Remote Sensing (Dec 2023)

Analysis of Light Obstruction from Street Lighting in Road Scenes

  • Jingzhi Ren,
  • Yongqiang Li,
  • Huiyun Liu,
  • Kanghong Li,
  • Daoqian Hao,
  • Zhiyao Wang

DOI
https://doi.org/10.3390/rs15245655
Journal volume & issue
Vol. 15, no. 24
p. 5655

Abstract

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As urban greenery improves and the ecological environment is continuously optimized, road facilities are also impacted to varying degrees. For example, as vegetation grows, it causes varying degrees of obstruction to the lighting facilities on the roads. This article is based on vehicle-mounted LiDAR data and focuses on the point cloud data characteristics of different objects. Using appropriate modeling techniques, it accurately models road surfaces, green belts, streetlights, and other objects. On the Lumion platform, this system creates a 3D visualization of road scenes and examines the interplay between objects and lighting space, analyzing lit areas. Leveraging the precise 3D spatial relationships found in point clouds, it determines the effective illumination area on the ground from streetlights after object obstruction, comparing it to the theoretical illumination area. This not only visualizes the road scene but also quantifies the lighting obstruction rate. Furthermore, it assesses the lighting conditions in road scenes based on illuminance distribution, offering scientific insights and suggestions for enhancing road lighting.

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