Team members at the Pedology Lab focus primarily on the combination of how soils form, what they look like from a morphology perspective, and how they are distributed across the landscape.
All projects start with the collection and description of soil samples from the field and are most commonly used for some laboratory analysis to quantify a chemical, physical, or biological property. From there, team members use those measurements to compare some treatment effect like agricultural management on soil health or they apply those data for spatial predictions with GIS and remote sensing to predict properties at unsampled locations.
A variety of prediction models are used ranging from simple regression to machine learning in order to understand spatial and temporal patterns of soils which results in a better understanding and managing of soil resources. These spatiotemporal predictions are also applied to address other questions related to precision agriculture, wildfire prediction, surface hydrology, and other soil-water-plant dynamics.