The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
A Mark 1 Geographical Analysis Machine for the automated analysis of point data sets
Abstract
This paper presents the first of a new generation of spatial analytical technology based on a fusion of statistical, GIS and computational thinking. It describes how to build what is termed a Geographical Analysis Machine (GAM), with high descriptive power. A GAM offers an imaginative new approach to the analysis of point pattern data based on a fully automated process whereby a point data set is explored for evidence of pattern without being unduly affected by predefined areal units or data error. No prior information or specification of particular location-specific hypotheses is required. If geographical data contain strong evidence of pattern in geographical space, then the GAM will find it. This technology is demonstrated by an analysis of data on cancer for northern England.
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Metadata
- Authors
- OPENSHAW, S., CHARLTON, M., WYMER, C., & CRAFT, A.
- Venue
- International journal of geographical information systems
- Publisher
- Informa UK Limited
- Published
- 1987-01
- Volume
- 1
- Issue
- 4
- Pages
- 335-358
- ISSN
- 0269-3798 (ISSN-L)
- OpenAlex
- W2282743468
- Cited by
- 508
- References
- 12
- FWCI
- 9.74
- Type
- journal article
- Language
- en
- Open access
- closed
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- OPENSHAW, S., CHARLTON, M., WYMER, C., & CRAFT, A. (1987). A Mark 1 Geographical Analysis Machine for the automated analysis of point data sets. International journal of geographical information systems. https://doi.org/10.1080/02693798708927821
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
