Modeling Lidar Waveforms Using a Radiative Transfer Model

In the past, obtaining reliable measurements of key forest canopy metrics has been difficult, even after the development of remote sensing technology. Fortunately, next-generation lidar systems are proving to be useful tools for deriving critical canopy measurements, such as height, structure and biomass. These studies have all focused on empirical comparisons between basic lidar-derived and field-sampled measurements. The results of these studies have shown that lidar remote sensing instruments can successfully measure forest canopy characteristics. However, physically-based remote sensing models are necessary to more fully understand and interpret the interactions of the laser energy with the forest canopy. In this study the Geometric Optical and Radiative Transfer (GORT) model is used to model lidar waveforms. GORT is capable of modeling lidar returns from canopies with clumped multiple layers and multiple species. For this study, GORT was used to model waveforms over the Sierra National Forest in California. Field data input into GORT are a representative sample of the different vegetation types found in the forest. The modeled waveforms are then validated against actual lidar data collected by the Laser Vegetation Imaging Sensor (LVIS) which mapped the area in October 1999. By modeling lidar waveforms based on the physical principles of radiative transfer, GORT fills a missing link between the remotely sensed and actual canopy structure. The results of this study will also aid in future large-scale land surface mapping by developing a link between lidar and other remote sensing data.