Articles | Volume 8, issue 2
Original research article
05 Sep 2022
Original research article |  | 05 Sep 2022

How well does digital soil mapping represent soil geography? An investigation from the USA

David G. Rossiter, Laura Poggio, Dylan Beaudette, and Zamir Libohova

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Cited articles

Araujo-Carrillo, G. A., Varón-Ramírez, V. M., Jaramillo-Barrios, C. I., Estupiñan-Casallas, J. M., Silva-Arero, E. A., Gómez-Latorre, D. A., and Martínez-Maldonado, F. E.: IRAKA: The First Colombian Soil Information System with Digital Soil Mapping Products, CATENA, 196, 104940,, 2021. a
Arrouays, D., Grundy, M. G., Hartemink, A. E., Hempel, J. W., Heuvelink, G. B., Hong, S. Y., Lagacherie, P., Lelyk, G., McBratney, A. B., McKenzie, N. J., d. L. Mendonca-Santos, M., Minasny, B., Montanarella, L., Odeh, I. O., Sanchez, P. A., Thompson, J. A., and Zhang, G.-L.: GlobalSoilMap: Towards a Fine-Resolution Global Grid of Soil Properties, Adv. Agron., 125, 93–134, 2014. a, b, c
Arrouays, D., McBratney, A., Bouma, J., Libohova, Z., Richer-de-Forges, A. C., Morgan, C. L., Roudier, P., Poggio, L., and Mulder, V. L.: Impressions of Digital Soil Maps: The Good, the Not so Good, and Making Them Ever Better, Geoderma Reg., 20, e00255,, 2020. a, b, c
Batjes, N. H., Ribeiro, E., and van Oostrum, A.: Standardised Soil Profile Data to Support Global Mapping and Modelling (WoSIS Snapshot 2019), Earth Syst. Sci. Data, 12, 299–320,, 2020. a
Beaudette, D.: ncss-tech/compare-psm: PSM Comparison Code v1.0, Zenodo [code],, 2021. a
Short summary
Maps of soil properties made by machine learning techniques are increasingly applied in Earth surface process modelling and agronomy. Maps of the same area made by different methods appear quite different and also differ from field-based polygon soil survey maps. We explore these differences both visually and numerically, using methods that quantify the spatial patterns. Readers can apply the methods to their areas of interest in the USA with the supplied R Markdown scripts.