GIScience & Remote Sensing (Aug 2020)

Mapping 3D visibility in an urban street environment from mobile LiDAR point clouds

  • Yi Zhao,
  • Bin Wu,
  • Jianping Wu,
  • Song Shu,
  • Handong Liang,
  • Min Liu,
  • Vladimir Badenko,
  • Alexander Fedotov,
  • Shenjun Yao,
  • Bailang Yu

DOI
https://doi.org/10.1080/15481603.2020.1804248
Journal volume & issue
Vol. 57, no. 6
pp. 797 – 812

Abstract

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Visibility determination is a key requirement in a wide range of national and urban applications, such as national security, landscape management, and urban design. Mobile LiDAR point clouds can depict the urban built environment with a high level of details and accuracy. However, few three-dimensional visibility approaches have been developed for the street-level point-cloud data. Accordingly, an approach based on mobile LiDAR point clouds has been developed to map the three-dimensional visibility at the street level. The method consists of five steps: voxelization of point-cloud data, construction of lines-of-sight, construction of sectors of sight, construction of three-dimensional visible space, and calculation of volume index. The proposed approach is able to automatically measure the volume of visible space and openness at any viewpoint along a street. This approach has been applied to three study areas. The results indicated that the proposed approach enables accurate simulation of visible space as well as high-resolution (1 m × 1 m) mapping of the visible volume index. The proposed approach can make a contribution to the improvement of urban planning and design processes that aim at developing more sustainable built environments.

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