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Preliminary Spectral and Geologic Analysis of Landsat-4 Thematic Mapper Data, Wind River Basin Area, Wyoming

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4 Author(s)
James E. Conel ; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109 ; Harold R. Lang ; Earnest D. Paylor ; Ronald E. Alley

A Landsat-4 Thematic Mapper (TM) image covering the Wind River Basin area, Wyoming, is under evaluation for stratigraphicand structural mapping, and for assessment of spectral and spatialcharacteristics using the six visible, near-infrared, and short-wavelengthinfrared bands.The image (path 36, row 30, ID # 40128-17232) was acquired on November 21, 1982. The data were obtained from the NASA Goddard Space Flight Center in radiometrically and geometrically correctedfullscene magnetic-tape format.To estimate equivalent Lambertian surface spectral reflectance, TMradiance data must first be calibrated to remove atmospheric andinstrumental effects. Reflectance measurements for homogeneousnatural and cultural targets in the scene were acquired during the period October 27-November 3, 1983, about one year after satellite dataacquisition. Scatterplots were prepared of image DN versus reflectancefor these sites. The scatterplots show the TM sensor system response islinear for the conditions of image acquisition and for the mix of terraincover types encountered.Low TM offset and gain settings result in encoded spectral data thatdo not occupy the full dynamic range (256 gray levels) of the TM.Calibration data acquired during the study were used to calculate new gainsand offsets that would improve scanner response for Earth scienceapplications.Analysis demonstrates that principal component images provideuseful structural and stratigraphic information. Principal componentscalculated from the correlation matix result from linear transformationsof ground reflectance. In images prepared from this transform, theseparation of spectral classes is largely independent of systematicatmospheric and instrumental factors.

Published in:

IEEE Transactions on Geoscience and Remote Sensing  (Volume:GE-23 ,  Issue: 4 )