Scaling Forest Biometric Properties Derived From High Resolution Imagery To The Amazon Basin Using Moderate Resolution Spectral Reflectance Data
Michael William Palace University of New Hampshire (US-PI)
Recent observations from plots and eddy flux towers of carbon sink activity in Amazonian forests could be caused by recovery from disturbance, Because many or most of the currently studied forest plots were not randomly selected, and because their geographic distribution leaves vast areas unstudied, regional remote sensing data is required to understand the rate and frequency of forest disturbance in Amazonia and the linkage of disturbance to ecosystem carbon flux. We will use high resolution optical data to quantify forest structural properties including stem frequency, crown dimensions, and canopy gap fraction. We will extrapolate these estimates of forest structure from the local and regional scale to the basin scale by linking them statistically with synoptic reflectance data from moderate resolution sensors (MODIS/MISR). This will be done annually for seven years (2002- 2008) using linear and non-linear statistical methods. The resulting temporal and spatial distributions of forest structural properties will provide insight into changes in carbon cycling at regional scales.