OpenTopography Services Oriented Architecture Paper Accepted to COM.Geo 2011 Conference

Mar 28, 2011

A paper highlighting the Services Oriented Architecture implemented by OpenTopography to enable lidar data access and processing has been accepted for presentation at the 2nd International Conference and Exhibition on Computing for Geospatial Research and Application (COM.Geo) on May 23-25, 2011 in Washington DC. The paper, OpenTopography: A Services Oriented Architecture for Community Access to LIDAR Topography, provides an overview of the technical implementation of the OpenTopography cyberinfrastructure.


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 if 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, 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 higherlevel 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 communityoriented cyberinfrastructure systems.

The paper will be presented at the COM.Geo conference in Washington D.C. and will be published in the COM.Geo Proceedings on Computing for Geospatial Research and Application, published by the Association for Computing Machinery.