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The CURA publications library is currently being digitized by the University of Minnesota Digital Conservancy. When the project is complete, the entire CURA publications library will be online and fully searchable. Unfortunately, during this process we are not able to honor individual requests for publications . Additionally, we no longer have physical copies of publications to send out.

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Spatial Data Mining: An Emerging Tool for Policy Makers.

Chawla, Sanjay, Shaski Shekhar, Wei Li Wu, and Xinhong Tan.

Widespread use of spatial databases has increased interest in 'mining' useful but implicit spatial patterns among data. The sheer size of such spatial data sets often makes it difficult to search for meaningful patterns or relationships among data. However, spatial data mining--which draws on techniques from machine-learning, database management, and statistics--holds the promise of rapidly uncovering patterns within spatial databases with minimal human effort or intervention. This article discusses differences between classic data mining and spatial data mining techniques, develops a model for incorporating spatial properties into a data mining framework, applies this model to an example from ecology involving red-winged blackbird habitat, and discusses the implications of spatial data mining for policy makers. The authors conclude that spatial data mining has potential applications in many areas, including environmental management, crime prediction, transportation and land use planning, econometrics, regional science, epidemiology, geographic analysis, and remote sensing.

CURA Reporter
Publication date: 
Minneapolis: Center for Urban and Regional Affairs, University of Minnesota.
Supported by a CURA Interactive Research Grant.
30 (3) 10-15.
Online availability
Download from CURA: 
CURA call number: 
Reporter 30 (3)

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