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\chapter{Introduction To GIS}
A Geographical Information System (GIS)\footnote{This chapter is by Tyler Mitchell
 (\url{http://www.oreillynet.com/pub/wlg/7053}) and
used under the Creative Commons License. Tyler is the author of \textit{Web
Mapping Illustrated}, published by O'Reilly, 2005.}
is a collection of software that allows you to create, visualise, query and
analyse geospatial data. Geospatial data refers to information about the
geographic location of an entity. This often involves the use of a geographic
coordinate, like a latitude or longitude value. Spatial data is another
commonly used term, as are: geographic data, GIS data, map data, location
data, coordinate data and spatial geometry data.

Applications using geospatial data perform a variety of functions. Map
production is the most easily understood function of geospatial applications.
Mapping programs take geospatial data and render it in a form that is
viewable, usually on a computer screen or printed page. Applications can
present static maps (a simple image) or dynamic maps that are customised by
the person viewing the map through a desktop program or a web page.

Many people mistakenly assume that geospatial applications just produce maps,
but geospatial data analysis is another primary function of geospatial
applications. Some typical types of analysis include computing:

\begin{compactenum}
\item distances between geographic locations
\item the amount of area (e.g., square metres) within a certain geographic region
\item what geographic features overlap other features
\item the amount of overlap between features
\item the number of locations within a certain distance of another
\item and so on...
\end{compactenum}

These may seem simplistic, but can be applied in all sorts of ways across many
disciplines. The results of analysis may be shown on a map, but are often
tabulated into a report to support management decisions.

The recent phenomena of location-based services promises to introduce all
sorts of other features, but many will be based on a combination of maps and
analysis. For example, you have a cell phone that tracks your geographic
location. If you have the right software, your phone can tell you what kind of
restaurants are within walking distance. While this is a novel application of
geospatial technology, it is essentially doing geospatial data analysis and
listing the results for you.

\section{Why is all this so new?}
Well, it's not. There are many new hardware devices that are enabling mobile
geospatial services. Many open source geospatial applications are also
available, but the existence of geospatially focused hardware and software is
nothing new. Global positioning system (GPS) receivers are becoming
commonplace, but have been used in various industries for more than a decade.
Likewise, desktop mapping and analysis tools have also been a major commercial
market, primarily focused on industries such as natural resource management.

What is new, is how the latest hardware and software is being applied and who
is applying it. Traditional users of mapping and analysis tools were highly
trained GIS Analysts or digital mapping technicians trained to use CAD-like
tools. Now, the processing capabilities of home PC's and open source software
packages have enabled an army of hobbyists, professionals, web developers,
etc. to interact with geospatial data. The learning curve has come down. The
costs have come down. The amount of geospatial technology saturation has
increased.

How is geospatial data stored?
In a nutshell, there are two types of geospatial data in widespread use today.
This is in additional to traditional tabular data that is also widely used by
geospatial applications.

\subsection{Raster Data}
One type of geospatial data is called raster data or simply "a raster". The
most easily recognised form of raster data is digital satellite imagery or air
photos. Elevation shading or digital elevation models are also typically
represented as raster data. Any type of map feature can be represented as
raster data, but there are limitations.

A raster is a regular grid made up of cells, or in the case of imagery,
pixels. They have a fixed number of rows and columns. Each cell has a numeric
value and has a certain geographic size (e.g. 30x30 metres in size).

Multiple overlapping rasters are used to represent images using more than one
colour value (i.e. one raster for each set of red, green and blue values is
combined to create a colour image). Satellite imagery also represents data in
multiple "bands". Each band is essentially a separate, spatially overlapping
raster where each band holds values of certain wavelengths of light. As you
can imagine, a large raster takes up more file space. A raster with smaller
cells can provide more detail, but takes up more file space. The trick is
finding the right balance between cell size for storage purposes and cell size
for analytical or mapping purposes.

\subsection{Vector Data}
Vector data is also used in geospatial applications. If you stayed awake
during trigonometry and coordinate geometry classes, you will already be
familiar with some of the qualities of vector data. In its simplest sense,
vectors are a way of describing a location by using a set of coordinates. Each
coordinate refers to a geographic location using a system of x and y values.

This can be thought of in reference to a Cartesian plane - you know, the
diagrams from school that showed an x and y-axis. You might have used them to
chart declining retirement savings or increasing compound mortgage interest,
but the concepts are essential to geospatial data analysis and mapping.

There are various ways of representing these geographic coordinates depending
on your purpose. This is a whole area of study for another day - map
projections.

Vector data takes on three forms, each progressively more complex and building
on the former.  
\begin{compactenum}
\item Points - A single coordinate (x y) represents the discrete geographic location
\item Lines - Multiple coordinates (x1 y1, x2 y2, x3 y4, ... xn yn) strung
together in a certain order. Like drawing a line from Point (x1 y1) to Point
(x2 y2) and so on. These parts between each point are considered line
segments. They have a length and the line can be said to have a direction
based on the order of the points. Technically, a line is a single pair of
coordinates connected together; whereas, a line string is multiple lines
connected together.  
\item Polygons - When lines are strung together by more
than two points, with the last point being at the same location as the first,
we call this a polygon. A triangle, circle, rectangle, etc. are all polygons.
The key feature of polygons is that there is a fixed area within them.
\end{compactenum}

