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CAST

Python-Based Software for Exploratory Space-Time Analytics

Introduction

CAST is a free and open-source, cross-platform program (Windows, Mac OSX and Linux) designed "to detect spatial patterns and trends in space-time data."

It is developed using Python (based on wxPython and PySAL) and C++ (to accelerate some core functionalities e.g. kernel density maps and Local Indicators of Spatial Autocorrelation or LISA maps).

Like its sister software GeoDa, CAST provides a user-friendly and graphical interface to methods of exploratory spatial data analysis (ESDA), in this case for space-time data.

CAST makes it easy to represent different dimensions of space-time data (like crime types or neighborhood characteristics) in views such as maps, graphs, and calendars that can be animated over time. All of these views are linked to allow analysts to identify how selected subsets of the data are characterized across these dimensions. Using statistical significance tests, CAST includes several cluster maps and trend graphs to detect where concentrations of crimes are higher or lower than expected.