Abstract
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.
This research is supported by US National Science Foundation grants: EAR-0930731, EAR-0744229, CluE-0844530.
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Nandigam, V., Baru, C., Crosby, C. (2010). Database Design for High-Resolution LIDAR Topography Data. In: Gertz, M., Ludäscher, B. (eds) Scientific and Statistical Database Management. SSDBM 2010. Lecture Notes in Computer Science, vol 6187. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13818-8_12
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DOI: https://doi.org/10.1007/978-3-642-13818-8_12
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