Journal article
Spatial Clustering Overview and Comparison: Accuracy, Sensitivity, and Computational Expense
Annals of the Association of American Geographers, v 104(6), pp 1134-1155
02 Nov 2014
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Cluster analysis continues to be an important exploratory technique in scientific inquiry. It is used widely in geography, public health, criminology, ecology, and many other fields. Spatial cluster detection is driven by geographic information corresponding to the location of activities, requiring appropriate and meaningful treatment of space and spatial relationships combined with observed attributes of location and events. To date, this has meant utilizing dedicated measures and techniques to structure and account for distance, neighbors, contiguity, irregular geographic morphology, and so on. Unfortunately, all spatial clustering approaches, regardless of their theoretical underpinning, statistical foundation, or mathematical specification, have limitations in accuracy, sensitivity, and the computational effort required for identifying clusters. As a result, a major challenge in practice is determining which technique(s) will provide the most meaningful insights for a particular substantive issue or planning context. The purpose of this article is to provide an overview and evaluation of spatial clustering techniques, identifying the strengths and weaknesses of the most widely applied approaches. Results suggest that performance varies significantly in terms of accuracy, sensitivity, and computational expense. This is noteworthy because the misidentification of clusters, whether false positives or false negatives, has the potential to bias not only hypothesis formulation but also pragmatic facets of policy, process, and planning efforts within a region.
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Details
- Title
- Spatial Clustering Overview and Comparison: Accuracy, Sensitivity, and Computational Expense
- Creators
- Tony H. Grubesic - Drexel UniversityRan Wei - University of UtahAlan T. Murray - Drexel University
- Publication Details
- Annals of the Association of American Geographers, v 104(6), pp 1134-1155
- Publisher
- Taylor & Francis
- Number of pages
- 22
- Resource Type
- Journal article
- Language
- English
- Web of Science ID
- WOS:000343668200003
- Scopus ID
- 2-s2.0-84908220528
- Other Identifier
- 991019357771804721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Geography