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Detecting Soils under Cultural Vegetation Using Digital Landsat Thematic Mapper Data¹

ABSTRACT

Aircraft thematic mapper simulator (TMS) and Landsat-4 Thematic Mapper (TM) data from the same site were examined for their relative accuracy in separating soils of an intensely cultivated agricultural area. Data from five different dates throughout the 1982 growing season of corn (Zea mays L.) and soybeans [Glycine max (L.) Merr.] were used in this study. Soils under corn canopy were separated at the soil mapping unit level with an accuracy of 55.5% and soils under soybeans at an accuracy of 46% on the 23 June date. As these soils are similar in their physical and taxonomic classifications, frequent errors could be expected at the mapping unit level. As the vegetative cover increased, the errors also increased, which could be expected. At the subgroup level, however, and at the great group level, the classification accuracy of soil groups increased. The great group level was separable with greater than 60% accuracy throughout the growing season. The TMS data on 23 June had the highest accuracy (92.9 for corn and 75.6 for soybeans). The 3 September TM data, even with > 90% ground cover, separated the great group level with 72.5% accuracy for corn and 68% accuracy for soybeans. The results of this study indicate that the improved spectral and spatial resolution of TM offers the potential to separate important soil properties even in a region with similar soils and under a dense vegetation canopy.

¹ Contribution from Earth Sciences and Applications Div., NASA Johnson Space Center, Houston, TX 77058.

² Soil Scientist and Agronomist, respectively, NASA Johnson Space Center. Mail Code: EX4, Houston, TX 77058.

Received for publication August 11, 1983. Accepted for publication May 10, 1984.