Radiometric surveys are being applied across a growing range of use cases, from mineral exploration and geological mapping to environmental investigations, tailings assessment, and soil characterisation. At the same time, smaller detectors and UAV-based surveys are changing the way radiometric data is collected and processed.
This white paper explains the role of radiometric processing in preparing gamma-ray spectrometry data for interpretation. It explores spectral smoothing using noise-adjusted singular value decomposition (NASVD), the importance of eigenvector selection, and the value of structured processing workflows for producing reliable results.
