Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS) — ##plugins.generic.mcfnsReadingTools.readingTools##

This paper explores the information forest inventory data can produce regarding forest types that were not sampled and develops the equations necessary to define the upper confidence bounds on not-sampled forest types. The problem is reduced to a Bernoulli variable. This simplification allows the upper confidence bounds to be calculated based on Cochran (1977). Examples are provided that demonstrate how the resultant equations are relevant to creating mid-level vegetation maps by assisting in the development of statistically defensible map units.