Understanding the drivers of ecological change through time requires detailed, multi-dimensional information that quantifies functional and structural properties of ecosystems, from points to pixels on, below and above the ground and from local to broad, continental scales. NEON hyperspectral imagery (HSI), coupled with lidar, and extensive biological, chemical and physical ground measurements, collected across the United States, over a 30 year time period will provide a unique opportunity to understand ecological change across critical spatial and temporal scales. This talk will be an overview of the data products that NEON will provide from 428 band hyperspectral imagery to derived products that characterize vegetation structure, health and condition. It will further explore the power of these data as applied by the scientific community, when coupled with in situ data.
Results/Conclusions
Early results from comparisons between ground and remote sensing data products will be presented. Lidar derived canopy height data have been found to closely approximate in situ measured height. In contrast canopy chemistry estimates derived from hyperspectral imagery using a vegetation index approach, has a weak correlation with in situ measurements making this area well suited for further community research.