A data system for visualizing 4 d atmospheric co 2 models and data
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A Data System for Visualizing 4-D Atmospheric CO 2 Models and Data. Tyler A. Erickson, Ph.D. Research Scientist Adjunct Assistant Professor of Civil & Environmental Engineering Michigan Technological University, Michigan, USA 22 October 2009. Collaborators.

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A data system for visualizing 4 d atmospheric co 2 models and data
A Data System for Visualizing 4-D Atmospheric CO2 Models and Data

Tyler A. Erickson, Ph.D.

Research Scientist

Adjunct Assistant Professor of Civil & Environmental Engineering

Michigan Technological University, Michigan, USA

22 October 2009


Collaborators
Collaborators

Prof. Anna M. MichalakUniversity of MichiganAnn Arbor, Michigan, USA

Carbon Cycle Science Researcher

Prof. John C. LinUniversity of WaterlooWaterloo, Ontario, Canada

STILT Atmospheric Transport Model Creator


Time is important
Time is Important

Geospatial representation of present conditions is fine,but predicting future conditions is really useful and interesting...


Temporal change is everywhere
Temporal Change is Everywhere

Land cover change

Climate Change

Disease Spread

Environmental Change

Economic Change

Photo credit: John McColgan of the Bureau of Land Management, Alaska Fire Service


Spatial temporal data
Spatial-Temporal Data

radio collar(a.k.a. caribou bling)

Location: North Slope of Alaska, USASource: The National Academies

Location: Central CanadaSource: NASA


Problem 1 too few data
Problem #1: Too Few Data!

Collecting data with in-situ sensors is expensive

Even with dense meshesof sensors, processes are severely undersampled

Soddie Meteorological TowerLocation: Niwot Ridge LTER, Colorado, USASource: Tyler Erickson


Solution 1 model it
Solution #1: Model it!

“Give me a modeland data with which run it,and I shall estimate allthe properties of the worldin both space and time.”

- Archimedes of Syracuse(severely paraphrased)


Spatial temporal modeling
Spatial-Temporal Modeling

DATA(x,t) = MODEL(x,t) + ERROR(x,t)

Models should rigorously represent reality, if possible

Errors near each other are often similar(i.e. geostatistics)


Problem 2 too much data
Problem #2: Too Much Data!

Data volumes are overwhelming!

How do you go about exploringthe data in space and time?

Soddie Meterological TowerLocation: Niwot Ridge LTER, Colorado, USASource: Tyler Erickson



Co 2 monitoring
CO2 Monitoring

Source: http://commons.wikimedia.org/wiki/File:Mauna_Loa_Carbon_Dioxide.png


Carbon balance
Carbon Balance

Source: NASA


Atmospheric carbon monitoring
Atmospheric Carbon Monitoring

NOAATall Tower

Adapted from work by: K. Mueller, University of Michigan


By the numbers
By the Numbers...

A Typical Particle Simulation:

500*24 per day, simulated particles

10*24 hours of simulation per particle

6 positions per hour per particle

30 days, total dataset length

TOTAL: ~500 million records per measurement tower


How does this data get reported
How does this data get reported?

Source: Lin, J.C. et al., 2003. JGR (Atmospheres) Figure 7


Another approach
Another Approach

IDEA: Provide model results in user-friendly, standard data formats

OGC KML 2.2 standard


What s under the hood
What's under the Hood?

Virtual Globe

ClientApplication

KML

GeospatialServer

SciPy/NumPy

libkml

pylibkml

DataStorage


Geodjango
GeoDjango

+

=

“A world-class geographic web framework”

  • A geospatial extension of a web framework designedfor publishing on-line newspapers (Django)created by a law student (Justin Bronn)

  • Python-based

  • Leverages GEOS, GDAL, Proj.4, and PostGIS

  • Templates allow for output in various geospatial formats

Image Sources: Wikipedia and Wikimedia Commons


Pylibkml
pylibkml

pylibkml is a Python wrapper for the libkml C++ library

Allows for easy programmatic creation of valid KML documents

http://code.google.com/p/pylibkml/

from pylibkml import Kml

placemark = Kml().create_placemark({

'name' : 'FOSS4G 2009',

'description' : 'In Sydney',

'timestamp' : {'when': '8/22/2009'},

'point' : Kml().create_point({

'extrude' : True,

'altitudemode' : 'relativetoground',

'coordinates' : Kml().create_coordinates(

151.1998,-33.8761),

})

})


Why google earth
Why Google Earth?

Free (for some uses)

Open Source

Easy to Use Interface

Rich Reference Imagery

Wide User Base

Runs on Linux

Full KML Implementation

Talks to External Servers

Source: http://www.flickr.com/photos/gillpoole/


Google s kml in research competition
Google's KML in Research Competition

Earlier this year Google hosted a contest onusing KML to communicate scientific research

Judging criteria:

Usability

Educational value

Visual/interactive appeal

Efficiency

Attribution

KML output from this data system was selected as one of 5 professional winners


Tall tower measurements
Tall Tower Measurements

NOAATall Tower

Adapted from work by: K. Mueller, University of Michigan


Sensitivity to surface flux
Sensitivity to Surface Flux

NOAATall Tower

Adapted from work by: K. Mueller, University of Michigan



What else goes under the hood
What Else Goes Under The Hood?

ASCII Grid

netCDF

GeoTiff

ESRIShapefile

KML

CONSUME

(Fuel Consumption &

Emissions Model)

SciPy/NumPy

libkml

WKT Raster



Wkt raster
WKT Raster

Adds raster-vector spatial analysis to PostGIS

http://trac.osgeo.org/postgis/wiki/WKTRaster

2 2 2 2 2 2 2 2 2 2 2 2 2 2

2 2 2 2 2 2 2 2 2 2 2 2 2 2

1 1 1 1 1 1 1 1 2 2 2 2 2 2

0 0 1

2 2 2 2 0 0

1 1 0 0

1 1 1 1 1 1 1 1 2 2 2 2 2 2

2 2 2 2 2 0

0 1 1

1 1 1 0

1 1 1 1 1 1 1 1 2 2 2 2 2 2

2 2 2 2 2 2

1 1 1

1 1 1 1

1 1 1 1 1 1 1 1 2 2 2 2 2 2

2 2 2 2 2 2

1 1 1

1 1 1 1

1 1 1 1 1 1 1 1 2 2 2 2 2 2

2 2 2 2 2 2

1 1 1 1

1 1 1

1 1 1 1 1 1 1 1 2 2 2 2 2 2

1 1 1

2 2 2 2 2 2

1 1 1 1

1 1 1 1 1 1 1 1 2 2 2 2 2 2

2 2 2 2 2 2

1 1 1

1 1 1 1

1 1 1 1 1 1 1 1 2 2 2 2 2 2

0 1 1

2 2 2 2 2 0

1 1 1 0

1 1 1 1 1 1 1 1 2 2 2 2 2 2

2 2 2 2 0 0

0 0 1

1 1 0 0

1 1 1 1 1 1 1 1 2 2 2 2 2 2

1 1 1 1 1 1 1 1 2 2 2 2 2 2

2 2 2 2 2 2 2 2 2 2 2 2 2 2

Example:Intersection(geometry,raster) → raster

and

=

b

a

Source: WKTSpecifications1.0.ppt (Pierre Racine)


Next steps
Next Steps

Atmospheric Carbon Application: move from prototypeto a web-accessible tool for researchers

Allow users to upload data from atmospheric transport model runs

Improve KML styling

Create visualizations of additional high-dimensional datasets


Questions
Questions?

Tyler A. Erickson, Ph.D.

Email: tyler.erickson@mtu.edu

Web: http://people.mtri.org/tyler+erickson

Twitter: tylerickson

Code: http://bitbucket.org/tylere/geodjango-stilt/