ABSTRACT
The spatial and statistical output from a classification procedure comprises one of the major information products on forest condition available by remote sensing; generally, a second set of forestry information products is obtained by continuous variable estimation procedures. Classification produces information on the features that are contained in the list of classes imposed on the image data; the result is typically a classification map. Continuous variable estimation produces information on features that vary continuously over the landscape depicted in imagery. The result may be a map or an image in which the tones correspond to the level or value of the feature of interest and vary over the extent of the map. The process can become more complex when continuously varying forest conditions are used in the process of classification. This is not usually a problem in conventional vegetation typing or species composition of stands; the map is derived via the usual logic of classification (Zsilinsky, 1964; Avery, 1968). But typing and compiling species composition are only two of the structural attributes of forest stands that are of interest, usually as part of a general forest inventory. Some of the other forest attributes of interest might include:
1. Forest crown closure, 2. Diameter at breast height (dbh), 3. Volume, 4. Height, 5. Stem density 6. Age, and 7. Stage of development.
