Abstract

In many forest inventory applications, numerous attributes of interest must be estimated using a lookup-table or an equation (collectively referred to as a model). Stem volume, for instance is rarely directly measured in the field, but is estimated from dimensional measurements like diameter or height. Individual observations are usually aggregated for reporting purposes and may be grouped during field data collection, such as when trees are tallied by diameter or height class. Aggregation simplifies presentation of data, but the information content is reduced.

Variables such as volume, biomass, or carbon content are frequently estimated from equations. It is sometimes difficult to judge whether a given equation is applicable to a particular situation; an assessment of model quality and a consideration of the impact of model error to total error should be included during inventory planning. The selection of a particular model depends on these evaluations, as well as modeling objective and context.

Some inventories focus on assessing the state of the resource, others on the change in the resource over time. Different field procedures and sampling designs are optimum for different objectives. It is possible to utilize sampling methods to address both state and change over time, but these methods tend to be computationally complex and care must be taken to insure appropriate assessment of accuracy and precision.