Volume XL-3/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 535-541, 2015
https://doi.org/10.5194/isprsarchives-XL-3-W3-535-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 535-541, 2015
https://doi.org/10.5194/isprsarchives-XL-3-W3-535-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  20 Aug 2015

20 Aug 2015

AD HOC MODEL GENERATION USING MULTISCALE LIDAR DATA FROM A GEOSPATIAL DATABASE

M. Gordon, B. Borgmann, J. Gehrung, M. Hebel, and M. Arens M. Gordon et al.
  • Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB Ettlingen, Germany

Keywords: LIDAR, Database, Model, Mapping, Visualization, Urban

Abstract. Due to the spread of economically priced laser scanning technology nowadays, especially in the field of topographic surveying and mapping, ever-growing amounts of data need to be handled. Depending on the requirements of the specific application, airborne, mobile or terrestrial laser scanners are commonly used. Since visualizing this flood of data is not feasible with classical approaches like raw point cloud rendering, real time decision making requires sophisticated solutions. In addition, the efficient storage and recovery of 3D measurements is a challenging task. Therefore we propose an approach for the intelligent storage of 3D point clouds using a spatial database. For a given region of interest, the database is queried for the data available. All resulting point clouds are fused in a model generation process, utilizing the fact that low density airborne measurements could be used to supplement higher density mobile or terrestrial laser scans. The octree based modeling approach divides and subdivides the world into cells of varying size and fits one plane per cell, once a specified amount of points is present. The resulting model exceeds the completeness and precision of every single data source and enables for real time visualization. This is especially supported by data compression ratios of about 90%.