Data Fusion

We have a number of research efforts that involve the synergistic use of technologies to achieve more than would be possible with a single technology alone. Some key fusions efforts include:

Lidar and Hyperspectral Fusion to assess forest 3-dimensional structure and physiology. Lidar data allows us to model the 3-D architecture of the crown, which provides information about tree shape, canopy gaps, and light penetration to the forest floor. This is used synergistically with reflectance data from the top of the canopy, to better estimate physiological indicators, such as foliar biochemistry, stress, etc.

IGEP INVESTIGATOR: V. THOMAS

Lidar, Synthetic Aperture Radar (SAR), and Multispectral Fusion to improve satellite-based estimates of LAI and respiration. Here, lidar data provides estimates related to height and biomass, and SAR provides measures related to forest volume which are used as predictor variables with optical indices in multivariate regression analysis to predict LAI and respiration.

IGEP INVESTIGATOR: R. WYNNE