Assessing nighttime artificial light pollution from the perspective of an unmanned aerial vehicle tilt

Assessing nighttime artificial light pollution from the perspective of an unmanned aerial vehicle tilt

Increasing artificial light at night (ALAN) impacts urban sustainability and contributes to light pollution. Nighttime satellites miss side ALAN, so drone-captured tilted images and measured illuminance are used to assess ALAN pollution within urban streets. By integrating deep learning methods, ALA...

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Bibliographic Details
Main Authors: Jiejie Wu, Liang Zhou, Deping Li, Daoquan Zhang, Tingting Jiang, Chengzhi Zong
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Geocarto International
Subjects:
UAV tilted images
artificial light at night
light pollution
illuminance
deep learning
Online Access:https://www.tandfonline.com/doi/10.1080/10106049.2025.2453631
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https://www.tandfonline.com/doi/10.1080/10106049.2025.2453631

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