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000857588 037__ $$aFZJ-2018-06573
000857588 1001_ $$0P:(DE-Juel1)132190$$aMemon, Mohammad Shahbaz$$b0$$eCorresponding author$$ufzj
000857588 1112_ $$a2018 IEEE International Geoscience and Remote Sensing Symposium$$cValencia$$d2018-07-22 - 2018-07-27$$gIGARSS 2018$$wSpain
000857588 245__ $$aAutomated Analysis of Remotely Sensed Images Using the Unicore Workflow Management System
000857588 260__ $$bIEEE$$c2018
000857588 300__ $$a1128 - 1131
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000857588 520__ $$aThe progress of remote sensing technologies leads to increased supply of high-resolution image data. However, solutions for processing large volumes of data are lagging behind: desktop computers cannot cope anymore with the requirements of macro-scale remote sensing applications; therefore, parallel methods running in High-Performance Computing (HPC) environments are essential. Managing an HPC processing pipeline is non-trivial for a scientist, especially when the computing environment is heterogeneous and the set of tasks has complex dependencies. This paper proposes an end-to-end scientific workflow approach based on the UNICORE workflow management system for automating the full chain of Support Vector Machine (SVM)-based classification of remotely sensed images. The high-level nature of UNICORE workflows allows to deal with heterogeneity of HPC computing environments and offers powerful workflow operations such as needed for parameter sweeps. As a result, the remote sensing workflow of SVM-based classification becomes re-usable across different computing environments, thus increasing usability and reducing efforts for a scientist.
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000857588 7001_ $$0P:(DE-Juel1)171343$$aCavallaro, Gabriele$$b1$$ufzj
000857588 7001_ $$0P:(DE-Juel1)132123$$aHagemeier, Bjorn$$b2$$ufzj
000857588 7001_ $$0P:(DE-Juel1)132239$$aRiedel, Morris$$b3$$ufzj
000857588 7001_ $$0P:(DE-HGF)0$$aNeukirchen, Helmut$$b4
000857588 773__ $$a10.1109/IGARSS.2018.8519364
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