North American Forest Dynamics (NAFD) project is exploiting the Landsat historical record to develop a quantitative understanding of forest disturbance patterns across the conterminous U.S. The primary components of this study are:
The NAFD team, consisting of principal investigators from the University of Maryland, USFS, and NASA, has been working to accomplish this science goal as a contribution to the North American Carbon Program (NACP) since 2003, when the team first began to explore whether Landsat time series stacks (LTSS) could be combined with FIA data for this purpose. In earlier phases of this work a national sampling approach was used, mostly because of data cost and processing complexity. In this study we transformed our previous data processing and analysis approaches into a highly automated system, exploiting the newly developed NASA Ames Research Center NEX computing environment. Whereas in previous efforts we examined no more than 2000 Landsat images, in this study we are processing and analyzing over 15,000 images to produce this annual, nationwide assessment of forest disturbance history.
The results from this study will not only be published in the scientific literature but a set of national map products, including annual disturbance history, national variations in forest recovery trajectories, and nationwide analysis of the spatial-temporal patterns of underlying forest disturbance causal factors will be made available to interested users. This information is of vital importance to understanding the carbon balance of the US and the North American continent.
North American forests are thought to be a long-term sink for atmospheric carbon, with much of the sink attributed to either forest regrowth from past agricultural clearing or to woody encroachment. However, the magnitude of the North American forest sink is uncertain, because disturbance and regrowth dynamics are not well characterized or understood. Disturbance events (including harvest, fire, insect and storm damage, and disease) strongly affect carbon dynamics in many ways, including biomass removal, emissions from decaying biomass, and changes in productivity. This research should help reduce these uncertainties through integration of forest inventory data and satellite data. In addition, our approach of automating the processing and analysis steps in this study will serve as a necessary precursor to the implementation of operational national carbon monitoring system and the development of more aggressive systematic land survey missions.