Advanced space-time predictive analysis with STAR-BME

Hwa-Lung Yu, Shang-Jen Ku, Alexander Kolovos
2012 Proceedings of the 20th International Conference on Advances in Geographic Information Systems - SIGSPATIAL '12  
Stochastic analysis and prediction is an important component of space-time data processing for a broad spectrum of Geographic Information Systems scientists and end users. For this task, a variety of numerical tools are available that are based on established statistical techniques. We present an original software tool that implements stochastic data analysis and prediction based on the Bayesian Maximum Entropy methodology, which has attractive advanced analytical features and has been known to
more » ... address shortcomings of common mainstream techniques. The proposed tool contains a library of Bayesian Maximum Entropy analytical functions, and is available in the form of a plugin for the Quantum GIS open source Geographic Information System software.
doi:10.1145/2424321.2424424 dblp:conf/gis/YuKK12 fatcat:ewo6g5bjcjepxpsqotgqqf7jja