Systematic background radiation variations can lead to both false positives and failures to detect an orphan source when searching using car-borne mobile gamma-ray spectrometry. The stochastic variation at each point is well described by Poisson statistics, but when moving in a background radiation gradient the mean count rate will continually change, leading to inaccurate background estimations. Airborne gamma spectrometry (AGS) surveys conducted on the national level, usually in connection to mineral exploration, exist in many countries. These data hold information about the background radiation gradients which could be used at the ground level. This article describes a method that aims to incorporate the systematic as well as stochastic variations of the background radiation. We introduce a weighted moving average where the weights are calculated from existing AGS data, supplied by the Geological Survey of Sweden. To test the method we chose an area with strong background gradients, especially in the thorium component. Within the area we identified two roads which pass through the high-variability locations. The proposed method is compared with an unweighted moving average. The results show that the weighting reduces the excess false positives in the positive background gradients without introducing an excess of failures to detect a source during passage in negative gradients. (C) 2013 Elsevier Ltd. All rights reserved.
|Journal||Journal of Environmental Radioactivity|
|Publication status||Published - 2014|
Subject classification (UKÄ)
- Environmental Sciences
- Background radiation
- Orphan source
- Mobile gamma spectrometry