Peter B Boucher1,2, Ian Paynter3, David A Orwig4, Ilan Valencius1, Crystal Schaaf1. 1. School for the Environment, University of Massachusetts, Boston, MA, USA. 2. Department of Organismic and Evolutionary Biology (OEB), Harvard University, Cambridge, MA, USA. 3. Universities Space Research Association (USRA), GESTAR, NASA Earth Sciences, GSFC, Greenbelt, MD, USA. 4. Harvard Forest, Harvard University, Petersham, MA, USA.
Abstract
BACKGROUND AND AIMS: Terrestrial laser scanners (TLS) have successfully captured various properties of individual trees and have potential to further increase the quality and efficiency of forest surveys. However, TLS are limited to line-of-sight observations, and forests are complex structural environments that can occlude TLS beams and thereby cause incomplete TLS samples. We evaluate the prevalence and sources of occlusion that limit line-of-sight to forest stems for TLS scans, assess the impacts of TLS sample incompleteness, and evaluate sampling strategies and data analysis techniques aimed at improving sample quality and representativeness. METHODS: We use a large number of TLS s cans (761), taken across a 255,650 m 2 area of forest with detailed field survey data: the Harvard Forest Global Earth Observatory (ForestGEO) (Massachusetts, USA). Sets of TLS returns are matched to stem positions in the field surveys to derive TLS-observed stem sets, which are compared to two additional stem sets derived solely from the field survey data: a set of stems within a fixed range from the TLS and a set of stems based on two-dimensional modelling of line-of-sight. Stem counts and densities are compared between the stem sets, and four alternative derivations of area to correct stem densities for the effects of occlusion are evaluated. Representation of DBH and species, drawn from the field survey data, are also compared between the stem sets. KEY RESULTS: Occlusion from non-stem sources was the major influence on TLS line-of-sight. Transect and point TLS samples demonstrated better representativeness of some stem properties than did plots. Deriving sampled area from TLS scans improved estimates of stem density. CONCLUSIONS: TLS sampling efforts should consider alternative sampling strategies and move towards in-progress assessment of sample quality, and dynamic adaptation of sampling.
BACKGROUND AND AIMS: Terrestrial laser scanners (TLS) have successfully captured various properties of individual trees and have potential to further increase the quality and efficiency of forest surveys. However, TLS are limited to line-of-sight observations, and forests are complex structural environments that can occlude TLS beams and thereby cause incomplete TLS samples. We evaluate the prevalence and sources of occlusion that limit line-of-sight to forest stems for TLS scans, assess the impacts of TLS sample incompleteness, and evaluate sampling strategies and data analysis techniques aimed at improving sample quality and representativeness. METHODS: We use a large number of TLS s cans (761), taken across a 255,650 m 2 area of forest with detailed field survey data: the Harvard Forest Global Earth Observatory (ForestGEO) (Massachusetts, USA). Sets of TLS returns are matched to stem positions in the field surveys to derive TLS-observed stem sets, which are compared to two additional stem sets derived solely from the field survey data: a set of stems within a fixed range from the TLS and a set of stems based on two-dimensional modelling of line-of-sight. Stem counts and densities are compared between the stem sets, and four alternative derivations of area to correct stem densities for the effects of occlusion are evaluated. Representation of DBH and species, drawn from the field survey data, are also compared between the stem sets. KEY RESULTS:Occlusion from non-stem sources was the major influence on TLS line-of-sight. Transect and point TLS samples demonstrated better representativeness of some stem properties than did plots. Deriving sampled area from TLS scans improved estimates of stem density. CONCLUSIONS: TLS sampling efforts should consider alternative sampling strategies and move towards in-progress assessment of sample quality, and dynamic adaptation of sampling.