Abstract

Tree volume is a key feature in forest monitoring, delivering information, such as wood availability or forest carbon balance. To date, tree volume, i.e. the total volume of the above ground woody parts of a tree, cannot be measured directly with conventional tools. Terrestrial laser scanning (TLS) offers the potential to directly measure tree volume. However, its application in forest monitoring requires a profound understanding of the precision and accuracy of retrieval approaches. In this study, we present a simulation environment for evaluating TLS application in forest inventories. We investigate the influence of understorey density, scanner placement and TLS sensor type on volume estimation of tree parts of varying diameters. Using information from 30 sample plots from the Swiss NFI to simulate 197 sample trees, we evaluate three understorey densities, five scanner locations and their combinations and three realistic and one hypothetic (geometric scanning) TLS sensor types. We show that tree volume estimates from point clouds are biased to certain extent: from about 25% for small trees to a few percent for larger trees above 40 cm diameter at breast height (DBH). Especially small tree parts (diameters < 7 cm) lack accurate and precise estimation. In small trees with 12 cm DBH they are overestimated by 110% in average with a high variation, whereas they are underestimated in large trees, i.e. with DBH ≥ 75 cm, by 50% in average. Volume estimation of small tree parts is subject to physical limits of TLS, however the estimation of volume of large tree parts could be feasible with appropriate TLS settings and field protocols. Nevertheless, tree volume estimation using TLS must be understood in greater depth before it can be applied regularly in forest inventories.

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