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Analysis of Light Obstruction from Street Lighting in Road Scenes.

Authors :
Ren, Jingzhi
Li, Yongqiang
Liu, Huiyun
Li, Kanghong
Hao, Daoqian
Wang, Zhiyao
Source :
Remote Sensing. Dec2023, Vol. 15 Issue 24, p5655. 20p.
Publication Year :
2023

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
24
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
174465285
Full Text :
https://doi.org/10.3390/rs15245655