tools that assist with all of these
steps
Import species observations into GIS
Obtain oceanographic datasets
Prepare oceanographic data for use
Explore maps of oceano. and observations
Create derived oceanographic datasets
Analyze/model species habitat or behavior
Sample oceanographic data
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Typical workflow
Import species observations into GIS
Obtain oceanographic datasets
Prepare oceanographic data for use
Explore maps of oceano. and observations
Create derived oceanographic datasets
Analyze/model species habitat or behavior
Sample oceanographic data
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Species observations

• Skipping the details of this step to save time
• Ultimately you must produce a point shapefile or
  feature class that shows locations where the
  species was present and where it was absent

Species presence field 1 present, 0 absent
Date field records date of observation
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Typical habitat modeling workflow
Import species observations into GIS
Download oceanographic datasets
Prepare oceanographic data for use
Explore maps of oceano. and observations
Create derived oceanographic datasets
Analyze/model species habitat or behavior
Sample oceanographic data
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Options for obtaining data

• Download files from data providers using FTP
• Nearly all data products are available with FTP
• Powerful, free downloaders exist (e.g. SmartFTP)
• But must often convert files to ArcGIS-compatible
  formats
• Download using MGET or other tool (e.g. NOAA EDC)
• The tool hides details of download, using FTP,
  OPeNDAP or other protocols, and writes
  ArcGIS-compatible formats
• Not many such tools exist
• Order files on CD-ROM or DVD-ROM
• Use this if your Internet connection is slow

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Tools for specific products
Downloads sea surface height data from
http//opendap.aviso.oceanobs.com/thredds
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Example SSH and currents data with turtle track
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Typical workflow
Import species observations into GIS
Obtain oceanographic datasets
Prepare oceanographic data for use
Explore maps of oceano. and observations
Create derived oceanographic datasets
Analyze/model species habitat or behavior
Sample oceanographic data
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Preparing oceanography for use

• Most oceanographic datasets are not immediately
  usable by ArcGIS
• Common preprocessing steps include
• Converting to an ArcGIS-supported format
• Projecting to a desired projection
• Clipping to region of interest
• Performing basic calculations (via map algebra)
• E.g. converting integers given by the original
  data provider to floats that represent the real
  values
• Building pyramids

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Converting data
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Sea surface temperature
NOAA CoastWatch AVHRR
GOES 10/12 from PO.DAAC
NOAA NODC 4km AVHRR Pathfinder v5
Also MODIS Aqua and Terra, GOES 9
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Sea surface chlorophyll density
SeaWiFS from the NASA GSFC OceanColor Group
Also MODIS Aqua and combined MODIS/SeaWiFS
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QuikSCAT ocean winds from PO.DAAC
28-Aug-2005
Also BYU QuikSCAT Sigma-0 (approximates sea
surface rougness)
Katrina
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Global bathymetries

• ETOPO2
• GEBCO
• S2004

Map shows S2004 clipped to eastern Pacific ocean
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Typical workflow
Import species observations into GIS
Obtain oceanographic datasets
Prepare oceanographic data for use
Explore maps of oceano. and observations
Create derived oceanographic datasets
Analyze/model species habitat or behavior
Sample oceanographic data
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Identifying SST fronts
Cayula and Cornillion (1992) edge detection
algorithm
Step 1 Histogram analysis
ArcGIS model
Bimodal
Optimal break 27.0 C
Frequency
Temperature
Example output
Step 2 Spatial cohesion test
Mexico
Strong cohesion ? front present
Weak cohesion ? no front
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Identifying geostrophic eddies
Available in MGET 0.8
SSH anomaly
Example output
Negative W at eddy core
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Typical workflow
Import species observations into GIS
Obtain oceanographic datasets
Prepare oceanographic data for use
Explore maps of oceano. and observations
Create derived oceanographic datasets
Analyze/model species habitat or behavior
Sample oceanographic data
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Sampling raster data

• Sampling is the procedure of overlaying points
  over a map and storing the maps value as an
  attribute of each point.

Chlorophyll-a Density
Chl attribute of the points filled with values
from the map
MGET has sampling tools for various scenarios
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Typical workflow
Import species observations into GIS
Obtain oceanographic datasets
Prepare oceanographic data for use
Explore maps of oceano. and observations
Create derived oceanographic datasets
Analyze/model species habitat with statistics
Sample oceanographic data
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MGET statistics tools

• Lots of tools, many more planned
• Built from Ben Bests ArcRStats / HabMod projects
• Tools require the R statistics program to be
  installed on your computer

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Exploratory analysis
Scatterplot Matrix tool
Density Histogram tool
Turtle present
Density
Turtle absent
Distance to nesting beach (m)
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Fitting statistical models
ROC plots
Term plots
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Predicting habitat maps from the model
Binary habitat (cutoff 0.025)
Input 3 Rasters for predictor variables
Predict GAM tool
Input 2 Cutoff value
Input 1 The fitted model
Bayesian probability that predicted presence
0.025
Predicted species presence
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Analyzing coral reef connectivity
Ocean currents data
Larval density time series rasters
Coral reef ID and cover maps
Tool downloads data for the region and dates you
specify
Edge list feature class representing dispersal
network
Original research by Eric A. Treml
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Available in MGET 0.7 alpha 10
Calculate Species Diversity
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More Information
Census of Marine Life Map Vis www.comlmaps.org i
nfo_at_comlmaps.org Marine Geospatial Ecology
Tools code.env.duke.edu/projects/mget