A test set containing 50,000 isols based on an automated tree delineation of 40 cm multispectral airborne imagery of a diverse temperate-boreal forest site was used. Isolations representing single trees or several trees were the focus, as opposed to cases where a tree is split into several isols. For eight shape classes from regular through to convolute, shape classification accuracy was in the order of 62%; simplifying to six classes accuracy was 83%. Shape type did give an indication of the type of remediation and there were 6% false alarms (i.e., isols classed as needing remediation but did not). Alternately, there were 5% omissions (i.e., isols of regular shape and not earmarked for remediation that did need remediation).
The usefulness of the concept of identifying poor delineations in need of remediation was demonstrated and one suite of methods developed and shown to be effective.