Multiscale structure of UXO site characterization: spatial estimation and uncertainty quantification |
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| Authors: | G Ostrouchov W E Doll L P Beard M D Morris D A Wolf |
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| Institution: | (1) Statistics and Data Sciences Group, Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA;(2) Battelle––Oak Ridge Operations, Oak Ridge, TN 37830, USA;(3) Department of Statistics, Iowa State University, Ames, IA, USA |
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| Abstract: | Unexploded ordnance (UXO) site characterization must consider both how the contamination is generated and how we observe that
contamination. Within the generation and observation processes, dependence structures can be exploited at multiple scales.
We describe a conceptual site characterization process, the dependence structures available at several scales, and consider
their statistical estimation aspects. It is evident that most of the statistical methods that are needed to address the estimation
problems are known but their application-specific implementation may not be available. We demonstrate estimation at one scale
and propose a representation for site contamination intensity that takes full account of uncertainty, is flexible enough to
answer regulatory requirements, and is a practical tool for managing detailed spatial site characterization and remediation.
The representation is based on point process spatial estimation methods that require modern computational resources for practical
application. These methods have provisions for including prior and covariate information. |
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