The National Science Foundation’s (NSF) NEON Program (National Ecological Observatory Network) has been collecting hyperspectral (380-2500nm) data over the last six years using the next generation AVIRIS (Airborne Visible InfraRed Imaging Spectrometer) imager from JPL (Jet Propulsion Laboratory). These 1m spatial resolution sensors are flown on Twin Otter aircraft (crew of 4) to provide orthorectified surface directional reflectance, at-sensor radiance, fPAR (fraction of Photosynthetically Active Radiation, LAI (Leaf Area Index), and other indices. What if the same high-quality measurements could be made via an Uncrewed Aerial Vehicle (UAV), giving scientists flexibility in scheduling, repeat observation times, and increased spatial resolution (~8cm)?
In 2019, during a calibration flight of the NEON hyperspectral imager, a Headwall co-aligned VNIR-SWIR hyperspectral imager (400-2500nm) was flown on a DJI Matrice M600 drone (at 400′ AGL) within 30 seconds of each of the Twin Otter’s five flight lines (at 3,000′ AGL). This survey area included two 10m x 10m reflectance tarps of 3% and 48% reflection, where an ASD (Analytical Spectral Devices) was used to provide ground truth data.
This presentation will show the differences between the two hyperspectral systems based on binning the reflectivity into ten 200nm wide spectral segments over the calibrated tarps, and over three fairly homogeneous surfaces, often found throughout the US. Additionally, there will be a discussion on the operational impacts of using UAV’s for gathering hyperspectral data at a much higher temporal rate than annually. This work aims to quantify the utility of drone-based hyperspectral data for ecological mapping purposes.