Multichannel processing for airborne gamma‐ray spectrometry

Abstract

The conventional approach to the processing of airborne gamma‐ray spectrometric data is to first sum the observed spectra over three relatively broad energy windows. These three window count rates are then processed to obtain estimates of the potassium (K), uranium (U), and thorium (Th) elemental abundances. However, multichannel spectra contain additional information on the concentrations of K, U, and Th in the source, on the distance between the source and the detector, and on the relative contribution of atmospheric radon to the observed spectrum. This information can be extracted using multichannel processing procedures. The observed spectrum is considered as the sum of three terrestrial and three background component spectra, which are determined through suitable airborne and ground calibrations. The background components can be calculated independently and removed from the observed spectra. A parametric model based on a principal component analysis of the terrestrial components as functions of simulated detector height is then used to find the effective heights at which the K, U, and Th terrestrial components best fit the background‐corrected airborne data. The component spectra for these heights are then fitted to the background‐corrected observed spectra to obtain elemental count rates. The multichannel processing results in significant reductions in the fractional errors associated with the estimated elemental count rates. For three surveys processed using the new methodology, the average deviations of the K, U, and Th elemental count rates from the estimated mean elemental count rates at each observation point are reduced by 12.4%, 26.5 %, and 20.3 %, respectively, when compared with the conventional three‐channel method. This results in a better structural resolution of small anomalies in enhanced images of the processed data.