Articles | Volume 7, issue 2
SOIL, 7, 525–546, 2021
SOIL, 7, 525–546, 2021
Original research article
18 Aug 2021
Original research article | 18 Aug 2021

Developing the Swiss mid-infrared soil spectral library for local estimation and monitoring

Philipp Baumann et al.

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Cited articles

Agroscope: Schweizerische Referenzmethoden der Forschungsanstalten Agroscope, avaiable at: (last access: 16 August 2021), 1996. a, b
Ambroise, C. and McLachlan, G. J.: Selection Bias in Gene Extraction on the Basis of Microarray Gene-Expression Data, P. Natl. Acad. Sci. USA, 99, 6562–6566,, 2002. a
Angelopoulou, T., Balafoutis, A., Zalidis, G., and Bochtis, D.: From Laboratory to Proximal Sensing Spectroscopy for Soil Organic Carbon Estimation – A Review, Sustainability, 12, 443,, 2020. a
Awiti, A. O., Walsh, M. G., Shepherd, K. D., and Kinyamario, J.: Soil condition classification using infrared spectroscopy: A proposition for assessment of soil condition along a tropical forest-cropland chronosequence, Geoderma, 143, 73–84,, 2008. a
Baumann, P.: philipp-baumann/simplerspec: Beta release simplerspec 0.1.0 for zenodo, Zenodo [code],, 2019. a
Short summary
We developed the Swiss mid-infrared spectral library and a statistical model collection across 4374 soil samples with reference measurements of 16 properties. Our library incorporates soil from 1094 grid locations and 71 long-term monitoring sites. This work confirms once again that nationwide spectral libraries with diverse soils can reliably feed information to a fast chemical diagnosis. Our data-driven reduction of the library has the potential to accurately monitor carbon at the plot scale.