VEGNET - a novel terrestrial laser scanner for daily monitoring of forest canopy dynamics

Thursday, 17 December 2015
Poster Hall (Moscone South)
Stefan K Arndt1, Anne Griebel2, Glenn Newnham3, Darius Culvenor3 and Lauren T. Bennett4, (1)University of Melbourne, Parkville, Australia, (2)University of Melbourne, Parkville, VIC, Australia, (3)CSIRO Land and Water, Clayton South, Australia, (4)University of Melbourne, School of Ecosystem and Forest Sciences, Creswick, Australia
Leaf area index (LAI) or plant area index (PAI) are commonly used to represent canopy structure and dynamics, but daily estimation of these variables using traditional ground-based methods is impractical and prone to multiple errors during data acquisition and processing. Existing terrestrial laser scanners can provide accurate representation of forest canopy structure, but the sensors are expensive, data processing is complex, and measurements are typically confined to a single event, which severely limits their utility in the interpretation of canopy trends indicated by remotely sensed data. We tested a novel, low-cost terrestrial laser scanner for its capacity to provide reliable and successive assessments of canopy PAI in an evergreen eucalypt forest. Daily scans were made by three scanners at one forest site over a three-year period, providing mostly consecutive estimates of PAI, and of vertical structure profiles (as Plant Area Volume Density, PAVD). Data filtering, involving objective statistical methods to identify outliers, indicated that scan quality was adversely affected by moist weather and moderate wind speeds (>4 m s-1), suggesting limited utility in some forest environments. We found strong agreement between lidar-derived PAI estimates, and those from monthly hemispherical images (±0.1 PAI); with both methods indicating mostly stable PAI over multiple seasons. The PAVD profiles from the laser scanner indicated that leaf flush in the upper canopy concomitantly balanced leaf loss from the middle canopy in summer, which was consistent with measured summer peaks in litter fall. This clearly illustrated the advantages of three-dimensional lidar data over traditional two-dimensional PAI estimates in monitoring tree phenology, and in interpreting changes in canopy reflectance as detected by air- and space-borne remotely sensed data.