Due Dates:
See Schedule
Resources
Read Manly Chapter 9
Lesson
Description
This module introduces you to
techniques for the analysis of spatial data. Like time series
analysis, spatial data analysis is a complex topic and could be the
subject of a full semester course (or more). This module is
simply an introduction to the relevant concepts and techniques.
The first main objective of
the module is to understand spatial autocorrelation, to be able to
explain what it is, and to have a feel for why it is important to
worry about it. The second main objective is to be able to
test a data set consisting of quadrat counts for positive or
negative spatial autocorrelation, clustering or uniformity
respectively. The third main objective is to become familiar with
variograms, their component parts, and the different types of them
that can be constructed. The last objective is to be
introduced to kriging, a technique for using the autocorrelation
structure to predict the value of a variable in areas that were not
measured.
This week, work through the learning module and
review Chapter 9 in the textbook. You will need to show
mastery of this material in
Problem Set 5.
Printable
Notes
