Eight different ways to map data
(Click on the maps for a full-sized version, or on the above links for a more detailed pdf.)
The data for this example comes from the course “Introduction to ArcGIS 9 Geostatistical Analyst” by ESRI and Jay Ver Hoef, Ph.D., available on http://training.esri.com.
This study (most likely fictitious) of ozone levels in California comes to us in the form of a set of points linked to a coordinate. That point’s ozone level in parts per million is the recorded data for that particular point. When this information is loaded into GIS software, in this case, ESRI’s ArcGIS, one can see how the points are related in space, and estimates can be made of how the entire state of California measures up for ozone levels.
To estimate the ozone levels for all of California based on the ozone levels at particular points throughout the state is to use a technique called “interpolation”. There are many different kinds of interpolation methods, all of them derived from statistics. The definitions of all the methods employed here are shown on the maps, but you might ask, ‘Which one is the most accurate?’ That will depend on the available data and which method fits the data best.
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