Acta Oecologica, 31(2), pp.193-202,
a. Australian School of Environmental Studies,
b. School of Computer Science and Software Engineering
(now Faculty of Information Technology),
This paper examines the effects of using a segmentation method to
identify change-points or edges in vegetation.
It identifies coherence (spatial or temporal) in place of
The segmentation method involves change-point detection along a
sequence of observations so that each cluster formed is composed of
adjacent samples; this is a form of constrained clustering.
The protocol identifies one or more models, one for each section identified,
and the quality of each is assessed using a minimum message length criterion,
which provides a rational basis for selecting an appropriate model.
Although the segmentation is less efficient than clustering, it does
provide other information because it incorporates textural similarity as
well as homogeneity.
In addition it can be useful in determining various scales of variation
that may apply to the data, providing a general method of
small-scale pattern analysis.
MML, minimum message length, KL Kullback-Leibler,
BIC, Bayesian Information Criterion.
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