Diagrammatic Description of Satellite Image Processing Workflow

Multiple experiments on grid based satellite imagery classification require flexible descriptions of the processing workflow. The user develops the processing workflow pattern by visual tools in terms of satellite image multi-band spectral data. Each pattern may be stored into a repository and instantiated later for a particular area and time of the satellite image. The specific processing can be scheduled for the right time and data flow. By this flexible approach the user can optimize the processing algorithm for appropriate resource configuration, image type and on-line data feeding.

[1]  Dorian Gorgan,et al.  Resource Measurements for Water Detection Algorithm in MedioGrid Architecture , 2007, Sixth International Symposium on Parallel and Distributed Computing (ISPDC'07).

[2]  Dorian Gorgan,et al.  PIMS--Multispectral Image Processing Tool for Semantic Information Detection Based on Vegetation Indices , 2006, 2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing.

[3]  T. S. Perry,et al.  Capturing climate change , 2002 .

[4]  Adam Arbree,et al.  Mapping Abstract Complex Workflows onto Grid Environments , 2003, Journal of Grid Computing.

[5]  Francine Berman,et al.  Toward a framework for preparing and executing adaptive grid programs , 2002, Proceedings 16th International Parallel and Distributed Processing Symposium.

[6]  Ken Kennedy,et al.  Scheduling strategies for mapping application workflows onto the grid , 2005, HPDC-14. Proceedings. 14th IEEE International Symposium on High Performance Distributed Computing, 2005..

[7]  Martha C. Anderson,et al.  Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans , 2004 .

[8]  K. Beven,et al.  A physically based, variable contributing area model of basin hydrology , 1979 .

[9]  John P. Morrison,et al.  WebCom-G: Middleware To Hide The Grid , 2006 .

[10]  Yong Zhao,et al.  Chimera: a virtual data system for representing, querying, and automating data derivation , 2002, Proceedings 14th International Conference on Scientific and Statistical Database Management.

[11]  George A. Gravvanis,et al.  Grid Technologies : Emerging from Distributed Architectures to Virtual Organizations , 2006 .

[12]  GilYolanda,et al.  Simplifying construction of complex workflows for non-expert users of the Southern California Earthquake Center Community Modeling Environment , 2005 .