Ray tracing for modeling of small footprint airborne laser scanning returns

Abstract

Airborne Laser Scanning (ALS) has been established as a valuable tool for the estimation of biophysical canopy variables, such as tree height and vegetation density. However, up to now most approaches are built upon empirical stand based methods for linking ALS data with the relevant canopy properties estimated by field work. These empirical methods mostly comprise regression models, where effects of site conditions and sensor configurations are contained in the models. Thus, these models are only valid for a specific study, which renders inter-comparison of different approaches difficult. Physically based approaches exist e.g. for the estimation of tree height and tree location, however systematic underestimation depending upon sampling and vegetation type remains an issue. Using a radiative transfer model that builds on the foundation of the Open-Source ray tracer povray we are simulating return signals for two ALS system settings (footprint size and laser wavelength). The tree crowns are represented by fractal models (L-systems), which explicitly resolve the position and orientation of single leafs. The model is validated using ALS data from an experiment with geometric reference targets. We were able to reproduce the effects of target size and target reflectance that were found in the real data with our modeling approach. A sensitivity study was carried out in order to determine the effect of properties such as beam divergence (0.5, 1, and 2 mrad), canopy reflectance (laser wavelength, 1064 and 1560 nm) on the ALS return statistics. Using the two laser wavelengths above, we were able to show that the laser wavelength will not significantly influence discrete return statistics in our model. It was found that first echo return statistics only differ significantly if the footprint size was altered by a factor of 4. Last return distributions were significantly different for all three modelled footprint sizes, and we were able to reproduce the effect of an increased number of ground returns for large footprint sizes. These forward simulations are a first step in the direction of physically based derivation of biophysical ALS data products and could improve the accuracy of the derived parameters by establishing correction terms.