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Identifying patterns in spatial information: A survey of methods
Author(s) -
Shekhar Shashi,
Evans Michael R.,
Kang James M.,
Mohan Pradeep
Publication year - 2011
Publication title -
wiley interdisciplinary reviews: data mining and knowledge discovery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.506
H-Index - 47
eISSN - 1942-4795
pISSN - 1942-4787
DOI - 10.1002/widm.25
Subject(s) - geospatial analysis , spatial analysis , data mining , data science , field (mathematics) , computer science , spatial ecology , spatial database , process (computing) , geography , cartography , remote sensing , mathematics , ecology , pure mathematics , biology , operating system
Explosive growth in geospatial data and the emergence of new spatial technologies emphasize the need for automated discovery of spatial knowledge. Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful patterns from large spatial databases. The complexity of spatial data and implicit spatial relationships limits the usefulness of conventional data mining techniques for extracting spatial patterns. In this paper, we explore the emerging field of spatial data mining, focusing on different methods to extract patterns from spatial information. We conclude with a look at future research needs. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 193–214 DOI: 10.1002/widm.25 This article is categorized under: Algorithmic Development > Spatial and Temporal Data Mining