building an online system for research, outreach, and education of geospatial environmental research...
Post on 19-Dec-2015
214 views
TRANSCRIPT
Building an Online System for Research, Outreach, and Education of Geospatial Environmental Research
Jim GrahamColorado State UniversityFort Collins, Colorado
Data Management Challenges
Lat Lon Temp Precip
-105.504 40.35819 5.32 58.4
-107.472 40.498 6.31 47.6
Example: Potential habitat distribution of invasive plant dalmation toadflax (Linaria dalmatica) in Colorado, USA
Hierarchical Vector data
!
!
!!
!
!
!
!!!!
!!
!!
!
!!
!
!!!
!!!
!
!!
!
!
!
!
!
!
!!
!!
!
Legend
predict1
Value
High : 100
Low : 00
100
Precipitation
Temperature
ModelingAlgorithm
Variable Coefficient P-Value
Intercept -1.52 0.064
Annual Precip
-0.05 0.0
Annual Temp.
0.61 0.0
Map Generation
Model-Specific Data
Geo Referenced Rasters
Spreadsheets
Geo Referenced Rasters
General Imaging Issues
• Resolution and coverage of available data
• Acquisition costs
• Hardware and software performance
• Data quality
• File Format Compatibility
Goals
• Create an online system for geospatial-ecological science
• End-users: researchers, resource managers, teachers, and the public
• End-Users can add spatial data– Vector data (text and Shapefiles)– Raster data
Vector Data
• A few very large, complex shapes– National parks– Countries– States
• Lots of small, simple shapes– Individual surveys– Observation points
• Some regions have very high densities of spatial coordinates
• P – Projection time per coordinate• L – Loading time per coordinate• R – Rendering time per coordinate• N – Number of coordinates
T1 ( ) P L R N
Approaches
• Access only data within viewing area
• 4 – Maintain All Required Projections– Geographic– 3 UTM Zones– All are WGS84
• Optimal use of an indexed, relational, enterprise-level database
• Equation 7: low resolution– NC – Number of cells
• Equation 8: high resolution– MH – Maximum point density at high resolution
• Q1 = maximum time to access indexed data in the database
Maximum Rendering Times
T7 Q1 ( )L R NC
T8 Q1 ( )L R MH
Limiting Data Quantity
1 meter per pixel1 degree per pixel
Viewing Resolution
100% 100%
0% 0%
% Rendered as coordinates
% Rendered as grid-pixels
1 meter per pixel1 degree per pixel
Viewing Resolution
100% 100%
0% 0%
% Rendered as coordinates
% Rendered as grid-pixels
Acknowledgements: www.NIISS.org
• NIISS: Tom Stohlgren, Mohammed Kalkhan, Greg Newman, Alycia Crall, Catherine Jarnevich, Tracey Davern, Paul Evangelista, Sunil Kumar, Sara Simonson
• NSF Grant #OCI-0636210
• Volunteer Groups