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A huge quantity of Earth observation and geospatial data is produced daily by numerous satellites launched by several worldwide space agencies. The processing of remote sensing data requires several steps, some of which are computationally intensive. The extraction of prominent information from remote sensing data requires a coordinated use of many applications and algorithms. Sharing computational resources among different scientists represents the sole way to approach the problem in order to achieve good performance. We describe a problem solving environment for remote sensing data processing layered on grid technologies. The proposed architecture allows sharing resources among different organizations taking into account each access policy defined by the owner of the resource.