D. Feld, J. Garcke, J. Liu, E. Schricker, T. Soddemann, and Y. Xue.
Energy-Efficiency and Performance Comparison of Aerosol Optical
Depth Retrieval on Distributed Embedded SoC Architectures.
In M. Griebel, A. Schüller, and M. A. Schweitzer, editors,
Scientific Computing and Algorithms in Industrial Simulations: Projects and
Products of Fraunhofer SCAI, pages 341-358. Springer International
Publishing, Cham, 2017.
[ bib | DOI | http | .pdf 1 ]
The Aerosol Optical Depth (AOD) is a significant optical property of aerosols and is applied to the atmospheric correction of remotely sensed surface features as well as for monitoring volcanic eruptions, forest fires, and air quality in general, as well as gathering data for climate predictions on the basis of observations from satellites. We have developed an AOD retrieval workflow for processing satellite data not only with ordinary CPUs but also with parallel processors and GPU accelerators in a distributed hardware environment. This workflow includes pre-processing procedures which are followed by the runtime dominating main retrieval method.