A moving-window ordinary kriging approach for airborne and ground gamma-ray spectrometric data processing

Abstract Airborne gamma-ray spectrometry is a kind of radiometric method used to geological, mineral exploration and environmental mapping. Interpolation of radiometric data is a key step for estimating potassium (K), equivalent uranium (eU), and equivalent thorium (eTh) spatial distribution concentrations. Commonly used interpolators such as inverse distance weighting and minimum curvature are widely applied, but they do not explicitly model the stochastic nature of radioactive decay. We present a moving-window ordinary kriging (MW-OK) algorithm that accounts for the detector footprint by operating within locally defined circular window. This approach better preserves short-wavelength variability and sharp gradients at contacts, producing concentration and ternary maps with improved spatial resolution. We implemented a radiometric processing workflow in open-source platform (Python) that exports standard deliverables (GXF, KMZ, GeoTIFF and PNG) and is interoperable with common geoscientific platforms.