Topic:
Geostatistical Models and Methods
OVERVIEW and OBJECTIVES
In this module we investigate geostatistical methods. In particular,
we are interested in the production of maps from data. The general procedure
is as follows:
- examine the data, to determine what kind of interpolation (mapping) is
appropriate;
- model the spatial autocorrelation of the data;
- use the model to "krig" the data (generate the map); and
- check the results.
OBJECTIVES:
Those who successfully complete the module should
- understand spatial autocorrelation as a function of space, with
important characteristics such as the distance over which correlation
exists, the relative size of the correlation, etc.;
- understand the variogram and its relationship to kriging;
- know how to model the variogram, and plausible models;
- understand kriging interpolation and its relationship to the variogram;
- be able to use geostatistical software to
- create and model variograms, and know why it's done
(decomposing sample variance to explore spatial
autocorrelation),
- krig, and know why it's done (make better
assumptions about spatial autocorrelation to get better
maps than arbitrary, ad hoc inverse-distance
weighting and other methods provide).
SCENARIOS FOR DISCUSSION
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