The canonical data model means fewer maps to write, and also if the data model of either a requestor or a provider was to change, it only affects their specific mapping to or from the canonical model.

This paper analyzes the change of cultivated land intensive use degree from 1990 to 2006 in China and its influencing factors using canonical correlation analysis.

This paper introduces some classical approaches and some other ways such as in direct change detection adding the gray level classification, mending the m canonical transformation method.