Volume IV-4
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4, 67-71, 2018
https://doi.org/10.5194/isprs-annals-IV-4-67-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4, 67-71, 2018
https://doi.org/10.5194/isprs-annals-IV-4-67-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Sep 2018

19 Sep 2018

A COMPUTATIONALLY CHEAP TRICK TO DETERMINE SHADOW IN A VOXEL MODEL

B. G. H. Gorte1, K. Zhou2, C. J. van der Sande3, and C. Valk3 B. G. H. Gorte et al.
  • 1University of New South Wales, Faculty of the Built Environment, Sydney Australia
  • 2Delft University of Technology, Dept. of Geoscience and Remote Sensing, the Netherlands
  • 3NEO BV., Amersfoort, the Netherlands

Keywords: 3D City models, Voxels, Shadow, Quantitative Modelling, Simulation

Abstract. Representation of scenes on the Earth surface by using voxels is gaining attention because of its suitability for integrating heterogeneous data sources in simulations and quantitative models. Computation of shadows in such models is needed, for example, to obtain crop suitability of agricultural fields in the presence of trees and buildings, or to analyze urban heat island causes and effects. We present an efficient algorithm to compute which of the voxels in a dataset receive direct sunlight, given the solar azimuth and elevation angles. The algorithm can work with multiple (sparse and dense) voxel storage strategies.