The recent advances in remote sensing are contributing to improve emerging applications like geographical information systems. One of the constraint in remotely-sensed images processing is the computational resources required to obtain an efficient and precise service. Parallel processing is applied in remote sensing in order to reduce spatial or temporal cost using the message passing paradigm. In this paper, we present our experiences in the design of a workbench, called DIPORSI, developed to provide a framework to perform the distributed processing of Landsat images using a cluster of workstations. We have focused in describing the results obtained in the implementation of the georeferring function on a biprocessor cluster. In addition, this work offers a set of reflections about the design of complex distributed software systems like the distributed geographic information systems are.
CITATION STYLE
Gallud, J. A., García-Consuegra, J., García, J. M., & Orozco, L. (2001). Evaluating the DIPORSI framework: Distributed processing of remotely sensed imagery. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2131, pp. 401–409). Springer Verlag. https://doi.org/10.1007/3-540-45417-9_54
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