Adjusting for nondetection in forest inventories derived from terrestrial laser scanning.

Abstract Nondetection of trees is a serious problem for the use of terrestrial laser scanning (TLS) in forest inventory applications. The use of multiple coregistered scans can reduce nondetection but may not eliminate it, and it carries substantial field and post-processing costs. We examined and extended previously developed theoretical approaches to modeling nondetection. The results suggested that tree size as well as multiple stand structural characteristics may be factors, but the theoretical models do not lend themselves to empirical estimation. We then used distance sampling techniques to identify detection probabilities and develop adjusted estimates for trees per hectare and basal area in nine forest stands in southern Norway. The results compared favorably with field estimates based on fixed-area plots. The estimated detection probabilities indicate that correction for nondetection is needed unless the search for trees is limited to very small distances from the scanner. Distance sampling appears promising when TLS is used in the context of temporary-plot forest inventories