Quantifying Surface Reflectivity for Spaceborne Lidar Missions

Spaceborne lidar missions are being studied to estimate atmospheric concentrations of CO₂, water vapour and O₃, as well as for measuring surface biophysical properties. Lidar instruments typically observe the highest possible surface reflectance due to observing in the retroreflection peak (the so-called ´hotspot´), where shadowing on the surface is minimised. The likely range of observed reflectance will determine the required dynamic range and desired signal-to-noise ratio (SNR) of such an instrument, but it is difficult to predict this range a priori. A method is presented for estimating lidar surface reflectance over a range of vegetated surface types using multi-angle, multi-spectral reflectance data. The approach is validated using radiative transfer simulations of highly detailed 3D vegetation canopy models. The method is particularly useful for testing proposed lidar instrument configurations.