A Simulation-Based Approach to Assess Subpixel Vegetation Structural Variation Impacts on Global Imaging Spectroscopy

Consistent and scalable estimation of vegetation structural parameters-essential to understanding forest ecosystems-is widely investigated through remote sensing imaging spectroscopy. NASA's proposed spaceborne mission, the Hyperspectral Infrared Imager (HyspIRI), will measure spectral radiance from 380 to 2500 nm in 10-nm contiguous bands with a 60-m ground sample distance (GSD) and provide a global benchmark from which future changes can be assessed. The historic foci of spectrometers have been foliar/canopy biochemistry and species classification; however, given the relatively large GSD of a spaceborne instrument, there is uncertainty as to the effects of subpixel vegetation structure on observed radiance. This paper, therefore, evaluates the linkages between the within-pixel vegetation structure and imaging spectroscopy signals at the pixel level. We constructed a realistic virtual forest scene representing the National Ecological Observatory Network (NEON) Pacific Southwest domain site. Anticipated HyspIRI data (60-m GSD) for this site were then simulated using the physics-driven Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. Both the models were first validated via comparison to overflow classic Airborne Visible/Infrared Imaging Spectrometer and NEON's imaging spectrometer (NIS). Then, to assess the impact of within-pixel: 1) tree canopy cover (CC); 2) tree positioning; and 3) distribution on large-footprint HyspIRI signals, we generated the variations of the baseline virtual forest scene and measured the anticipated spectral radiance using DIRSIG. Results indicate that HyspIRI is sensitive to subpixel vegetation structural variation in the visible to a short-wavelength infrared spectrum due to vegetation structural changes. This has implications for improving the system's suitability for consistent global vegetation structural assessments by adapting calibration strategies to account for this subpixel variation.