Improved Digital Soils Mapping Techniques for Initial Soil Survey, Malheur County, Oregon

Soil surveys provide essential information for making land use and management decisions on publicly-owned lands in the semi-arid Great Basin. Soils maps produced with conventional mapping techniques are time-consuming, costly, and do not explicitly document the soil scientist's mental soil-landscape model. Predictive soils mapping using decision tree analysis (DTA) can increase mapping efficiency and accuracy by extracting relationships between soil types and environmental variables, applying these relationships to predict soil types for unmapped areas, and explicitly documenting the process. Currently, no research exists that examines the use of DTA for predictive soils mapping on an active Natural Resources Conservation Service (NRCS) soil survey.

This poster documents the procedure for producing and validating preliminary soils maps using DTA on the Malheur County, Southern Part Soil Survey (MCSPSS), documents interactions with survey staff, and proposes a system for predictive mapping implementation on the MCSPSS and other soil surveys. Personnel, computer hardware and software constraints currently prevent successful implementation of DTA techniques on the MCSPSS. Skepticism and resistance among field scientists are also major barriers.

The proposed system for implementation requires specific personnel: an administrative support position within NRCS who would conduct training sessions and serve as the point of contact for issue resolution; an experienced field scientist with area-specific knowledge who would carry out the DTA and produce pre-maps under the supervision of the soil survey project leader; and a GIS analyst who would provide data acquisition, data preparation and digitization support. Full documentation of procedures would be provided as an NRCS technical note. Adequate support in early stages of adoption is essential for long-term success.