Exploring spatial data by using interactive graphics and local statistics

Exploratory spatial data analysis has a series of aims including determining spatial structure in the data, describing and visualizing geographical distributions, exploring spatial dependencies, measuring heterogeneity and identifying outliers, To quantify these phenomena a rich variety of statistics has been proposed. Standard methods use all the data for the entire area under study, yet this area has usually been arbitrarily bounded and may include quite distinctive geographic features. Local statistics are relatively independent of the global boundaries and they attempt to quantify how close a given datum is to the values in its neighbourhood. Since each local statistic focuses on slightly different aspects of the data the use of more than one is suggested. Interactive graphics methods help to link the information from different local statistics and dynamic tools can be used to visualize the effects of changing the neighbourhood definition.