Semantic discovery and integration of remote sensing data on grid - art. no. 67903A

With the rapid development of remote sensing technology, the available amount of remote sensing data collected by various sensors is increasing at a tremendous rate during the last decade. The large volume and high complexity of remote sensing data make the effective management and processing of mass remote sensing data a difficult technical challenge. We design and implement. a prototype system named RSDPS-G (Remote Sensing Data Processing Software based on Grid), which using the Grid technologies to provide an "open platform" for handling computing resources, data and processing services for mass remote sensing data processing. The remote sensing data management, especially data discovery and data integration, is one of the most important components of the RSDPS-G, due to the large volume and high heterogeneities of remote sensing data on Grid. However the current methods of remote sensing data management is only at the syntactic metadata level, thus can't address the semantic heterogeneity and interoperability challenges. In this paper, we present a framework for semantic discovery and integration of remote sensing data, which solving semantic heterogeneity and interoperability issues in remote sensing data management on Grid.