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Activity Number: 80 - Advancement in Spatial and Spatiotemporal Point Process
Type: Contributed
Date/Time: Sunday, July 29, 2018 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #328965 Presentation
Title: Inferring Spatial Point Intensity of Geomagnetic Anomalies from Transect Sampling
Author(s): Kenneth Flagg* and Andrew Hoegh and Megan Higgs and John Borkowski
Companies: Montana State University and Montana State University and Montana State University and Montana State University
Keywords: Bayesian statistics; spatial point process; Dirichlet process; unexploded ordnance

Geomagnetic anomalies recorded at munitions use sites are often collected along transects that cover a very small proportion of the site area. Munitions items are assumed to occur in elliptical regions of high point intensity, so a primary analysis goal is to map the intensity over the site and identify high-intensity regions that might contain unexploded ordnance. We propose a Bayesian spatial Poisson process model with a Dirichlet process mixture as the inhomogeneous intensity function. Then we incorporate data augmentation into a Gibbs sampler to fit the model to data observed in a subset of the site region. We demonstrate fitting the model to simulated data, using both the fully-observed region and the restriction to two different subsets. Finally, we fit the model to data collected at the Victorville Precision Bombing range in southern California.

Authors who are presenting talks have a * after their name.

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