Introduction

Earth scientists often rely on different types of maps where the spatial location of each sampling unit is one of the variables of interest. For example, a geoscientist might have data for the presence or absence of copper-bearing ore at 54 test cores drilled within the sampling space of a 10 000 square mile mining lease. The effectiveness of any further prospecting would be improved if you knew whether the spatial distribution of cores showing copper-bearing ores occurred at random or in some sort of pattern within the sampling space. The methods for summarizing and analyzing such data are called spatial analyses.

Even though the Earth is three-dimensional, most summary spatial information is presented as two-dimensional maps representing the Earth's surface, often with an overlay to indicate other variables. For example, maps showing landforms are printed on two-dimensional sheets, with contour lines and numbers to show the third dimension of elevation. Similarly, a map of the location and flow per minute of test wells for oil might indicate flow with numbers (e.g. the average number of barrels per day from each well) or display this as the proportional height of a single bar at each well.

The location of any point on a two-dimensional surface can be accurately and precisely defined by its X and Y coordinates, which are the distances in two directions at 90° to each other from a set reference point, in just the same way as a graph is used to display a two-dimensional scatter plot of bivariate data.