Uni or multi-variate analysis

Change analysis can concentrates on property change of a single or a set of phenomenon:

• Univariate analysis: a single phenomenon characterised with a single variable is processed in this analysis. The population density analysis, illustrated before is an example of univariate change analysis concerning several spatial features. Each row of the table corresponds to a time series that express the change in population density for each spatial feature, a municipality.
• Multivariate analysis: the change analysis can concern the simultaneous changes of several phenomena expressed by multiple variables. This allows for the study of relationships and interactions between changes of phenomena. Such multivariate approach can be applied to either a single spatial feature (multivariate single feature analysis) or several (multivariate multiple features analysis). Spatial analysis is primarily concern with this latter. In order to simplify the complexity of this analysis, often change indicators are first derived for each spatial feature with respect to each variable.