Journal
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE
Volume 34, Issue 4, Pages 659-676Publisher
WILEY
DOI: 10.1002/cjs.5550340407
Keywords
Bayesian inference; Bayesian model averaging; Berkson model; bivariate spatial process; coregionalization; measurement error
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The authors consider the issue of map positional error, or the difference between location as represented in a spatial database (i.e., a map) and the corresponding unobservable true location. They propose a fully model-based approach that incorporates aspects of the map registration process commonly performed by users of geographic informations systems, including rubber-sheeting. They explain how estimates of positional error can be obtained, hence estimates of true location. They show that with multiple maps of varying accuracy along with ground truthing data, suitable model averaging offers a strategy for using all of the maps to learn about true location.
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