Visualizing Spatial Autocorrelation with Dynamically Linked Windows Visualizing Spatial Autocorrelation with Dynamically Linked Windows 1

Several recent efforts have focused on adding exploratory data analysis functionality to geographic information systems (GIS) by integrating established statistical software with a GIS. In this paper, we outline an alternative approach, where the functionality is built from scratch, using a combination of small libraries of dedicated functions, rather than relying on the full scope of existing software suites. The suggested approach is modular and freestanding. Within an overall framework of dynamically linked windows, it combines a cartographic representation of data on a map with traditional statistical graphics, such as histograms, box plots, and scatterplots. In addition, it includes several devices to visualize spatial autocorrelation in lattice (or regional) data, such as the Moran Scatterplot and LISA maps. This new program (DynESDA2) also implements the capability to brush polygon coverages, simultaneous linking of multiple maps with multiple statistical graphics, and interactive LISA maps.