Transcript LEEASP: A Linked Environment of Coordinated Multiple Views

Embedding and Extending GIS
for Exploratory Analysis
of Large-Scale Species Distribution Data
Jianting Zhang, Dept. of Computer Science
The City College of the City University of New York
Le Gruenwald, School of Computer Science
The University of Oklahoma
Outline
•Background and Motivation
•Modeling/Representation for Data Integration
•LEEASP: The Prototype System for Visual
Exploration
•Related Works and Discussions
NEON Infrastructure Overview
William K. Michener
Deborah Estrin, http://www.projectscience.org/workshop7/talks/estrin.pdf
Terrestrial Arrays
Aquatic Arrays
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Background
• Species distribution analysis
– Quantifying the relationship between species distributions and the
environment
– Central to ecology/biogeography theories and conservation practices
– Incorporating climate change and human impact scenarios
• Enabling Technologies
– GPS technology in modern field survey
– Geo-referring technology in transforming descriptive museum records
to geographical coordinates
– Internet and the cyber-infrastructure for distributed data
access/integration
– Spatial databases and GIS for data management and analysis
Background
1. Guisan, A. and N. E. Zimmermann (2000). Predictive habitat distribution models in ecology.
Ecological Modelling 135(2-3): 147-186.
2. Waide, R. B., M. R. Willig, et al. (1999). The relationship between productivity and species
richness. Annual Review of Ecology and Systematics, 30, pp. 257-300.
3. Stockwell, D. R. B. and D. P. Peters (1999). The GARP modelling system: problems and
solutions to automated spatial prediction. International Journal of Geographic Information
Systems 13(2): 143-158.
4. Hirzel, A. H., Hausser, J., Chessel, D.,Perrin, N., 2002. Ecological-niche factor analysis:
How to compute habitat-suitability maps without absence data? Ecology, 83(7), 2027-2036.
Total
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2002
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1
751
143
166
166
100
85
46
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9
2
383
22
56
58
64
47
52
41
29
14
3
240
35
60
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22
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10
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1
4
123
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37
25
12
9
7
1999
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Background
The availability of compiled digital datasets
•USDA PLANT Database
•89759 plant species in 3141 US counties
WWF Wildfinder database:
•29112 species, 4815 genus, 445 families, 69 orders in 4 classes
(amphibians, reptiles, birds, and mammals) among the world’s 845
ecoregions
•350045 species-ecoregion records
•USGS
•Little tree species distribution data: 679
•NatureServe species distribution maps
•5743 amphibians species worldwide
•4273 birds species of the western hemisphere
•1786 mammals species of the western hemisphere
Background
Community – Ecosystem – Biome – Biosphere
Species
Taxonomic (Linnaean ranks)
Kingdom
Phylum
Class
Order
Family
Genus
Species
SubSpecies
Phylogenentic
Environment
Area
Environmental Gradient
WaterEnergy
Latitude
Altitude
Productivity
Phylogeography
Background
Taxonomic
Distribution
Correlation
Configuration
Geographical
Environmental
Distribution
Motivations
•We aim at developing an integrated data model/representation
that seamlessly links geographical, taxonomic and environmental
data.
•We utilize state-of-the-art visualization techniques to build a
prototype to allow visual explorations between and among
relevant data:
•Embedding GIS for visualizing geographical maps
•Incorporating Graph/tree visualization for taxonomic trees and ecoregion
hierarchies
•Using Sortable Table, Parallel Coordinate Plot (PCP) and other
techniques for multivariate environmental data
Data Modeling/Representation
Using Traditional GIS Data Model
GIS Data Model
Layer 1
Species 1
Layer 2
Species 2
Layer n
Species n
Data Modeling/Representation
Problems
•The relationships among the geographical units in different layers
are not a part of the traditional GIS data models.
•To use the layer-based GIS data model for managing multiple
species distribution data, the geographical and the environmental
data need to be joined for each layer, either permanently or
dynamically.
•While it is possible to arrange the species layers into groups in
modern GIS to mimic the taxonomic hierarchy, it is difficult to
identify/visualize query results that involve multiple layers back in
the layer list.
Data Modeling/Representation
The Integrated Data Model
GIS Data Model
Data Modeling/Representation
•Object-Relational Framework
•Taxonomic data is now first-class citizen
From/To
Environmental
Geographical
Taxonomic
Environmental
Geographical Taxonomic
Relational
(RDBMS)
GIS
Data Modeling/Representation
Supported Operations
Environmental
Taxonomic
E->G(+T)
T->G(+E)
G->T
Geographical
Operations need to
be formally defined!
G->E
LEEASP: Prototype
http://www-cs.ccny.cuny.edu/~jzhang/tech/LEEASPV10.zip
Geographical View
Taxonomic View
Ecoregion View
Environmental View
Linked
Environment
for
Exploratory
Analysis of
Large-Scale
Species
Distribution
Data
LEEASP: Prototype
Example Data
•USGS NA Little dataset: 679 tree species, 90 Megabytes in
ESRI Shapefile format
•WorldClim 10 minutes altitude and 18 bioclimate variables
•EPA NA Ecoregion data: up to Level III
•Resolution: 0.5*0.5 Deg
•11777 valid cells
LEEASP: Prototype
Geographical View
On-screen digitizing to specify
environmental gradients
•Embedding GIS
•Based on open source JUMP GIS from Vividsolutions
•Designed to present the distribution information
•Follows “Focus+Context” principle
LEEASP: Prototype
Environmental View
Overview
Control
Summary
Details
LEEASP: Prototype
Taxonomic View
……
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G->T
T->G
LEEASP: Prototype
Ecoregion View
•Using the same API for Taxonomic view
•Based on Prefuse (Jeffrey et al, 2005)
•Efficient Tree Layout algorithms
•Advanced information visualization functions (zoom/animation)
LEEASP: Prototype
Coordinated Multiple View
•Overview+Detail
•Focus+Context
Related Works/Discussions
•USGS (1990s): Climate-Vegetation Atlas of the North
America (http://pubs.usgs.gov/pp/p1650-a/)
•Prasad and Iverson (1999-ongoing):A Climate Change Atlas
for 80 Forest Tree Species of the Eastern United States
http://www.fs.fed.us/ne/delaware/atlas/ (Forest Service)
•Spatiotemporal data modeling and visualization (Andrienko
et al 2003, Guo et al 2006)
•Tree and graph visualization research (Bongshin et al 2004,
Hillis et al 2005, Graham and Kennedy 2005, Parr et al 2007)
Related Works/Discussions
•LEEASP focuses on dynamic visualizations through user
interactions rather than delivering static mapping results.
•LEEASP provides multi-way mapping among geographical,
ecoregion, environmental and taxonomic data
•Views in LEEASP represent the four types of data are
coordinated: when a subset of data in one view is selected
through the graphic user interfaces, the subset of data will be
identified and highlighted in other views.
Related Works/Discussions
•Future work
•Better formalization of the integrated data
model
•Conduct more thorough user evaluations by
domain scientists
•Distributed data integration based SOA
•Explore “mashup” technologies
Acknowledgements
•Prefuse and JUMP GIS open source development teams.
•This work is supported in part by NSF grant ITR #0225665 SEEK and NSF
grant ATM #0619139 CEO:P-COMET.
•Thanks to Profs. Robert K. Peet (UNC) and Jessie Kennedy (Napier University,
UK) for taxonomy help.
•Thanks to Dr. Weimin Xi (TAUM) and Anantha M. Prasad (USDA Forest
Service) for evaluating the prototype and providing constructive suggestions.
•Special thanks to three anoymous ACM-GIS conference reviewers for their
comments and suggestions.
• Conference travel is supported by faculty startup fund from the Grove School
of Engineering, the City College of the City University of New York.
Q&A
[email protected]
http://www-cs.ccny.cuny.edu/~jzhang/tech/LEEASPV10.zip
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