Retrieving 3D canopy structure from synergistic analysis of multi-angle and lidar data

Recent empirical studies have shown that multi-angle data can be useful for predicting canopy height, but the physical reason for this correlation was not understood. The research presented here puts forth a physical explanation for this phenomenon. We employ the use of Radiative Transfer, more specifically canopy spectral invariants, which can decouple spectral and structural parameters in a vegetation canopy. As a case study we compare canopy heights predicted from a multivariate analysis of 28 (7 cameras* 4 bands) and LVIS canopy heights and a multivariate analysis of 7 directional escape probabilities and LVIS canopy heights. We find that the 7 directional escape probabilities can provide approximately the same amount of information about canopy height as 28 spectral/angular reflectances from AirMISR. Finally we speculate that multi-angle data does not allow for extraction of canopy height but in fact requires synergy between Lidar sensors.