Simulating Global Dynamic Surface Reflectances for Imaging Spectroscopy Spaceborne Missions: LPJ-PROSAIL

Spectroscopic reflectance data provide novel information on the properties of the Earth's terrestrial and aquatic surfaces. Until recently, imaging spectroscopy missions were dependent mainly on airborne instruments, such as the Next Generation Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG), providing limited spatial and temporal observations. Currently, there is an emergence of spaceborne imaging spectroscopy missions, which require advances in end-to-end model support for traceability studies. To provide this support, the LPJ-wsl dynamic global vegetation model is coupled with the canopy radiative transfer model, PROSAIL, to generate global, gridded, daily visible to shortwave infrared (VSWIR) spectra (400-2,500 nm). LPJ-wsl variables are cross-walked to meet required PROSAIL parameters, which include leaf structure, chlorophyll a + b, brown pigment, equivalent water thickness, and dry matter content. Simulated spectra are compared to a boreal forest site, a temperate forest, managed grassland, a dryland and a tropical forest site using reflectance data from tower-mounted, aircraft, and spaceborne imagers. We find that canopy nitrogen and leaf-area index are the most uncertain variables in translating LPJ-wsl to PROSAIL parameters but at first order, LPJ-PROSAIL successfully simulates surface reflectance dynamics. Future work will optimize functional relationships required for improving PROSAIL parameters and include the development of the LPJ-model to represent improvements in leaf water content and canopy nitrogen. The LPJ-PROSAIL model is intended to support missions such as NASA's Surface Biology and Geology and subsequent modeled products related to the carbon cycle and hydrology. Plain Language Summary The reflectance of the land surface provides information on vegetation composition, health, and productivity. New satellite missions are designed to better capture finely resolved reflectance information using imaging spectroscopy or hyperspectral techniques. These missions require modeling support to evaluate uncertainties. Here we present a new integrated land surface model that simulates reflectance spectra from 400 to 2,500 nm at 10 nm resolution for the entire global land surface at daily resolution. The model is evaluated using tower and pathfinder hyperspectral missions. We find that the modeling approach reproduces surface reflectance and identifies areas of model and observational improvements.