Spatial Data Mining Software
iRedistrict: A Redistricting Software with Human-Computer Collaboration

iRedistrict is a patent-pending redistricting software, with powerful optimization algorithms and intuitive user control.
EntroMap: Detecting Spatially Varying Multivariate Relationships

EntropMap is a new approach that can detect the existence of multivariate relationships without assuming a prior relationship form.
Flow Mapping with Graph Partitioning and Regionalization

Flow Mapping with Graph Partitioning and Regionalization is an integrated software tool to explore flow patterns in large spatial interaction data.
REDCAP: Regionalization with Constrained Clustering and Partitioning

Regionalization is to divide a large set of spatial objects into a number of spatially contiguous regions while optimizing an objective function, which is normally a homogeneity (or heterogeneity) measure of the derived regions.
VIS-STAMP: A Visualization System for Space-Time and Multivariate Patterns

VIS-STAMP is a geo-visual analytic software package that couples computational, visual, and cartographic methods for exploring and understanding spatio-temporal and multivariate data. It can help analysts investigate complex patterns across multivariate, spatial, and temporal dimensions via clustering, sorting, and visualization.
SOMVIS: Multivariate Mapping and Visualization

SomVis is an integrated software tool that is able to: (1) perform multivariate analysis, dimensional reduction, and data reduction (summarizing a large number of input data items in a moderate number of clusters) with the Self-Organizing Map (SOM); (2) encode theSOM result with a systematically designed color scheme; (3) visualize th
POLO: Program for Optimal Linear Ordering

Linear ordering is to transform a set of data objects to a one dimensional order, which preserves multivariate or graph patterns as much possible. Linear ordering is widely used to discover patterns. When applied in geographical analysis, a linear ordering can be used to facilitate the detection of space-time (Guo et al. 2006), space-multivariate, and spatial interaction patterns (Guo 2007).

The materials distributed on this website since 2008 are based upon work partially supported by the National Science Foundation under Grant No. 0748813. Any opinions, findings and conclusions or recomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).