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.
|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.
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.
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.