Site Harvard Hemlock Site 305Site Harvard EMS tower  The LAI estimates are impacted by changes in the occlusion effect at the different scales.  75m is considered as the appropriate scale due to the layout of the EVI scans.  Modeled G vs. G=0.5: more work is needed to define the transition between the two in intermediate sites Retrieving Leaf Area Index and Foliage Profiles through Voxelized 3-D Forest Reconstruction Using Terrestrial Full Waveform Dual-Wavelength Echidna® Lidar (DWEL) Alan Strahler 1, Xiaoyuan Yang 2, 3, Crystal Schaaf 3, Zhan Li 1, Zhuosen Wang 3, Tian Yao 4, Feng Zhao 5, Edward Saenz 3, Ian Paynter 3, Ewan Douglas 1, Supriya Chakrabarti 6, Timothy Cook 6, Jason Martel 6, Glenn Howe 6, David Jupp 7, Darius Culvenor 8, Glenn Newnham 9, Jenny Lovell 10 1 Boston University, Boston, MA, USA; 2 Sandia National Laboratory, Livermore, CA, USA; 3 University of Massachusetts Boston, Boston, MA, USA; 4 Montclair State University, Montclair, NJ, USA; 5 University of Maryland, College Park, MD, USA; 6 University of Massachusetts Lowell, Lowell, MA, USA; 7 CSIRO Marine and Atmospheric Research, Canberra ACT, Australia; 8 Environmental Sensing Systems, Melbourne, Victoria 3000, Australia; 9 CSIRO Land and Water, Clayton South, Victoria, Australia; 10 CSIRO Marine and Atmospheric Research, Hobart, Tasmania, Australia  Foliage Area Volume Density & Leaf Area Index G-functionLeaf reflectance Apparent reflectance of the point Probability of gap  Three-dimensional Forest Reconstruction  Voxelization Voxelization transform s the irregular, unorganized cloud of data points in the 3-D forest reconstruction into volumetric datasets.  Voxel Based LAI & FAVD Estimation FAVD Model for point cloud The total effective area of objects in volume V or Leaf area index: Noted: In the case of multiple observations: the average of LAI is used. Horizontal fraction of canopy cover Site IDField LAI Voxel based LAI by Diameter G=0.5 50m75m100m Hemlock4.32± EMS tower4.67± ± * Measuring and monitoring canopy biophysical parameters provide a baseline for carbon flux studies related to deforestation and disturbance in forest ecosystem. Terrestrial full-waveform lidar systems, Echidna® Validation Instrument (EVI) and its successor Dual- Wavelength Echidna® Lidar (DWEL), offer rapid, accurate, and automated characterization of forest structure (Strahler et al., 2008; Yang et al., 2013). In this study, we proposed a methodology based on voxelized 3-D forest reconstruction built from EVI and DWEL scans (Douglas et al., 2012) to directly estimate two important biophysical parameters: Leaf Area Index (LAI) and foliage profiles.  Overview  Site Characteristics Site ID Leading dominants Top canopy height (m) Mean DBH (m) Stem count density (ha –1 ) Above- ground biomass (t ha –1 ) Hemlock ± ±71234±7 EMS Tower Red maple, red oak ± ±69373±36 305Red fir ± ±401215±150 While the two instruments detected the top of the canopy pretty well, LVIS sees more upper canopy component while EVI sees more lower canopy component over the same forest area. (Profiles are compared at 75 m plot diameter.) Site Harvard Hemlock Site 305Site Harvard EMS tower  Terrestrial (EVI) vs. Airborne (LVIS) Lidar  Dual-Wavelength Echidna® Lidar (DWEL) The Dual-Wavelength Echidna ® Lidar (DWEL), the successor instrument to the EVI, emits simultaneous laser pulses at 1064 nm and 1548 nm wavelengths. DWEL scans provide the capability to separate hits of leaves from hits of trunks and branches because of the reduced response at 1548 nm due to water absorption by leaf cellular contents. Normalized Difference Index (NDI): (1064nm – 1548nm) / (1064 nm nm) 1064nm 1548 nm 1064 nm1548 nm Classification by thresholding NDI By simply thresholding NDI of each point, the range effects in the classification is largely reduced, and the trunks are differentiated from foliage/branchlets points.