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Abstract

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.