Top of atmosphere Hyperspectral image simulation through radiative transfer models

Authors
A. Mousivand
A. Mousivand
Remote sensing and GIS department, Tarbiat Modares university, Tehran, Iran
Abstract
Satellite image simulation is of paramount importance in quantitative remote sensing studies. Synthetic signals/images are used in a range of applications including; pre-launch algorithm development and performance evaluation; designing sensors for given application; and parameter retrieval through inverse modelling. Top of atmosphere sensor reaching radiance is a complex function of the interactions between solar radiation and the Earth's atmosphere and surface. The at-sensor radiance is, therefore, a combination of the surface reflectance, atmospheric effects, target’s surroundings effects plus illumination and viewing geometry. Radiative transfer models are commonly used to simulate at-sensor radiance using physical and chemical properties of the surface and atmosphere. This paper presents a modeling system for the simulation of optical hyperspectral images through the extended four-stream approach. The system is modeled at three different levels: the surface, the atmosphere and the sensor. The simulation begins with four surface reflectance factors modeled by the Soil-Leaf-Canopy radiative transfer model SLC at the top of canopy and propagate them through the effects of the atmosphere which is explained by six atmospheric coefficients, derived from MODTRAN4 radiative transfer code. The top of atmosphere radiance is then convolved with the sensor spectral and spatial response functions. Validation of the model is considered over the Barrax area in Spain, using the dataset provided during SEN3EXP campaign (2009), to simulate hyperspectral CHRIS-Proba and multispectral LANDSAT-5 imageries. Overall, comparisons between simulated and actual images demonstrated model’s capability in simulating satellite signal/image with RMSE better that 0.02 for vegetative surface reflectances.

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The Journal of Spatial Planning and Geomatics
Volume 21, Issue 4
December 2017
Pages 161-182