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  {\bf Abstract}
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This thesis describes an interactive image analysis algorithm for the correct
placement of trees within a virtual reality wildfire visualization system.
The wildfire visualization system is VFIRE (Virtual Fire in Realistic
Environments), which uses fire simulation results produced by software
programs such as FARSITE to place the user into an immersive, artificial
environment where he or she can see graphical depictions of real or
fictitious wildfire events.  The purpose of VFIRE is to assist in training
and planning for actual fires, and our purpose is to
place trees within the artificial environment at locations corresponding
to their locations in the real environment.  Our goal was to achieve adequate tree-placement accuracy using
any, arbitrarily chosen image, assuming no constraints on the minimum
suitability of that image for tree detection.  This goal led to
the selection of a template-matching algorithm wherein the user selects
a particular tree as a template and begins to search the
image for similar-looking trees.   Tree detection results are presented
for a 1-meter panchromatic image of the current area of interest, Kyle
Canyon, in Southern Nevada.  It is difficult to perceive the aesthetic
effect of tree-detection inaccuracies in terms of numeric error rates.
Therefore, screen shots are provided representing tree-detection results
placed into three broad, subjective categories: good, adequate, and poor.
The results obtained were found to be roughly fifteen percent good,
seventy percent adequate, and fifteen percent poor, where accuracy was
directly related to the suitability of the terrain for tree detection
in each particular region of the image. 

