Evaluating the Accuracy of Ensemble Machine Learning and Statistical Uncertainty: Spatial Prediction of Topsoil Thickness in Iowa

Meyer Bohn and Bradley Miller – Iowa Water Center Conference April 6-8, 2021 Abstract The objectives of this study were to assess spatial predictions of topsoil thickness from models produced from ensemble machine learning algorithms along with assessing the uncertainty estimations associated with those models. Boosting is one example of an ensemble method, which attempts …Continue reading “Evaluating the Accuracy of Ensemble Machine Learning and Statistical Uncertainty: Spatial Prediction of Topsoil Thickness in Iowa”

Digital Hillslope Position as an Alternative Method for Soil Mapping: A Case Study for Soil Surface Properties and Topsoil Thickness in Iowa

A statistical comparison of soil properties classified via Digital Hillslope Position and Floodplain algorithm vs. gSSURGO and Iowa physiographic regions.

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