Lights, Camera, Travel!

The satellite image of an “illuminated” India that emerges every Diwali on social media to depict how the whole country was lit up in celebration is all too familiar to most of us. However, the fact that night time lights in satellite imagery are used to imply celebration and jostling social activity leads one to wonder, could this data be used for something other than WhatsApp forwards?

Night-light trend during Christmas season in Moscow, Russia.

For all my boomers out there, the answer is YES. Extensive research has been conducted on how we can use night-light data as an indicator for current GDP, economic development, night time activity etc., especially for areas where data is sparse and hard to collect such as underdeveloped parts of Africa and North Korea.

Here at Kawa, we’re all a bunch of globe-trotters. However, since 2020 threw a wrench in our travel plans, we wasted no time trying to figure out when and where we can go next. And sure enough, we figured a way out of our quarantine slump using the VIIRS Night-light data by NASA.

The idea is to use night light data as an indicator of social activity and simultaneously gather data about the number of restaurants, transit stations, and other economical businesses in the relevant area. There are several sources that can be used for that information, Kawa recommends checking out Google’s Places API. Coupling the two leads to a decent estimate of how much social activity occurs in a particular area, since areas with high counts of night lights and businesses like restaurants means that the area is socially thriving and busy. Consider this similar to how your mom knows you’re awake and raving, simply by the light emanating from under your bedroom door. Another way to go about this is to pick commercial spaces in the destination of your choice and track the nightlight trends. For example, here is a snippet of the night light trends in Connaught Place, New Delhi. Note the decline observed in the months of April till August, indicating the effects of the lockdown imposed by the Indian Government.

Drop in night-light values during lockdown in New Delhi, India.

Night light data isn’t just used to locate hubs of social activity, it can also help track movement patterns and even ensure safety. For solo travellers, especially all the single ladies, safety is a prime concern. This data can help eliminate all the possible shady places one might end up in otherwise. For instance, the night lights in a particular area can be analysed and if the value is below a certain threshold, it can be flagged. This will result in selection of places that are not just socially buzzing, but also well-illuminated, hereby guaranteeing a certain level of safety. The inverse relation between street lighting and crime has been well established by many studies. For Among Us players, think of all the kills an impostor pulls off during a lights sabotage. Better lighting also leads to fewer road accidents. Political and social unrest too can be mapped using this data, helping us to understand which routes and places to avoid (or head towards; we see you advocates). A sudden increase or decrease in night light of a particular area can be marked as heavy movement and can aid in understanding complex human interactions like group meetings, protests, marches, etc.

Night-light data is just a part of the puzzle that will ultimately lead to your best travel experience. There’s more where this came from; we are continuously updating our Signal catalogue and will be back soon with more signals that will enrich your post quarantine escapades!

To make travel more efficient using NTL, sign up to https://developers.kawa.space.

References:

  1. Night-time Luminosity: Does it Brighten Understanding of Economic Activity in India?
  2. Improved street lighting and crime prevention
  3. Major study finds outdoor lighting cut crime by 39%
  4. Improving Street Lighting to Reduce Crime in Residential Areas

Written by - Manya Chadha
Manya
Manya works as a Data Science Associate at Kawa Space and occasionally writes a blog about her work. When she’s not dealing with data, she likes to travel, read fiction, listen to music and watch game streams on YouTube. She aspires to get a full 8 hours of sleep one day.