Simulation of Multitemporal and Hyperspectral Vegetation Canopy Bidirectional Reflectance Using Detailed Virtual 3-D Canopy Models


The influence of plant and canopy architecture on canopy bidirectional reflectance and the bidirectional reflectance distribution function (BRDF) is the subject of this paper. To understand BRDF-influenced reflectance signals, this influence must be identified and quantified, which requires detailed knowledge concerning the structure and BRDF of the observed canopies. In situ BRDF measurements of canopies are time consuming and depend on the availability of a field goniometer. In contrast to field measurements, computer-based simulations of the canopy BRDF offer an alternative approach that considers parameter-driven setups of virtual canopies under constant illumination conditions. This paper presents the hyperspectral simulation of canopy reflectance (HySimCaR) system, which has been developed in the context of the EnMAP mission. This spectral, spatial, and temporal simulation system consists of detailed virtual 3-D cereal canopies of different phenological stages, whose geometries are linked to the corresponding spectral information. The system enables the simulation of realistic bidirectional reflectance spectra on the basis of virtual 3-D scenarios by incorporating any possible viewing position with ray-tracing techniques. The parameterization of a number of canopy structure parameters, such as phenological stage, row distance, and row orientation, enables the modeling of the bidirectional reflectance and, based on them, the approximation of the BRDF for many structurally different cereal canopies. HySimCaR has been validated with respect to structural and spectral accuracy using three cereal types, namely, wheat, rye, and barley, at 13 different phenological stages. The results show that the virtual cereal canopies are re-created in a realistic way, and it is possible to model their detailed canopy bidirectional reflectance and their BRDF using HySimCaR.

IEEE Transactions on Geoscience and Remote Sensing
Patrick Hostert
Patrick Hostert
Principal Investigator