Geographic Information and Analysis

This course is designed to explore various aspects of spatial analysis using GIS. It is assumed that the student taking this course already has working knowledge of GIS and statistical analysis, and is looking for ways to integrate the two methodlogies.

Course Syllabus
GIS lab handbook gives intro to unix, arc/info concepts
Getting started with arc/info

homework assignments

Labs

Lab 2 reclassification and updates
Lab 3 Correlation between polygon themes using chi-square
Lab 4: Correlations between a point and polygon using ANOVA, spatial averages, correlation coefficient
Lab 5: point patterns and quadrat analysis
Lab 6: Moran coefficient
Lab 7: Spatial interaction models
Lab 8: Destination-constrained spatial interaction models
Lab 9: Introduciton to swarm

Lab 10: Dynamic cellular modeling

Lecture Notes

Week 1	Jan 6	Jan 8	Jan 10	Introduction, Spatial Data, Spatial Measurement, Coordinate conversion
Week 2	Jan 13	Jan 15	Jan 17	Single layr operations
Week 3	Jan 20	Jan 22	Jan 24	Overlay analysis, correlations between polygon themes, contingency tables
Week 4	Jan 28	Jan 30	Feb 1	Correlations between point and polygon themes, spatial averages
Week 5	Feb 3	Feb 5	Feb 7	Point Patterns and quadrat analysis
Week 6	Feb 10	Feb 12	Feb 14	Spatial Autocorrelation
Week 7	Feb. 17	>Feb. 19	Feb 21	Network analysis

If you understand what you're doing, you're not learning anything
A. L.
Celestial Navigation is based on the premise that the Earth is at the center of the universe. The assumption is wrong, but the navigation works. An incorrect model can be a useful tool.
Kelvin Throop III
``I do not believe that. At this moment in time, if that changes in years to come I don't know, but what happens here today and changes as we go along that is part of life's learning and part of your inner beliefs.''
British soccer player Glenn Hoddle

\ Dr. Paul Box