Meyer Patrick Bohn
YOU?
Author Swipe
View article: Digital soil mapping via machine learning of agronomic properties for the full soil profile at within‐field resolution
Digital soil mapping via machine learning of agronomic properties for the full soil profile at within‐field resolution Open
Fine‐resolution maps of agronomic soil properties are essential for capturing within‐field variability, supporting precision agriculture, improving understanding of soil–crop interactions, and providing reliable inputs for agroecosystem mo…
View article: Locally enhanced digital soil mapping in support of a bottom-up approach is more accurate than conventional soil mapping and top-down digital soil mapping
Locally enhanced digital soil mapping in support of a bottom-up approach is more accurate than conventional soil mapping and top-down digital soil mapping Open
This study presents a regional digital soil mapping (DSM) product that used a locally enhanced method in support of a bottom-up approach to create spatial soil predictions that were more accurate than one of the most accurate and detailed …
Precision land surface analysis and machine learning for enhanced soil maps: Strengthening the foundation for agroecosystems research Open
Digital soil mapping (DSM) has been touted as the superior method to produce the next generation of enhanced soil maps with greater accuracy and spatial precision than traditional soil survey methods. The advancements in precision land sur…
Predicting Soil Health and Function of the Barnes Catena Using Evapotranspiration, Vegetative, Geologic, and Terrain Attributes in the Eastern Glaciated Plains of North Dakota Open
The benchmark Barnes soil series is an extensive northern Great Plains upland Hapludoll that is vital to the region. Accelerated erosion has degraded Barnes agricultural soil quality, but with unknown extent or severity. Samples from three…