Estimating the three dimensional structure of the harvard forest using a database driven multi-modal remote sensing technique

The global forest covers over 30% of the Earth's landmass and plays a critical role in a number of global systems including the carbon cycle. Developing methods to track the carbon flow into and out of forests is necessary to gain a complete understanding of the global carbon cycle and, in turn, its effect on the climate. Remote sensing technologies such as satellite based passive optical remote sensing and synthetic aperture radar are uniquely capable of interrogating forests. Using data fusion or synergy, we present a novel approach to estimating forest aboveground biomass and mean canopy height in heterogeneous forest regions with minimal required ancillary ground measurements. We present a dynamic database driven approach wherein a region of study is divided into stands and each stand is compared to a set of simulated forest stands. The simulated stands each contain a set of simulated fractal trees with distributions based on observed ranges within the area of study. Each stand within the region of study is examined and compared to the simulated forest stands using a measure of similarity. If a simulated stand is not found to be similar to the measured stand, an iterative process is employed wherein the most similar simulated stand is dynamically modified including its species composition and the mean canopy height and above-ground biomass within each species until a similar simulated stand is constructed. The simulated stand, regardless of if it existed previously in the set of simulated stands or if it needed to be dynamically generated, is considered a reasonable representation for the measured stand under test and its height and biomass are reported. This approach relies heavily on our sensor simulators, including our fractal-based tree geometry generator, as well as SAR, IfSAR, LiDAR, and Optical simulators. We propose to validate our approach in the Harvard Forest, a heavily studied region in central Massachusetts.