Accuracy and uncertainty of geostatistical models versus machine learning for digital mapping of soil calcium and potassium
Author:
Publisher
Springer Science and Business Media LLC
Subject
Management, Monitoring, Policy and Law,Pollution,General Environmental Science,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s10661-022-10434-9.pdf
Reference73 articles.
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2. Arrouays, D., Lagacherie, P., & Hartemink, A. E. (2017). Digital soil mapping across the globe. In Geoderma Regional (Vol. 9, pp. 1–4). Elsevier.
3. Beguin, J., Fuglstad, G.-A., Mansuy, N., & Paré, D. (2017). Predicting soil properties in the Canadian boreal forest with limited data: Comparison of spatial and non-spatial statistical approaches. Geoderma, 306, 195–205.
4. Beven, K. J., & Kirkby, M. J. (1979). A physically based, variable contributing area model of basin hydrology/Un modèle à base physique de zone d’appel variable de l’hydrologie du bassin versant. Hydrological Sciences Journal, 24(1), 43–69.
5. Bohling, G. C. (2007). Introduction to geostatistics. Kansas Geological Survey Open File Report, 2007–26, 50.
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