Light pollution is an umbrella term referring to the presence of excess artificial lighting in an environment. One of the most evocative indicators of pollution is a starless night, one which should be familiar to most New Yorkers. The rise in light pollution has become associated with urbanization trends, and recent literature suggests that over 80% of the world’s population, and an even greater majority of Americans, live in areas that are at least somewhat light-polluted. However, light pollution can vary dramatically, even within New York City. We hypothesize that the severity of light pollution is positively correlated with population density; more densely-populated neighborhoods are more light polluted, and vise versa.
We measured light pollution using the Dark Sky Meter app, available through Apple mobile devices. The app supports the Globe at Night project, an initiative of the NSF, and the Loss of the Night project. These citizen science initiatives crowd-source data from amateur astronomers and the general public, using the light sensors already found in iPhone cameras. Modern iPhones use a Complementary Metal-Oxide Semiconductor, or CMOS, composed of millions of pixels. When a photo is being taken, or when the app is asked to record, the sensor activates and the pixels capture incoming light. In photography, collecting light data is useful for adjusting exposure. For astronomers, these same features allow for individuals to register the intensity of visible light from stars. When data is collected by individuals worldwide, it is possible to gain rapid impressions of differences in light pollution between different areas.
Resources:
Light Pollution – Annotated Bibliography
Light Pollution – Presentation
Sasha Jamal
December 8, 2022 — 10:27 pm
I think light pollution is something that we don’t think about and yet affects us very much. I am also surprised by your results! I would have thought that you would have seen a positive correlation between light density and population, but your results show otherwise. Do you think for future research multiple parts of each neighborhood should be assessed at once instead of just one part? What was the selection process for the 5 neighborhoods you chose? Also, were the measurements taken on the same day?