Abstract
AbstractComputer pattern recognition techniques were used to discriminate soil information from the Landsat Thematic Mapper (TM) and the French Systeme Probatoire d'Observation de le Terre (SPOT) satellite data on a native prairie near Manhattan, KS. Digital Elevation Model (DEM) data were merged to Landsat TM and SPOT data to delineate soil mapping units within the study area. Soil mapping units from a conventional soil survey were compared with a classified soil spectral map obtained from Landsat TM or SPOT, and DEM derived elevation, slope, and aspect data, using an overall accuracy assessment. The overall accuracy of soil spectral classes from TM and SPOT data was improved after DEM data were merged. A higher average accuracy for soil mapping units was obtained with a low frequency filtering transformation of the data. For Landsat TM data, Band 5 (middle infrared, 1.55–1.75 µm) was most useful for soil information extraction, and a higher overall accuracy was obtained in the dormant season compared with the accuracy in the growing season. The overall accuracy (about 57%) from SPOT data was slightly higher than the accuracy (about 53%) from Landsat TM at a similar wavelength range. Our results indicate that high resolution Landsat TM and SPOT satellite data can be used to aid second‐order soil surveys in areas where the dominant land use is rangeland.
Published Version
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