Approaches for Improving Field Soil Identification

Abstract

Core Ideas The traditional dominant‐component‐based approach is not reliable for identifying soils. We developed two approaches that can be used to identify soils with mobile devices. A small set of easily collected field data could greatly improve soil identification. Use of soil survey information by non‐soil‐scientists is often limited by their inability to select the correct soil map unit component (COMP). Here, we developed two approaches that can be deployed to smartphones for non‐soil‐scientists to identify COMP from the location alone or location together with easily observed field data (i.e., slope, depth to the restrictive layer, and soil texture by depth). In addition, we also compared the two newly developed approaches with a traditional approach identifying COMP based on the dominant COMP (DC‐based approach). All three approaches were tested with the Rapid Assessment of US Soil Carbon database and the combined USDA‐ NRCS Soil Survey Geographic database and the USDA‐NRCS State Soil Geographic Database. The results indicated that the observation‐based approach performed significantly better than the other two approaches, suggesting that a small set of easy‐to‐measure site‐specific observations could significantly improve COMP identification. The location‐ and DC‐based approaches had similar low performance overall. However, the location‐based approach slightly improved identifications over the DC‐based approach for cases where (i) there were multiple possible components within the soil map unit and (ii) the components were located in close proximity to a boundary of a different soil map unit polygon. The benefit of using the location‐based approach may be greater in specific soil survey areas where topography was the major factor leading to the creation of the map unit legend.