Description: 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 phe nological 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.

Description: Data simulation is a useful tool in preparation of new remote sensing missions since simulated data can already serve as a test bench for the development of algorithms for the scientific exploitation of future data. Monitoring of arable crops is one of the core applications of the upcoming EnMAP mission. In this study we use a spectral, spatial and temporal simulation system to generate cereal field reflectance patterns for the analysis of upcoming challenges posed by varying viewing geometry and plant phenology. Realistic EnMAP measurements with typical observation constellations were calculated by using this simulation system. The measurements can be categorised into nearly nadir observations, nearly backward scattered observations, and nearly forward scattered observations depending on the constellation sun-target-satellite. Due to this bidirectional behaviour of canopies EnMAP data have to be corrected for this effect enabling the comparison of vegetation indices (VI) or retrieval methods for biophysical parameters. In this paper a new approach is presented offering the potential for the correction of these effects demonstrated for the leaf area index (LAI). As a second application of the spectral simulation system a classification method is presented determining different cereal types and growth stages. Both examples demonstrated the need of modelling the bidirectional re- flectance distribution function (BRDF) leading to an improved identification of cereal types.