Optimising camera and flight settings for ultrafine resolution mapping of artificial night-time lights using an unoccupied aerial system
Light pollution from artificial night-time lights (ANTLs) is a global health, economic, and environmental issue. Remote sensing and unoccupied aerial systems (UASs) provide efficient and cost-effective ways to study ANTL spatial patterns and dynamics over large areas. With ultrahigh-resolution image...
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Published in | Drone systems and applications Vol. 12; pp. 1 - 11 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
NRC Research Press
01.01.2024
Canadian Science Publishing |
Subjects | |
Online Access | Get full text |
ISSN | 2564-4939 2564-4939 |
DOI | 10.1139/dsa-2023-0086 |
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Summary: | Light pollution from artificial night-time lights (ANTLs) is a global health, economic, and environmental issue. Remote sensing and unoccupied aerial systems (UASs) provide efficient and cost-effective ways to study ANTL spatial patterns and dynamics over large areas. With ultrahigh-resolution images that can identify individual light sources, UAS offers more detailed image than satellite imagery. However, standardisation and optimisation of camera and flight settings during the acquisition ANTL UAS images is lacking. The aim of this paper is to determine the camera and flight settings to capture high-quality ANTL using a DJI Matrice 300 RTK aircraft with a Zenmuse P1 camera. It emphasises the importance of selecting appropriate camera settings for high-quality ANTL images, which can benefit future research. Results show significant image quality gains when camera and flight settings are chosen appropriately in relation to the lighting conditions. We present three experiments demonstrating a range of camera settings, and we provide practical recommendations for high-quality night-time image collection. The optimal camera settings were determined to be an exposure time of 0.0166 s, ISO of 25600, and aperture of 2.97. This experiment produced outstanding results, with 85% of images having a blur extent below 0.40. |
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ISSN: | 2564-4939 2564-4939 |
DOI: | 10.1139/dsa-2023-0086 |