‘The Sky Had No Stars’: Gurugram Student Builds Free Website To Check Light Pollution Using a Phone Photo

SkyQi is a free online platform created by Suhani Gupta to estimate the quality of a night sky. It addresses a practical problem: professional Sky Quality Meters can be expensive, while smartphones are widely available. This makes night-sky monitoring more accessible to students, amateur astronomers and community groups.

A user takes a photograph of the night sky with a smartphone and submits it to SkyQi. The platform processes the image and produces an estimate of night-sky quality. The article explains that Suhani taught herself image processing and used Python, research papers and programming libraries while developing the project.

SkyQi has grown into a citizen-science initiative, with observations from users in dozens of countries. The supplied article does not explain the platform’s exact image-processing steps, so those details cannot be stated reliably. Its broader purpose is to make changes in light pollution easier to observe and understand.

The provided article excerpt does not identify three specific features that SkyQi examines in a night-sky photograph. It says only that Suhani Gupta taught herself image processing and developed a platform that estimates night-sky quality from smartphone photos. Naming particular features would therefore go beyond the supplied source.

In general, image-based brightness tools may examine pixel brightness, exposure information and visible sky conditions. However, the excerpt does not confirm that SkyQi uses those exact features, nor does it describe its algorithm, calibration process or image requirements. They should not be presented as established facts about SkyQi.

What the article does establish is the project’s purpose. SkyQi offers an inexpensive way to collect observations without a professional Sky Quality Meter. Its citizen-science model allows people in many countries to contribute photographs and help make gradual changes in night-sky conditions easier to observe.

Suhani Gupta’s analysis found that the median Indian city had 70% higher measured night-time radiance in 2025 than in 2015. This is a large increase across a ten-year period, although the measurement describes radiance detected in satellite data rather than exactly how bright the sky looks from the ground.

She examined NASA satellite data for 50 Indian cities. Forty-seven cities recorded an increase, meaning that only three did not show a rise in her dataset. Leh had the steepest increase, at 546%, despite being known for dark skies and astronomy tourism.

These figures raise questions about changing outdoor lighting, urban growth and tourism. They do not prove that every location appears equally brighter to people standing outside. Still, the broad pattern suggests that night-time lighting deserves closer observation and discussion as Indian cities develop.

Light pollution is the excessive or poorly directed use of artificial light. It brightens the night sky and makes celestial objects harder to see. Unlike a polluted river or visible smoke, this environmental change can build gradually and remain difficult for people to notice.

Buildings, roads, commercial establishments, illuminated advertisements, streetlights and other outdoor sources can all add to the glow. Light directed upward or spreading beyond the place that needs illumination contributes to a brighter urban night. The article notes that new lighting can appear to signal safety or development, even when some of it is unnecessary or poorly directed.

The issue matters beyond stargazing. The article links artificial night lighting with effects on nocturnal wildlife, ecosystems and human exposure to darkness. Suhani’s work aims to make these changes easier to measure, understand and eventually address using accessible tools.

Satellite measurements and human experience describe related but different things. NASA satellite data can record night-time radiance across cities, but it does not directly measure how bright the sky appears to someone standing on the ground. The article explicitly warns that the two should not be treated as identical.

A satellite observes light from above across a broad area. A person’s view is shaped by the nearby environment, including buildings, roads, lamps and other sources of outdoor lighting. Haze and other atmospheric conditions can also affect what reaches the eye. These differences mean a city’s satellite value may not match every resident’s visual experience.

Suhani’s results therefore show a change in measured urban night-time radiance, not a complete ground-level description of sky brightness. Even so, the increase across 47 of 50 cities raises important questions about urban growth, tourism and outdoor lighting in India.

When artificial light brightens the night, the sky glows and celestial objects become harder to see. This directly affects astronomy. Suhani and her sister celebrate when they can spot more than seven stars from their Gurugram balcony, showing how limited visibility can become in a brightly lit city.

The article also identifies wider consequences for nocturnal wildlife, ecosystems and human exposure to darkness. It does not list specific effects on particular animals or ecosystems. Its central point is that unnecessary or poorly directed lighting changes the night environment, even when new lamps, advertisements and illuminated buildings are viewed as signs of safety or development.

The problem can be difficult to recognise because it develops gradually. Suhani is using SkyQi and satellite analysis to make the change more visible. Her findings suggest that growing urban lighting deserves attention, while her stated aim is to help people eventually address the problem.

A digital camera records light with a sensor. Each part of the sensor converts incoming light into an electrical signal, which becomes a pixel value in the image. Image-processing software can analyse those values to estimate relative brightness. This is the basic reason a photograph might serve as a low-cost measurement.

The reading can be misleading, however. Clouds may reflect or scatter nearby artificial light and make the sky appear brighter. Overexposure can make different brightness levels look similarly white, removing useful detail. Camera sensors, lenses and automatic phone settings can also respond differently, changing the image even when the actual sky is similar.

The supplied article does not describe SkyQi’s calibration or correction methods. Therefore, these are general measurement limitations, not confirmed details of its algorithm. Reliable comparisons would require consistent photography and careful handling of weather, exposure and device differences.