Skip directly to searchSkip directly to the site navigationSkip directly to the page's main content

Free Analytical Tools

Listed below are links to free analytical tools.

TerraServer and TerraServer Download for ArcGIS

TerraServer-USA is a free online repository of public domain aerial imagery and satellite imagery, formerly known as Microsoft TerraServer. The ArcView tool "TerraServer Download for ArcGIS" provides the user with the ability to download imagery hosted by the Terraserver Server directly into ArcMap.

Space-Time Analysis of Regional Systems (STARS)

Space-Time Analysis of Regional Systems (STARS) is an open source package designed for the analysis of aerial data measured over time. STARS brings together a number of recently developed methods of space-time analysis into a user-friendly graphical environment offering an array of dynamically linked graphical views. It is intended to be used as an exploratory data analysis tool. Written entirely in Python, STARS is cross platform and easy to install and expand.


GeoDa is the latest incarnation of a collection of software tools designed to implement techniques for exploratory spatial data analysis (ESDA) on lattice data. It is intended to provide a user-friendly graphical interface to methods of descriptive spatial data analysis, such as autocorrelation statistics and indicators of spatial outliers. The design of GeoDa consists of an interactive environment that combines maps with statistical graphics, using the technology of dynamically linked windows. The current software is freestanding. Runs on Windows OS. The GeoDa Center for Geospatial Analysis is located at the University of Chicago Center for Spatial Data Science


SaTScan is a free software that analyzes spatial, temporal, and space-time data using the spatial, temporal, or space-time scan statistics. It is designed for any of the following interrelated purposes: to perform geographical surveillance of disease; to detect spatial or space-time disease clusters; and to see if they are statistically significant; to test whether a disease is randomly distributed over space, over time, or over space and time; to evaluate the statistical significance of disease cluster alarms; and to perform repeated time-periodic disease surveillance for early detection of disease outbreaks.


WinBUGS is part of the BUGS project, which aims to make practical MCMC methods available to applied statisticians. The BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods.

R Packages

In computing, R is a programming language and software environment for statistical computing and graphics. It is an implementation of the S programming language with lexical scoping semantics inspired by Scheme. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is now developed by the R Development Core Team. The R language has become a de facto standard among statisticians for the development of statistical software.


GeoR is a package to perform geostatistical data analysis and spatial prediction, expanding the set of currently available methods and tools for analysis of spatial data in R. It has been developed at the Department of Mathematics and Statistics, Lancaster University, UK.

The information provided above is from the Utah Department of Health's Center for Health Data IBIS-PH web site ( The information published on this website may be reproduced without permission. Please use the following citation: " Retrieved Sun, 22 April 2018 12:26:21 from Utah Department of Health, Center for Health Data, Indicator-Based Information System for Public Health Web site: ".

Content updated: Tue, 13 Feb 2018 16:50:12 MST