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Realistic Benchmarks for Point Cloud Data Management Systems

  • Peter van OosteromEmail author
  • Oscar Martinez-Rubi
  • Theo Tijssen
  • Romulo Gonçalves
Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Lidar, photogrammetry, and various other survey technologies enable the collection of massive point clouds. Faced with hundreds of billions or trillions of points the traditional solutions for handling point clouds usually under-perform even for classical loading and retrieving operations. To obtain insight in the features affecting performance the authors carried out single-user tests with different storage models on various systems, including Oracle Spatial and Graph, PostgreSQL-PostGIS, MonetDB and LAStools (during the second half of 2014). In the summer of 2015, the tests are further extended with the latest developments of the systems, including the new version of Point Data Abstraction Library (PDAL) with efficient compression. Web services based on point cloud data are becoming popular and they have requirements that most of the available point cloud data management systems can not fulfil. This means that specific custom-made solutions are constructed. We identify the requirements of these web services and propose a realistic benchmark extension, including multi-user and level-of-detail queries. This helps in defining the future lines of work for more generic point cloud data management systems, supporting such increasingly demanded web services.

Keywords

Point Cloud Block Model Point Cloud Data Simultaneous User Retrieval Operation 
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.

Notes

Acknowledgments

We thank all the members of the project Massive Point Clouds for eSciences, which is supported in part by the Netherlands eScience Center under project code 027.012.101. Also special thanks for their assistance to Mike Horhammer, Daniel Geringer, Siva Ravada (all Oracle), Markus Schütz (developer of potree), Martin Isenburg (developer of LAStools), and to Howard Butler, Andrew Bell and the rest of PDAL developers.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Peter van Oosterom
    • 1
    Email author
  • Oscar Martinez-Rubi
    • 2
  • Theo Tijssen
    • 1
  • Romulo Gonçalves
    • 2
  1. 1.Faculty of Architecture and the Built Environment, Department OTB, Section GIS TechnologyTU DelftDelftThe Netherlands
  2. 2.Netherlands eScience CenterAmsterdamThe Netherlands

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