The improper use of artificial light causing skyglow is detrimental to many types of wildlife and potentially causes irregular human sleeping patterns. Studies have been performed to analyze light pollution on a global scale, where results have mainly been estimates and predictions. However, light pollution data on a local scale is not often available and the effects at local scale have rarely been studied. In this paper, a new way of evaluating light pollution at local scale by deploying a custom-designed autonomous light assessment drone (ALAD) is described. The autonomous light assessment drone is designed and equipped with a sky quality meter (SQM) to measure skyglow and a low-cost illuminance sensor to measure light from artificial sources. Outdoor field tests are performed at a remote site in central Utah (town of Helper, Utah) and the measured results are validated against data from lightpollutionmap.info. The sky quality meter measurements are in agreement with the estimates from the light pollution map, and the initial results demonstrate feasibility of the autonomous light assessment drone for local-scale skyglow assessment.


Autonomous Light Assessment Drone for Dark Skies Studies

Division / Sponsors: 
Dynamic Systems & Control (DSCD)

Paper Proceedings: https://asmedigitalcollection.asme.org/DSCC/DSCC2020/volume/84270

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