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Proceedings Paper

Bayesian hierarchical analysis of minefield data
Author(s): Noel A. C. Cressie; Andrew B. Lawson
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Paper Abstract

Based on remote sensing of a potential minefield, point locations are identified, some of which may not be mines. The mines and mine-like objects are to be distinguished based on their point patterns, although it must be emphasized that all we see is the superposition of their locations. In this paper, we construct a hierarchical spatial point-process model that accounts for the different patterns of mines and mine-like objects and uses posterior analysis to distinguish between them. Our Bayesian approach is applied to COBRA image data obtained from the NSWC Coastal Systems Station, Dahlgren Division, Panama City, Florida.

Paper Details

Date Published: 4 September 1998
PDF: 11 pages
Proc. SPIE 3392, Detection and Remediation Technologies for Mines and Minelike Targets III, (4 September 1998); doi: 10.1117/12.324262
Show Author Affiliations
Noel A. C. Cressie, Iowa State Univ. (United States)
Andrew B. Lawson, Univ. of Abertay Dundee (United Kingdom)


Published in SPIE Proceedings Vol. 3392:
Detection and Remediation Technologies for Mines and Minelike Targets III
Abinash C. Dubey; James F. Harvey; J. Thomas Broach, Editor(s)

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