Abstract: Using free open-source Lidar and Hyperspectral data to do ecology and conservation research? NEON makes this a possibility. Understanding the spatial distribution of vegetation diversity is crucial for ecological, conservation, and sustainability-related studies. However, continental to global scale plant diversity mapping based on occurrence data is biased by the sampling strategy. The increasing complex patterns of vegetation diversity across scales have recently been recognized, but understanding is limited. The National Ecological Observatory Network (NEON) is the first open-source continental-scale ecological observatory that combines in-situ field observations with airborne remote sensing. The intersection of instrumentation and ecosystem provides essential future opportunities for NEON to lead new types of biodiversity surveys to answer key ecological questions.

The large amount of NEON field data can be combined with site-wide coverage of Lidar and hyperspectral remote sensing provides a framework for uniquely testing the spatial distribution of biodiversity patterns. Here, we apply the Third Law of Geography to NEON Terrestrial Observational Sampling (TOS) and Airborne Observation Platform (AOP) datasets to map vegetation biodiversity and predict uncertainty in the Eastern US. The incorporation of open-source data through the NEON portal, enables our effort to test predictive modeling for regional upscaling effort highly transferrable and repeatable. Moreover, hyperspectral and Lidar mosaics at the NEON site level is a scaling bridge that allows us to develop upscaling techniques by relating high resolution airborne remote sensing variables to coarser satellite Earth observations.