Listed below are links to free analytical tools.
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) 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.
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.
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.
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.