Quantile regression as a generic approach for estimating uncertainty of digital soil maps produced from machine-learning. - Babak Kasraei; Brandon Heung; Daniel D. Saurette; Margaret G. Schmidt; Chuck E. Bulmer; William Bethel (Environ. Model. Softw., 2021)

An Extensive Field-Scale Dataset of Topsoil Organic Carbon Content Aimed to Assess Remote Sensed Datasets and Data-Derived Products from Modeling Approaches. - Ahmed Laamrani; Paul R. Voroney; Daniel D. Saurette; Aaron A. Berg; Line Blackburn; Adam W. Gillespie; Ralph C. Martin (Remote. Sens., 2022)

Assessing spatially heterogeneous scale representation with applied digital soil mapping. - Daniel R. Newman; Daniel D. Saurette; Jaclyn M. H. Cockburn; Lucian Dragut; John B. Lindsay (Environ. Model. Softw., 2023)

Evaluating the Soil Quality Index Using Three Methods to Assess Soil Fertility. - Hiba Chaudhry; Hiteshkumar Bhogilal Vasava; Songchao Chen; Daniel D. Saurette; Anshu Beri; Adam W. Gillespie; Asim Biswas (Sensors, 2024)

Deep metric learning for soil organic matter prediction: A novel similarity-based approach using smartphone-captured images. - Mojtaba Naeimi; Vishvam Porwal; Stacey Scott; Maja Krzic; Prasad Daggupati; Hiteshkumar Bhogilal Vasava; Daniel D. Saurette; Ayan Biswas; Abhinandan Roul; Asim Biswas (Comput. Electron. Agric., 2025)