Database Design for High-Resolution LIDAR Topography Data

  • Viswanath Nandigam
  • Chaitan Baru
  • Christopher Crosby
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6187)


The advent of high-resolution mapping technologies such as airborne Light Detection and Ranging (LIDAR) has revolutionized the study of processes acting on the earth’s surface. However, the massive volumes of data produced by LIDAR technology pose significant technical challenges in terms of the management and web-based distribution of these datasets. This paper provides a case study in the use of relational database technology for serving large airborne LIDAR “point cloud” datasets, as part of the National Science Foundation funded OpenTopography facility. We have experimented with the use of spatial extensions in the database as well as implementation solutions from a single partition database on a supercomputer resource to a multi-partition implementation on a shared-nothing commodity cluster for management of these terabyte scale datasets. We also describe future directions being pursued to support binary data formats and for scaling to larger system configurations.


Lidar Data Spatial Index Point Cloud Data Spatial Query Query Window 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Viswanath Nandigam
    • 1
  • Chaitan Baru
    • 1
  • Christopher Crosby
    • 1
  1. 1.San Diego Supercomputer CenterUniversity of California San Diego 

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