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Title: Estimating radiological background using imaging spectroscopy

Conference ·
DOI:https://doi.org/10.1117/12.2051049· OSTI ID:1140099

Optical imaging spectroscopy is investigated as a method to estimate radiological background by spectral identification of soils, sediments, rocks, minerals and building materials derived from natural materials and assigning tabulated radiological emission values to these materials. Radiological airborne surveys are undertaken by local, state and federal agencies to identify the presence of radiological materials out of regulatory compliance. Detection performance in such surveys is determined by (among other factors) the uncertainty in the radiation background; increased knowledge of the expected radiation background will improve the ability to detect low-activity radiological materials. Radiological background due to naturally occurring radiological materials (NORM) can be estimated by reference to previous survey results, use of global 40K, 238U, and 232Th (KUT) values, reference to existing USGS radiation background maps, or by a moving average of the data as it is acquired. Each of these methods has its drawbacks: previous survey results may not include recent changes, the global average provides only a zero-order estimate, the USGS background radiation map resolutions are coarse and are accurate only to 1 km – 25 km sampling intervals depending on locale, and a moving average may essentially low pass filter the data to obscure small changes in radiation counts. Imaging spectroscopy from airborne or spaceborne platforms can offer higher resolution identification of materials and background, as well as provide imaging context information. AVIRIS hyperspectral image data is analyzed using commercial exploitation software to determine the usefulness of imaging spectroscopy to identify qualitative radiological background emissions when compared to airborne radiological survey data.

Research Organization:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-76RL01830
OSTI ID:
1140099
Report Number(s):
PNNL-SA-102365; 400913000
Resource Relation:
Conference: Proceedings of the SPIE: Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XX, May 5, 2014, Baltimore, Maryland, 9088:Article No. 90880L
Country of Publication:
United States
Language:
English