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Simulation of Optical Remote-Sensing Scenes With Application to the EnMAP Hyperspectral Mission

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3 Author(s)
Luis Guanter ; Helmholtz Centre Potsdam, GeoForschungsZentrum German Res. Centre For Geosci., Potsdam ; Karl Segl ; Hermann Kaufmann

The simulation of remote-sensing images is a useful tool for a variety of tasks, such as the definition of future Earth Observation systems, the optimization of instrument specifications, and the development and validation of data processing algorithms. A scene simulator for optical hyperspectral and multispectral data has been implemented in the frame of the Environmental Mapping and Analysis Program (EnMAP) mission. EnMAP is a German-built hyperspectral space sensor scheduled for launch in 2012. EnMAP will measure in the 420-2450-nm spectral range at a varying spectral sampling of 6.5-10 nm. Images will cover 30 times 30 km areas at an approximate ground sampling distance of 30 m. The EnMAP scene simulator presented in this paper is able to generate realistic EnMAP-like data in an automatic way under a set of user-driven instrumental and scene parameters. Radiance and digital numbers data are generated by five sequential processing modules which are able to produce data over a range of natural environments, acquisition and illumination geometries, cloud covers, and instrument configurations. The latter include the simulation of data nonuniformity in the spatial and spectral domains, spatially coherent and noncoherent instrumental noise, and instrument's modulation transfer function. Realistic surface patterns for the simulated data are provided by existing remote-sensing data in different environments, from dry geological sites to green vegetation areas. A flexible radiative transfer simulation scheme enables the generation of different illumination, observation, and atmospheric conditions. The methodology applied to the complete scene simulation and some sample results are presented and analyzed in this paper.

Published in:

IEEE Transactions on Geoscience and Remote Sensing  (Volume:47 ,  Issue: 7 )