OpenTopography: a services oriented architecture for community access to LIDAR topography

COM.Geo(2011)

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摘要
High-resolution topography data acquired with LIDAR (Light Detection and Ranging) remote sensing technology have emerged as a fundamental tool for Earth science research. Because these acquisitions are often undertaken with federal and state funds at significant cost, it is important to maximize the impact of these geospatial data by providing online access to a range of potential users. The National Science Foundation-funded OpenTopography Facility hosted at the San Diego Supercomputer Center (SDSC), has developed a Geospatial Cyberinfrastructure (GCI) to enable online access to Earth science-oriented high-resolution LIDAR topography data, online processing tools, and derivative products. Leveraging high performance computational and data storage resources available at SDSC, OpenTopography provides access to terabytes of point cloud data, standard digital elevation models, and Google Earth image data, all co-located with computational resources for higher-level data processing. This paper describes the motivation, goals, and the technical details of the Services Oriented Architecture (SOA) and underlying cyberinfrastructure platform implemented by OpenTopography. The use of an SOA, and the co-location of processing and data resources are unique to the field of LIDAR topography data processing, and lays a foundation for providing an open system for hosting and providing access to data and computational tools for these important scientific data, and is an exemplar for similar large geospatial data and processing community-oriented cyberinfrastructure systems.
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关键词
important scientific data,data storage resource,community access,higher-level data processing,geospatial data,point cloud data,data resource,google earth image data,lidar topography data processing,high-resolution topography data,high-resolution lidar topography data,remote sensing,scientific data,open system,soa,service oriented architecture,digital elevation model,data processing,data storage,lidar,high resolution,point cloud
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