Autocorrelation, Variograms and Kriging

Purpose

This module deepens a students understanding of spatial autocorrelation and interpolation by introducing Moran's I, Variograms, and Kriging.

Learning Objectives

• Be able to articulate when spatial auto correlation is acceptable and when it is not
• Interprate Moran's I outputs
• Create and interprate Variograms
• Create Kriged surfaces and associated error surfaces

Reading

Bolstad, Chapter 12

• Skip "Core Area Mapping" for now

Presentations

1. Auto correlation
2. Interpolation review, variograms, and Kriging
3. QQPlots

Activities

The lab will use a traditional example of ozone in the atmosphere over Los Angeles, California. Another example would be interpolating from weather data from the NOAA web site. Try to come up with another example for yourself.

Lab

Start of a new lab

Assessment

The assessment can be based directly on the learning objectives (i.e. given a set of themes and extents, name the appropriate data type for each).