A Method for Mapping Vegetation Utilizing Multivariate Statistical Techniques

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Abstract
Principal component analysis and stepwise discriminant analysis were used to map the vegetation of a Ranch on the Texas Coastal Plains [USA] into 5 vegetion types based on relative frequency data of the major plant species. These 5 types were shown to be subdivisions of 2 plant communities previously reported for the area by researchers using conventional mapping techniques. In addition to separating the 5 types and classifying the 140 sample points into their respective types, the technique provided a key for field separation of the types based on 3 vegetative variables and provided indicator species values for rapid field identification of the types. The technique is presented as a means of mapping vegetation with a minimum of human bias, a maximum of repeatability and information content, and maximum applicability.

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