C

Glossary : C

C

Cartesian coordinate system

Two dimensional, planar coordinate system in which x is used to measure horizontal distances and y vertical distances. The location of any point is referenced using an x, y coordinate pair.

CartoPrint

Extension to OnPoint that enables high-quality map printing from ArcGIS Server map services while displayed in the OnPoint web-GIS application. Several CartoPrint-related properties must be specified in the map document (.mxd file) on which the map service is based before printing is enabled. These are specified using the OnPoint toolbar and dialog boxes installed in ArcMap as a result of running a separate AO Tools installation.

class break

A set of features that have been grouped according to one of the classification systems available in thematic mapping. You can choose the number of class breaks that OnPoint categorizes the features on a layer and the classification method OnPoint uses.

classification method

Any one of the several methods you can select to have features in a layer categorized according to values of an attribute. These classification methods are available when you create a class break theme in OnPoint:

Table 43

Classification systems available in class break themes in thematic mapping

Classification system

Description

Equal count

Data is divided so that an equal number of data entries falls into each class. In census data for Canada showing numbers of births, for example, there would be more classes in the baby boom years after 1945 to account for the larger number of people born during that period. There would be fewer classes to represent those born during the 1970s.

Equal division

Splits data into a user-specified number of classes, each with an equal range of values. Can create classes with an uneven distribution of data and classes with no data. In census data for Canada showing numbers of births, for example, if you chose an equal division of data into classes of 10 years each, those classes that span the baby boom years after 1945 would show large population growth, and those spanning the 1970s and 1980s would have lower numbers.

Natural

Splits data into classes based on natural breaks that occur in the data. If there are obvious groupings of data in specific value ranges, each obvious value range would make up a class. In census data for Canada showing numbers of births, for example, there is a disproportionately large number of people born between 1945 and 1965. This entire group would form a class. If data entries are too scattered across all values, then a different classification system would be more efficient.

coordinate system

A reference system made up of points and a set of rules to define precise locations on the Earth. Coordinate systems may be tied to a map projection.

crosshair tool

Two black lines crossed on top of the map used as a calibration or sighting reference.

Classification system	Description
Equal count	Data is divided so that an equal number of data entries falls into each class. In census data for Canada showing numbers of births, for example, there would be more classes in the baby boom years after 1945 to account for the larger number of people born during that period. There would be fewer classes to represent those born during the 1970s.
Equal division	Splits data into a user-specified number of classes, each with an equal range of values. Can create classes with an uneven distribution of data and classes with no data. In census data for Canada showing numbers of births, for example, if you chose an equal division of data into classes of 10 years each, those classes that span the baby boom years after 1945 would show large population growth, and those spanning the 1970s and 1980s would have lower numbers.
Natural	Splits data into classes based on natural breaks that occur in the data. If there are obvious groupings of data in specific value ranges, each obvious value range would make up a class. In census data for Canada showing numbers of births, for example, there is a disproportionately large number of people born between 1945 and 1965. This entire group would form a class. If data entries are too scattered across all values, then a different classification system would be more efficient.