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The distribution of laser pulses within conifer forest trees and canopies are examined by varying the rate of laser pulse emission and the inherent laser pulse properties (laser pulse energy, pulse width, pulse length, and roll-over or trigger time). In this study, an Optech, Inc. ALTM 3100 airborne lidar is used, emitting pulses at 50 kHz and 100 kHz, allowing for changes in laser pulse characteristics while also keeping all other survey parameters equal. We found that: 1. Pulses and associated characteristics emitted at 50 kHz penetrated further into the canopy than 100 kHz for a significant number of individual trees. 2. At tall tree plots with no understory, pulses emitted at 50 kHz penetrated further into the canopy than 100 kHz for a significant number of plots. 3. For plots with significant understory and shorter trees, pulses emitted at 100 kHz penetrated further into the canopy than 50 kHz. We suspect that this may be due, in part, to canopy openness. Laser pulse energy and character differences associated with different laser pulse emission frequencies are likely a contributing factor in laser pulse penetration through the canopy to the ground surface. Efforts to understand laser pulse character influences on canopy returns are important as biomass and vegetation structure models derived from lidar are increasingly adopted. [ABSTRACT FROM AUTHOR]

An evaluation of airborne lidar (Light Detection And Ranging) technology for snow depth mapping beneath different forest canopy covers (deciduous, coniferous, and mixed) is presented. Airborne lidar data were collected for a forested study site both prior to and during peak snowpack accumulation. Manual field measurements of snow depth were collected coincident with the peak snowpack lidar survey, and a comparison between field and lidar depth estimates was made. It was found that (1) snow depth distribution patterns can be mapped by subtracting a ‘bare-earth’ DEM from a ‘peak snowpack’ DEM, (2) snow depth estimates derived from lidar data are strongly related to manual field measures of snow depth, and (3) snow depth estimates are most accurate in areas of minimal understory. It has been demonstrated that airborne lidar data provide accurate snow depth data for the purpose of mapping spatial snowpack distribution for volume estimations, even under forest canopy conditions. [ABSTRACT FROM AUTHOR]