Phase II : Biomass Modeling
The biomass modeling component of this study serves dual objectives for both the North American Carbon Program (NACP) and the Forest Inventory and Analysis (FIA) program: to improve methods for quantification of forest disturbance and regrowth processes. In phase I of NAFD, we estimated the rates of forest disturbance and regrowth for 23 sample Landsat time-series stacks across the United States. In phase II of NAFD, we are furthering the characterization of forest disturbance and regrowth dynamics by integrating FIA data and the Landsat time-series data to model aboveground forest biomass dynamics for each of the sample scenes.
FIGURE: Sample biomass trajectories demonstrating the effect of curve-fitting (solid lines) on raw biomass predictions (dashed lines) for two recently disturbed FIA plots (plot-level biomass observations shown as stars).
Spatially explicit knowledge of aboveground forest biomass dynamics will ultimately aid in the characterization of carbon flux associated with forest disturbance and regrowth.
While limitations to empirical modeling of biomass using optical remote sensing data are well known, especially for a single time period, our approach hinges upon leveraging the temporal information contained within the Landsat time-series itself. Despite year-to-year variations in biomass predictions caused by model error, phenology, sun angle, and image-to-image misregistration, the trends across 20+ year trajectories of biomass are noteworthy, especially in instances of forest disturbance or regrowth. Therefore, by "smoothing" the biomass trajectories with a curve-fitting algorithm, some of this error can be mitigated and enable a more accurate evaluation of biomass dynamics.