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Published in Soil Sci Soc Am J 42:768-771 (1978)
© 1978 Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
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Map Unit Composition Assessment Using Drainage Classes Defined by Landsat Data1

F. R. Kirschner, S. A. Kaminsky, R. A. Weismiller, H. R. Sinclair and E. J. Hinzel2

ABSTRACT

Soil survey map units are designed such that the dominant soil represents the major proportion of the unit. At times, soil mapping delineations do not adequately represent conditions as stated in the map unit descriptions. Digital analysis of Landsat multispectral scanner (MSS) data provides a means of accurately delineating and quantifying soil map unit composition.

Digital analysis of Landsat MSS data collected on 9 June 1973 was used to prepare a spectral map for a 430-ha area in Clinton County, Indiana. Sixteen spectral classes were defined, representing 12 soil and 4 vegetation classes. The 12 spectral soil classes correlated with soil drainage characteristics and were grouped into four drainage classes. The four spectral vegetation classes were grouped for convenience into one vegetation class.

The soil delineations produced using these groupings were compared to a conventionally prepared soil map. Three map units were investigated in detail: (i) Mahalasville silty clay loam, poorly drained; (ii) Reesville silt loam, 0 to 2% slopes, somewhat poorly drained; and (iii) Xenia silt loam, 2 to 6% slopes, eroded, moderately well drained.

Results indicate that soil drainage characteristics can be identified. Correlation of drainage characteristics with soil series allows for the composition of soil map units to be accurately ascertained.


NOTES

1 This work was accomplished under the National Aeronautics and Space Administration, Office of University Affairs, Grant no. NGL-15-005-186. Journal Paper no. 6690, Purdue University, Agric. Exp. Stn.

2 Soil Scientist, USDA/Soil Conservation Service; Graduate Research Assistant, and Research Agronomist, Agronomy Dep., Lab. for Applications of Remote Sensing, Purdue University, West Lafayette, IN 47906; State Soil Scientist, Indiana, USDA/Soil Conservation Service, Indianapolis; and Graduate Research Assistant, Agronomy Dep., Lab. for Applications of Remote Sensing, Purdue Univ., W. Lafayette, Ind., respectively.

Received for publication September 29, 1977. Accepted for publication June 6, 1978.







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Copyright © 1978 by the Soil Science Society of America.