Integrating deep learning with digital soil core sensing for subsurface soil image segmentation
Sabine Grunwald
This study developed a computer vision application for soil-phase segmentation and precise characterization of soil porosity, as well as for estimating soil color and fractal properties from digital images collected in undisturbed in situ soils. The multi-sensor Digital Soil Core (DSC) was used to collect microscopic soil images from four cultivated locations in California’s Central Valley, encompassing eight soil series and six soil orders. Images were extracted from video frames of profiles do