Using Thematic Mapper Data to Identify Contrasting Soil Plains and Tillage Practices

Landsat-5 Thematic Mapper (TM) data from 11 May 1990 for Seneca County, Ohio were used to develop TM-based probability models for classifying agricultural management practices and soil properties. Logistic regression techniques were used to relate field data for 27 fields to TM bands and indices. Field data, including tillage and drainage practices, soil plain, and soil texture, were collected from 1988 to 1990. Both soil plain and tillage logistic regression models classified 89 percent of the fields correctly. Simple ratio and normalized differences of iM bands 5 and 7 proved most useful for classifying tillage practices. TM bands 1, 2, 3, and 4 were found useful for identifying soil plain. Spectral differences were attributed to soil color differences between lake and till plain soils and surface residue differences between conservation and conventional tillage. The developed models were tested with independent data from 15 additional fields and classified 88 percent of the soil plain and 93 percent of the tillage attributes correctly. Using TM data to identify drainage practices, organic matter content, and soil texture was generally inadequate for scientific purposes.