Choose the right type of theme to suit your data
 
 
 

You’ve almost certainly seen many thematic maps. These kind of maps are common nowadays in newspapers or on the internet, whenever the intention is to make some quantitative comparison of data. For example, a map of a country that shows election results is a thematic map. A map of the world showing GDP (gross domestic product) for each country is a thematic map.

A common use of thematic maps in local government is to show assessed property values. Other examples would be a zoning map or a map showing school districts.

In AutoCAD Map 3D, you theme a layer based on a particular property or attribute. For example, you could theme a layer containing parcels according to the LAND_VALUE property of each parcel, or you could theme the same features by the AREA property. In this way, you can have multiple thematic layers in the same map, all based on the same features. Normally, of course, you only display one theme at a time (although you can create some useful maps by overlaying one semi-transparent theme over another—for example, a zoning layer on top of a parcels layer).

Equally important is the way that you stratify your data when you create a theme. You can get very different results depending on how you categorize and divide up your data. For this reason, it is a good idea to take a look at your data by making a chart of it. This will help you make a better decision about what kind of theme is most appropriate. You can generate a simple chart in a spreadsheet program, such as Microsoft Excel. The chart in the illustration below shows the distribution of values in the LAND_VALUE column of a parcels database.

TipTo get your data into a spreadsheet, you can export it in .CSV format. See Generate a report by exporting records to a spreadsheet.

The illustration below shows four maps of the same set of parcels. Each theme is based on the same LAND_VALUE property, and each one divides the data into six classes or ranges. However, each map uses a different method of separating the data into those six ranges.

These are the four methods: