Visible-Near Infrared Spectra as a Proxy for Topsoil Texture and Glacial Boundaries

Spectroscopy is widely recognized as an effective tool for the analysis of soil properties. The majority of studies on the use of spectroscopy have focused on spectroscopic modeling to predict these properties. Information derived from spectra, however, can also be used to describe the soil type and how it varies across landscapes because spectra contain information on the fundamental composition of soil: its organic matter, and Fe oxide, clay and carbonate minerals, as well as on water and particle size. In this study, we used visible-near infrared (vis-NIR) spectra to describe topsoils across Denmark. We used 693 agricultural topsoil samples (0-20 cm) from the Danish soil collection and measured them with a vis-NIR spectrometer covering the spectral range between 350 and 2500 nm. We interpreted the soils by deriving the organic and texture information from the spectra. To summarize the information content in the spectra, we performed a principal component analysis (PCA). The first three principal components explained 94% of the variability in the spectra. The scores from the PCA were clustered using k-means to help with interpretation. Soil properties of the clusters were described using the mean spectrum of each class. We mapped the scores of the first three principal components and the clustered scores using ordinary kriging. Both the score maps and the spectroscopic k-means cluster map clearly reflected the general pattern of soil variability in Denmark, including the soil texture classes and the glacial origin of the landscape.