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Analysing soil variation in two dimensions with the discrete wavelet transform

Complex spatial variation in soil can be analysed by wavelets into contributions at several scales or resolutions. The first applications were to data recorded at regular intervals in one dimension, i.e. on transects. The theory extends readily to two dimensions, but the application to small sets of gridded data such as one is likely to have from a soil survey requires special adaptation. This paper describes the extension of wavelet theory to two dimensions. The adaptation of the wavelet filters near the limits of a region that was successful in one dimension proved unsuitable in two dimensions. We therefore had to pad the data out symmetrically beyond the limits to minimize edge effects.