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The colluvium and alluvium problem: Historical review and current state of definitions

Miller, B.A. and J. Juilleret. The colluvium and alluvium problem: Historical review and current state of definitions. Earth-Science Reviews 209: 103316. doi: 10.1016/j.earscirev.2020.103316.

Comparing Uganda’s indigenous soil classification system with World Reference Base and Soil Taxonomy

Kyebogola, S., C.L. Burras, B.A. Miller, O. Semalulu, R.S. Yost, M.M. Tenywa, A.W. Lenssen, P. Kyomuhendo, C. Smith, C.K. Luswata, M.J. Gilbert Majaliwa, L. Goettsch, C.J. Pierce Colfer, R.E. Mazur. Comparing Uganda’s indigenous soil classification system with World Reference Base and Soil Taxonomy. Geoderma Regional. doi: 10.1016/j.geodrs.2020.e00296.

Geomorphometric segmentation of complex slope elements to improve soil mapping in southeast Brazil

Marques, K., J.A. Demattê, B.A. Miller, and I. Lepsch. Geomorphometric segmentation of complex slope elements to improve soil mapping in southeast Brazil. Geoderma Regional 14: e00175. doi: 10.1016/j.geodrs.2018.e00175.

Physiographic Regions of Iowa (Shapefile)

The state of Iowa contains diverse landscapes, each with subtle but impactful differences in their physical characteristics. This data set builds on the previously established landform regions of Iowa (Prior, 2000). All boundaries have been refined based on spatial data sets that become available since Prior (2000). Most importantly, this data set introduces subregions that …Continue reading “Physiographic Regions of Iowa (Shapefile)”

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”

Surficial Geology of Wisconsin

This raster is a highly detailed map of geologic materials at the surface (delineations made from maps at 1:24,000 to 1:12,000 scale). The smaller extent maps were merged together by USDA-NRCS to produce the gSSURGO spatial database, covering the entire state of Wisconsin at a 10m resolution. The gSSURGO map was then interpreted by Iowa …Continue reading “Surficial Geology of Wisconsin”

Surficial Geology of Michigan

This raster is a highly detailed map of geologic materials at the surface (delineations made from maps at 1:24,000 to 1:12,000 scale). The smaller extent maps were merged together by USDA-NRCS to produce the gSSURGO spatial database, covering the entire state of Michigan at a 10m resolution. The gSSURGO map was then interpreted by Iowa …Continue reading “Surficial Geology of Michigan”

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