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<p>Airborne gamma-ray spectrometry is a radiometric method used in geological mapping, mineral exploration, and environmental monitoring. Interpolation of radiometric data is a key step in estimating the spatial distributions of potassium (K), equivalent uranium (eU), and equivalent thorium (eTh). Conventional interpolators, such as inverse distance weighting and minimum curvature, are widely used; however, they do not explicitly account for the local spatial structure of radiometric data and may oversmooth short-wavelength variability. We present a moving-window ordinary kriging (MW-OK) algorithm that performs local estimation within circular neighborhoods. By adapting the search neighborhood to the acquisition geometry, MW-OK provides a locally adaptive representation of radiometric gradients across geological contacts, supporting the interpretation of concentration and ternary maps. Pixel-wise comparisons with minimum-curvature grids yielded coefficients of determination greater than 0.90 for K, eU, and eTh, indicating agreement with standard gridding outputs at the domain scale. These metrics support the methodological consistency and robustness of the MW-OK implementation and indicate that differences between the two interpolation approaches arise mainly at local scales. We implemented an open-source workflow that exports standard deliverables and is directly interoperable with common geoscientific platforms, providing a practical alternative for routine processing of airborne and ground-based radiometric datasets.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月5日

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  • Dionisio Uendro Carlos,
  • César Augusto Moreira,
  • Guilherme Libardi Maestrelo

摘要

Airborne gamma-ray spectrometry is a radiometric method used in geological mapping, mineral exploration, and environmental monitoring. Interpolation of radiometric data is a key step in estimating the spatial distributions of potassium (K), equivalent uranium (eU), and equivalent thorium (eTh). Conventional interpolators, such as inverse distance weighting and minimum curvature, are widely used; however, they do not explicitly account for the local spatial structure of radiometric data and may oversmooth short-wavelength variability. We present a moving-window ordinary kriging (MW-OK) algorithm that performs local estimation within circular neighborhoods. By adapting the search neighborhood to the acquisition geometry, MW-OK provides a locally adaptive representation of radiometric gradients across geological contacts, supporting the interpretation of concentration and ternary maps. Pixel-wise comparisons with minimum-curvature grids yielded coefficients of determination greater than 0.90 for K, eU, and eTh, indicating agreement with standard gridding outputs at the domain scale. These metrics support the methodological consistency and robustness of the MW-OK implementation and indicate that differences between the two interpolation approaches arise mainly at local scales. We implemented an open-source workflow that exports standard deliverables and is directly interoperable with common geoscientific platforms, providing a practical alternative for routine processing of airborne and ground-based radiometric datasets.