SOIL, 6, 163–177, 2020 https://doi.org/10.5194/soil-6-163-2020 © Author(s) 2020. This work is distributed under SOIL the Creative Commons Attribution 4.0 License. Soil environment grouping system based on spectral, climate, and terrain data: a quantitative branch of soil series Andre Carnieletto Dotto1, Jose A. M. Demattê1, Raphael A. Viscarra Rossel2, and Rodnei Rizzo1 1Department of Soil Science, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, SP, 13418-900, Brazil 2School of Molecular and Life Sciences, Curtin University, Perth, WA 6102, Australia Correspondence: Jose A. M. Demattê (
[email protected]) Received: 2 October 2019 – Discussion started: 20 November 2019 Revised: 14 February 2020 – Accepted: 6 April 2020 – Published: 12 May 2020 Abstract. Soil classification has traditionally been developed by combining the interpretation of taxonomic rules that are related to soil information with the pedologist’s tacit knowledge. Hence, a more quantitative ap- proach is necessary to characterize soils with less subjectivity. The objective of this study was to develop a soil grouping system based on spectral, climate, and terrain variables with the aim of establishing a quantita- tive way of classifying soils. Spectral data were utilized to obtain information about the soil, and this infor- mation was complemented by climate and terrain variables in order to simulate the pedologist knowledge of soil–environment interactions. We used a data set of 2287 soil profiles from five Brazilian regions. The soil classes of World Reference Base (WRB) system were predicted using the three above-mentioned variables, and the results showed that they were able to correctly classify the soils with an overall accuracy of 88 %.