Readings from Webster and Oliver, Geostatistics for Environmental Scientists , (marked W&O) and Diggle and Ribeiro, Model-Based Geostatistics, (marked D&R), both of which are on reserve in Sinclair library (on the 4th floor in the Wong AV Center) under call numbers PC#130 and PC#131, respectively.
| Week | Topic |
|---|---|
| 1 | Intro to course content, requirements and participants.
Read: W&O Chap 1 & Appendix A. Lab: 00 Data in Surfer, ArcGIS and R |
| 2 | Review basic aspatial descriptive statistics,
interpolation. Spatial variability and regionalized variable theory.
Autocorrelation and impacts on statistical analysis.
Read: W&O Chap 2 Lab: (cont.) Getting started with R |
| 3 | Prediction and interpolation.
Read: W&O Chap 3. Skim D&R 1.3, 1.4, 2.1, 2.4-2.7 |
| 4 | Characterizing spatial processes: Covariance and Variogram.
Read: W&O Chap 4. D&R Chap 4 (?) Lab: Getting Variograms . |
| 5 | Estimating and Modelling the Variogram
Read: W&O Chap 5 & 6. D&R Chap 5. |
| 6 | Krigging
Read: W&O Chap 8. Lab: Finally... kriging. |
| 7 | Cross-correlation, coregionalization, co-krigging
Read: W&O Chap 9. Lab: co-kriging the Jura data. |
| 8 | Disjunctive kriging
Read: W&O Chap 10. Midterm Exam Lab: Disjunction at Broom's Barn Farm . |
| 9 | "Model-based" (re?)considered... kriging in context?
Read: D&R Preface, Chap 1 - 3. Lab: Simulation . |
| 10 | Generalized linear models for geostatistical data
Read: D&R Chap 4. |
| 11 | Classical parameter estimation
Read: D&R Chap 5. Due: Term Project Proposal. |
| 12 | Spatial Prediction
Read: D&R Chap 6. Lab: 04 Bayesian approach |
| 13 | Bayesian Inference
Read: D&R Chap 7. |
| 14 | Geostatistical design
Read: D&R Chap 8. |
| 15 | Student Presentations |
| 16 | ...continued. |