When I first looked back at the Earth, standing on the Moon, I cried.

This Big-data oriented project looks at the Earth from the night sky as observed by the VIIRS satellites. Our presence on this planet leaves a visual footprint influenced by our lifestyle, cultural, and financial habits. In this project, I try to look at, identify, and analyze the correlations between the Night Light Emissions from various regions of our planet and the region's economic activity.

Link to project GitHub:  NikhilToram/Night_Earth_Light_Analysis (github.com) 

(All sources and credits are given in the GitHub Repository linked above)

Before we dive into the core analysis part, let's dive into some key features of the project!

• Lean and Powerful: The data on which the project is being tested here has an input size of over 140 GBs! 
• Reusable and no hard coding: The project has been built in such a way that there is no hard coding of any data, information, or parameters! So you can run the project on your PC on custom regions based on your interests and objectives.
• Detailed Instructions and Guide: The Instructions on initializing the project provided on the aforementioned GitHub page give you detailed instructions on the process to initialize, use, or modify the project to your liking.
•  Objective-Driven Analytics: Employing Simple Analytical Techniques on Complex Pictographic Scientific Data. This project centers on conducting an objective analysis of intricate pictographic scientific data by employing non-complex analytics. The fundamental principle guiding the project is that data analysis should prioritize comprehension of the data's inherent nature and the insights it provides, as opposed to relying on elaborate pre-coded statistical packages. By adopting this approach, the study aims to deliver an objective-oriented exploration of the given data, facilitating a deeper understanding of its underlying patterns and implications. 

Here is the annual data of the summed 'total light intensity' or 'total brightness' in the solid line and the economy (GDP Current US$) in the dotted line. observe the close correlation between the two lines!

Here is the monthly data of the summed 'total light intensity' or 'total brightness' for the year 2022. We can look at the data from the perspective of the weather and climatic variations when being viewed in the granularity of monthly data:

(Note that due to the Satillite's systems being down the data from the months of July and August have reduced reliability. More information can be found in the Earth Observation Group's website link in the credit section)

The provided histogram curves illustrate the distribution of light intensity or brightness across different regions. The decreasing peak height of the bell curve and its forward movement can be interpreted as indicators of increasing disparity and average economic capacity, respectively, as well as reflecting the corresponding purchasing power.

In the following section, an attempt is made to infer the variation in economic activities by analyzing the top 0.5% brightest areas and comparing them to the rest of the region. By observing the stability of the brightest regions in contrast to the rest of the region, valuable insights can be gained into the extent of geographic inequalities and variations.

This section provides us with an opportunity to examine the economic activity of cities by analyzing the patterns of night lights. Such data offers a clear and straightforward means to understand and monitor the economic and cultural vitality of a city, especially in cases where conventional economic data may be insufficient or lacking. Night light patterns serve as a valuable alternative indicator for assessing economic activity at the city level.