NG UAV Spectral Systems and Analytics for Monitoring the Diversity and Dynamics in Vegetation Function

Remote sensing approaches used to assess vegetation function are commonly based on monthly or seasonal reflectance vegetation indices (VIs), and more recently on solar induced fluorescence (SIF), a by-product of photosynthesis which offers a strong potential for up-scaling of vegetation function directly. Currently, no single sensor can provide data at the desired temporal, spectral and spatial scales. Unmanned Aerial Vehicle (UAV) hyperspectral systems offer the potential to fill this gap at local scales by enabling high frequency measurements for spatial, diurnal and seasonal scaling of vegetation traits. Key limitations, currently precluding comparison of reflectance and SIF among different ecosystems, include solar illumination and canopy bi-directional reflectance (BRDF) effects. We will present a strategy to addresses these issues by advancing the UAV hyperspectral technology, through developing: 1) an autonomous UAV based hyperspectral system for high frequency observations of reflectance, SIF, and canopy structure; and 2) the tools required for UAV 3D reflectance and SIF data management, processing and comparative analysis. The goal of our technology development is to enable the 'integration of products from multiple instruments and acquisitions into a single, unified picture of the phenomena being studied (i.e., the dynamics of vegetation function). Our objectives are to enable the generation of science-ready datasets for assessment of vegetation traits, at the required spatial, temporal, and spectral resolution to link field, airborne and satellite observations. With this effort we would advance from operation of a single spectral system by adding a 3D Hyperspectral imaging snap-shot camera. Our focus on spectroscopy facilitates integration with the current research projects of the team supporting NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) and Multiple Sentinel/Landsat Imagery (MuSLI) programs, and is a step in preparation to support future missions such as Landsat-9, NASA's Surface Biology and Geology (SBG), Germany's Environmental Map-ping and Analysis Program (EnMAP), and European Space Administration's Chime and FLuorescence Explorer (FLEX) missions.