\chapter{Introduction}\label{ch1}

	VFIRE is an application that uses Virtual Reality (VR)
	technology to allow a user to be immersed in an artificial
	environment where real or fictitious wildfire scenarios can be
	visualized ~\cite{penicksThesis}.	The purpose of
	such simulations is to provide useful information about fire
	spread in a particular region under various wind, humidity,
	and other environmental conditions.  Currently, the region of
	interest is Kyle Canyon, near Mt. Charleston, Nevada.

	Since the simulation is intended to model an actual place,
	it is desirable that items within the simulation be located in
	the same place they would be located in the real environment.
	The purpose of this work is to accomplish such realistic item
	placement without the user having to specify the placement of
	each item individually.  This project provides a facility to make
	the process more (though not fully) automatic.	Some assistance
	from the user is still required.

	We are primarily focused on the placement of trees
	because trees constitute a large proportion of the fuel in a
	wildfire and because trees dominate the landscape in the current
	VFIRE region of interest.  Other items, such as buildings, can
	be placed in the simulation manually, but trees are currently
	the only items that can be placed automatically.

	We perform automatic tree placement by interpreting
	user-supplied information with reference to an image file showing
	the region of interest, and this image file is supplemented with
	information from various vegetation attribute files as well.
	If either of these file sets is not available, tree placements
	will be less accurate.	If neither is available, tree placements
	will be completely random.

	This project is currently configured to use satellite
	photographic image files showing the region of interest.
	Because satellite images tend to have low resolution, the
	current implementation cannot make use of algorithms requiring
	fine detail in the image.  Instead, we use a method more
	similar	to blob detection, which  selects blobs based on size and shape,
	ignoring details of the interior of the blob.

	It is the type and variety of data being used that distinguishes
	this work from others.  Much work has already been done to
	develop general-purpose interactive image analysis tools, tools
	for locating trees within relatively high-resolution aerial photo
	images, and tools to locate trees within groves of vegetation
	having uniform appearance.  This project, on the other hand, is
	similar to a general-purpose interactive image analysis utility 
	that incorporates vegetation maps to compensate for
	poor image quality and outputs tree locations directly in georeferenced
	coordinates.  In addition, this utility allows trees to be placed 
	based on vegetation maps alone in cases where photographic images
	are not available.

	The rest of this thesis is structured as follows: Chapter 2
	provides background information on basic image processing methods
	and existing item placement tools and algorithms.  Chapter 3
	explains the conceptual operation of this project.  The design
	of this project is presented in Chapter 4.  Information on the
	current implementation of this project as well as the results
	obtained so far are given in Chapter 5.  Chapter 6 presents our
	conclusions and identifies useful improvements to this project
	to be made in the future.
