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GEOBOTANICAL TECHNIQUES FOR DISCRIMINATING SERPENTINE ROCK TYPES 
IN WESTERN UNITED STATES 
D. MOUAT, NASA-Ames Research Center, Moffett Field, CA, U.S.A. 
C. ELVIDGE, R. Lyon, Stanford University, Stanford, CA, U.S.A. 
Serpentine-derived soils have a significant affect on species composition, 
vegetation density, and vegetation spectral response as a result of several 
factors including low calcium/magnesium ratios and high concentrations of 
chromium, cobalt, and nickel. 
Remote sensing techniques involving airborne scanner imagery and several 
statistical and image processing techniques were used in three diverse test 
sites in western United States to discriminate vegetation parameters 
associated with serpentine rock types. 
An important area of ultramafic lithology containing economic deposits of 
chromium and nickel occurs within the Siskiyou Mountains of southwest Oregon 
and northwest California. This region of high annual precipitation is 
characterized by dense conifer vegetation on non-ultramafic volcanics and 
sedimentary rocks. The ultramafic rock types, however, are characterized 
by unique vegetation assemblages often consisting of grassland or scrubland 
types which have only a sparse conifer cover. These types are easily 
discriminated with the airborne scanner imagery employing relatively simple 
analytical techniques. More sophisticated analytical techniques, however, 
were neded to differentiate rock units (serpentine and non-serpentinized 
peridotites) from within the ultramafics based upon their vegetation char- 
acteristics. The differentiation of these rock units is important in the 
exploration of economic deposits of chromium and nickel. 
  
The other serpentine-bearing regions were examined in central California. One, 
situated near the coast, is located near Stanford University's Jaspar Ridge 
Biological Preserve. The other is located approximately 250 kilometers to the 
east in the foothills of the Sierra Nevada. In both sites, multidate airborne 
scanner imagery was useful in discriminating the vegetation associated with 
the serpentine rock types on the basis of plant phenology as well as anomalous 
vegetation occurrences. Step-wise discriminant analysis was used to select 
the best multispectral channels for discriminating the serpentine areas. On 
account of phenological changes, the best wavelengths for separating the 
rock types varied. 
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