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In this work, we present a novel downscaling procedure for compositionalquantities based on the Aitchison geometry. The method is able to naturallyconsider compositional constraints, i.e. unit-sum and positivity. We show thatthe method can be used in a block sequential Gaussian simulation framework inorder to assess the variability of downscaled quantities. Finally, to validatethe method, we test it first in an idealized scenario and then apply it for thedownscaling of digital soil maps on a more realistic case study. The digitalsoil maps for the realistic case study are obtained from SoilGrids, a systemfor automated soil mapping based on state-of-the-art spatial predictionsmethods.

A novel dowscaling procedure for compositional data in the Aitchison geometry with application to soil texture data