Laboratory imaging spectroscopy can be used to explore physical and chemical variations in soil profiles on a submillimetre scale. We used a hyperspectral scanner in the 400 to 1000？nm spectral range mounted in a laboratory frame to record images of two soil cores. Samples from these cores were chemically analyzed, and spectra of the sampled regions were used to train chemometric PLS regression models. With these models detailed maps of the elemental concentrations in the soil cores could be produced. Eight different spectral pretreatments were applied to the sample spectra and to the resulting images in order to explore the influence of these pre-treatments on the estimation of elemental concentrations. We found that spectral preprocessing has a minor influence on chemometry results when powerful regression algorithms like PLSR are used. 1. Introduction Soils show a high degree of horizontal and vertical variation in physical and chemical properties. Visible and near-infrared spectroscopy is an established tool to qualitatively and quantitatively characterize these properties in soil samples [1–3]. Imaging spectroscopy is an approach that simultaneously creates VIS-NIR spectra for a complete image thus enabling analyses of the spatial distribution of these properties. In most cases imaging spectroscopy is applied from above, that is, an air- or space-borne sensor looking at the soil surface. The third spatial dimension, depth, is heterogeneous on much smaller scales but is invisible to remote sensors. Spectroscopic analyses of soil profiles can be done, for example, by measuring disturbed samples taken from different depths in the laboratory or by measuring the reflectance at different depths in boreholes [4]. However with these methods only few measurements can be made so that they cannot be used for a high-resolution characterization of complete soil profiles and their spatial variability. Our alternative is to take complete soil cores and measure their reflective properties with a laboratory imaging spectrometer [5, 6]. This way the vertical distribution of soil properties can be studied from sub-millimetre to decimetre scale. Comparable examinations on geologic cores have been introduced by Kruse [7]. The soil core spectroscopic images can be used for various purposes, for example, for classifying soil types and their horizons [8] or for a characterization of the spatial heterogeneity of the soil profiles. This paper deals with the derivation of high-resolution maps of elemental concentrations in the soil profiles that can serve as a basis for soil
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