×

Multiscale structure of UXO site characterization: spatial estimation and uncertainty quantification. (English) Zbl 1409.62189

Summary: 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.

MSC:

62M30 Inference from spatial processes
86A32 Geostatistics
62P99 Applications of statistics

Software:

R; geoRglm
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] Barrett B, Fanning A (1999) UXO calculator: a new statistical approach for determining unexploded ordnance (UXO) density at ordnance sites. UXO Forum 1999. Atlanta, GA, 25-27 May. http://www.uxocoe.brtrc.com/UXOForumDocs/Forum99/DT_Fanning.pdf
[2] Bartlett MS (1964) The spectral analysis of two-dimensional point processes. Biometrika 51:299-311
[3] Beard LP, Wolf DA, Spurgeon B, Gamey TJ, Doll WE (2003) Rapid screening of large area magnetic data for unexploded ordnance: expanded abstract. In: Proceedings of 2003 SAGEEP symposium, San Antonio
[4] Bilisoly RL, McKenna SA (2003) Determining optimal location and numbers of sample transects for characterization of UXO Sites. SAND Report SAND2002-3962. 47 pgs. January. 2003. Sandia National Laboratories, Albuquerque
[5] Christensen OF, Ribeiro PJ Jr (2002) geoRglm-a package for generalised linear spatial models. R News 2(2):26-28. ISSN 1609-3631
[6] Christensen OF, Waagepetersen RP (2002) Bayesian prediction of spatial count data using generalised linear mixed models. Biometrics 58:280-286 · Zbl 1209.62156 · doi:10.1111/j.0006-341X.2002.00280.x
[7] Cox DR (1955) Some statistical methods connected with series of events. J R Stat Soc B 17:29-164
[8] Cressie NAC (1993) Statistics for spatial data. Wiley, New York
[9] Diggle P (2003) Statistical analysis of spatial point patterns, 2nd edn. Oxford University Press, New York · Zbl 1021.62076
[10] Diggle P, Tawn JA, Moyeed RA (1998) Model-based geostatistics (with discussion). Appl Stat 47:299-350 · Zbl 0904.62119
[11] Doll WE, Gamey TJ, Beard LP, Bell DT, Holladay JS (2003) Recent advances in airborne survey technology yield performance approaching ground-based surveys. The Leading Edge 22:420-425
[12] Gasperikova E, Beard LP (2007) Special issue on geophysics applied to detection and discrimination of unexploded ordnance. J Appl Geophys 61(3-4):165-167. State-of-the-Art UXO Detection and Characterization · doi:10.1016/j.jappgeo.2006.06.007
[13] Geosoft. 1997. Oasis Montaj data processing and analysis system for Earth science applications, chap 7, Version 4.1 User Guide. Processing Data, p 290
[14] Ihaka R, Gentleman R (1996) R: a language for data analysis and graphics. J Comput Graph Stat 5:299-314 · doi:10.2307/1390807
[15] McDonald JR, Robertson R (1996) Sensor evaluation study for use with towed arrays for UXO site characterization. In: Proceedings of SAGEEP ’96, pp 451-464
[16] MacDonald JA, Small MJ (2006) Assessing sites contaminated with unexploded ordnance: statistical modeling of ordnance spatial distribution. Environ Sci Technol 40(3):931-938 · doi:10.1021/es051168t
[17] McDonald J, Nelson H, Neece J, Robertson R, Jeffries R (1998) MTADS unexploded ordnance operations at the badlands bombing range on the pine ridge reservation, Cuny Table, SD. NRL/PU/6110-98-353
[18] Mitchell TJ, Ostrouchov G, Frome EL, Kerr GD (1997). A method for estimating occupational radiation dose to individuals, using weekly dosimetry data. Radiat Res 147:195-207 · doi:10.2307/3579421
[19] Moller J, Syversveen AR, Waagepetersen RP (1998) Log Gaussian cox processes. Scand J Stat 25:451-482 · Zbl 0931.60038 · doi:10.1111/1467-9469.00115
[20] Neyman J, Scott EL (1958) Statistical approach to problems of cosmology. J R Stat Soc B 20(1):1-43 · Zbl 0085.42906
[21] Neyman J, Scott EL (1972) Processes of clustering and applications. Stochastic point processes, statistical analysis, theory and applications. In: Lewis PAW (ed) Wiley, New York, pp 646-681
[22] Ostrouchov G, Zimmerman GP, Beauchamp JJ, Federov VV, Downing DJ (1999) Evaluation of statistical methodologies used in U.S. Army ordnance and explosive work. ORNL/TM-13588. Oak Ridge National Laboratory, Oak Ridge, September 1999, p 34
[23] Ostrouchov G, Doll WE, Wolf DA, Beard LP, Morris MD, Butler DK (2003) Spatial statistical models and optimal survey design for rapid geophysical characterization of UXO sites, Unpublished project report SERDP CU-1201
[24] Quantitech (1995a) Ordnance and explosives site statistical sampling based methodology (SiteStats) final report. Technical report 95-R-011, QuantiTech, Huntsville, 30 September
[25] Quantitech (1995b) Grid statistical sampling based methodology (GridStats), Version 1.2, User’s Manual. Huntsville. Prepared for U.S. Army Engineer Division. Huntsville. 30 September
[26] Stoyan D, Kendall WS, Mecke J (1995) Stochastic geometry and its applications, 2nd edn. Wiley, New York
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.