Authors: Majid Shishehgar; Seyed Nasirodin Mirmohammadi; Ahmad Reza Ghapanchi
Addresses: Department of Industrial Engineering, Isfahan University of Technology, Isfahan, Isfahan, Iran ' Department of E-Learning, University of Shiraz, Shiraz, Fars, Iran ' Department of Computer Engineering, Isfahan University, Isfahan, Isfahan, Iran
Abstract: Spatial data in databases, specifically in geographic information systems (GIS) data centres, can produce huge amounts of data. This great volume of information includes useful and non-useful data along with some hidden patterns which can be better managed and controlled by utilising some novel artificial intelligence methods. In this research we have a brief survey on the application of statistical methods like data mining and knowledge discovery on spatial data. First, we present an overview of geospatial data mining and knowledge discovery techniques, including spatial clustering, classification, prediction, associate rules and pattern analysis. Then, some challenges faced by geographic knowledge discovery in geographic information systems (GIS) have discussed in order to have a more clear idea of the future's researches in this area.
Keywords: geospatial data mining; spatial knowledge discovery; spatial interaction; spatio-temporal patterns; classification; clustering; associated rules; decision trees; spatial data; geographic information systems; GIS data centres.
International Journal of Business Information Systems, 2015 Vol.19 No.2, pp.265 - 276
Received: 15 Feb 2014
Accepted: 20 Mar 2014
Published online: 16 May 2015 *