Library Concept and Design for LiDAR Data Processing

  • David N
  • Mallet C
  • Bretar F
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Abstract

Airborne Laser Scanning (ALS) is nowadays a very popular technology providing accurate altimetric data for remote sensing and mapping purposes. Therefore, many algorithms have been developed so far to process these data, depending on the application. Nevertheless, for researchers, it is still a challenging task to handle large amount of heterogeneous data and adapt them for their specific aim and processes. This paper reports the thoughts and the strategy developed by the MATIS laboratory of the Institut Geographique National (IGN) about an efficient lidar library design in order to tackle these issues. The specification of an efficient and versatile lidar file format is first discussed. The standard and current lidar file formats are first reviewed and a new one, dedicated to raw data processing with high feature modularity is presented. Besides, existing code components and libraries are reviewed with regard to their compatibility for research development. Modularity, availability and license conditions are here the main selection criteria. Then, differents strategies for large data set handling are summarized and extended by a new solution, both based on lidar strip and raw sensor topology. These workflows are illustrated through a UML activity diagram dedicated to 2D spatial query. Finally, the current status of the implementation of this federative software as well as the perspectives of development are sketched.

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David, N., Mallet, C., & Bretar, F. (2008). Library Concept and Design for LiDAR Data Processing. Computational Geometry, 2, 1–6. Retrieved from http://homepages.ucalgary.ca/~gjhay/geobia/Proceedings/Sessions/Session2/6703_David_Proc.pdf

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