Airborne geophysical surveys routinely collect data along traverse lines at sample spacing distances that are two or more orders of magnitude less than between-line separations. Grids and maps interpolated from such surveys can produce aliasing; features that cross flight lines can exhibit boudinage or string-of-beads artifacts. Boudinage effects can be addressed by novel gridding methods. Following developments in geostatistics, a nonstationary nested anisotropic gridding scheme is proposed that accommodates sampling and data anisotropy in geophysical surveys. Computation is reduced by including anchor points throughout the interpolation region that contain localized anisotropy information that is propagated throughout the survey area with a smoothing kernel. Additional anisotropy can be required at certain locations in the region to be gridded. A model selection scheme is proposed that uses Laplace approximations for determining whether increased model complexity is supported by the surrounding data. The efficacy of the method is shown using a synthetic data set obtained from satellite imagery. A pseudogeophysical survey is created from the image and reconstructed with this method. Two case histories are selected for further elucidation from airborne geophysical surveys conducted in Western Australia (WA). The first example illustrates improvement in gridding the depth of paleochannels interpreted from along-line conductivity-depth models of a regional airborne electromagnetic (AEM) survey in the Mid West WA region. The second example indicates how improvements can be made in producing grids of aeromagnetic data and inverted electrical conductivity from an AEM survey conducted in the Pilbara region. In both case histories, nested anisotropic kriging reduces the expression of boudinage patterns and sharpens crossline features in the final gridded products permitting increased confidence in interpretations based on such products.