Lidar (light detection and ranging) remote sensing has proven high accuracy/precision for quantification of forest biophysical parameters, many of which are needed for operational and ecological management. Although the significant effect of Bidirectional Scattering Distribution Functions (BSDF) on remote sensing of vegetation is well known, current radiative transfer simulations, designed for the development of remote sensing systems for ecological observation, seldom take leaf BSDF into account. Moreover, leaf directional scattering measurements are almost nonexistent, particularly for transmission. Previous studies have been limited in their electromagnetic spectrum extent, lacked validated models to capture all angles beyond measurements, and did not adequately incorporate transmission scattering. Many current remote sensing simulations assume leaves with Lambertian reflectance, opaque leaves, or apply purely Lambertian transmission, even though the validity of these assumptions and the effect on simulation results are currently unknown. This study captured deciduous broadleaf BSDFs (Norway Maple (Acer platanoides), American Sweetgum (Liquidambar styraciflua), and Northern Red Oak (Quercus rubra)) from the ultraviolet through shortwave infrared spectral regions (350-2500 nm), and accurately modeled the BSDF for extension to any illumination angle, viewing zenith, or azimuthal angle. Relative leaf physical parameters were extracted from the microfacet models delineating the three species. Leaf directional scattering effects on waveform lidar (wlidar) signals and their dependence on wavelength, lidar footprint, view angle, and leaf angle distribution (LAD) were explored using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. The greatest effects, compared to Lambertian assumptions, were observed at visible wavelengths, small wlidar footprints, and oblique interrogation angles relative to the mean leaf angle. These effects were attributed to (i) a large specular component of the BSDF in the visible region, (ii) small footprints having fewer leaf angles to integrate over, and (iii) oblique angles causing diminished backscatter due to forward scattering. Opaque leaf assumptions were seen to have the greatest error for near-infrared (NIR) wavelengths with large footprints, due to the increased multi-scatter contribution at these configurations. Armed with the knowledge from this study, researchers are able to select appropriate sensor configurations to account for or limit BSDF effects in forest lidar data.

Library of Congress Subject Headings

Optical radar; Trees--Remote sensing; Leaves--Remote sensing; Light--Scattering

Publication Date


Document Type


Student Type


Degree Name

Imaging Science (Ph.D.)

Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)


Jan van Aardt

Advisor/Committee Member

David Ross

Advisor/Committee Member

Charles Bachmann


RIT – Main Campus

Plan Codes