Monte Carlo simulation of multiple photon scattering in sugar maple tree canopies

Abstract

Detecting objects hidden beneath forest canopies is a difficult task for optical remote sensing systems. Rather than relying upon the existence of gaps between leaves, as other researchers have done, our ultimate goal is to use light scattered by leaves to image through dense foliage. Herein we describe the development of a Monte Carlo model for simulating the scattering of light as it propagates through the leaves of an extended tree canopy. We measured several parameters, including the gap fraction and maximum leaf-area density, of a nearby sugar maple tree grove and applied them to our model. We report the results of our simulation in both the ground and the receiver planes for an assumed illumination angle of 80 degrees. To validate our model, we then illuminated the sugar maple tree grove at 80 degrees and collected data both on the canopy floor and at our monostatic receiver aperture. Experimental results were found to correlate well with our simulated expectations.

Design and Evaluation of Multispectral LiDAR for the Recovery of Arboreal Parameters

“…For example, North [43] suggests for Sitka spruce a leaf angle distribution, (0.15 0.20 0.18 0.15 0.13 0.09 0.05 0.03 0.02), in 10 • increments from 0 • -90 • to the LiDAR axis. For Lambertian reflectance, the reflected light intensity would be proportional to the cosine of the LiDAR to surface normal angle, but Kaasalainen and Rautiainen [44] have shown that this is not a particularly good model for individual pine needles, as Greiner et al [45] did for maple leaves. For the pine needles, there is no convenient analytic expression, but it was observed, for example, that there was a significant increase in measured needle brightness (1.13-1.79) at 0 • compared to 3 • -4 • which is suggestive of significant specularity.…”