Visualization of Polar Ice Cap Reduction

#hacktheplanet #react #newrelic

Feb 4 ・2 min read

What I built

A data visualization app which depicts the declining extent of the North polar ice cap melting over the past years. I built the app using React and integrated New Relic APM tool to study and observe user time on the site, page views, page load times, track the app performance and other analytics. I've deployed the app in AWS Amplify.

Category Submission:

New Year, New Resources

App Link

https://master.d1hhgentpb9r5e.amplifyapp.com/

Screenshots

UI

New Relic One
Browser Application Dashboard

Page load times & interaction

Description

The app will have projections of the polar ice cap extent from year 1979 in two different charts which helps visualize the drastic change.

Link to Source Code

Github repo: https://github.com/chilupa/polar-ice-cap

Permissive License

MIT

Background

(Why this particular app? Share some more background about how you envision this app helping the fight against the effects of climate change.)

This app gives details about what Polar ice cap melting is and what damage it had caused, will cause in future to world and also depicts the extent in two types of charts which will provoke a thought to people at what stage we are in currently.

Melting of ice caps means much more than rise in sea levels. It will also lead to a change in ocean water currents and global weather conditions. Without effective programs in place to reduce pollution, regulate greenhouse gases such as carbon dioxide, methane, nitrous oxide, the environment will have major impact.

Hope this app will help people to understand one of the world's serious environmental problem and contribute towards the change.

How I built it

(What features of New Relic did you utilize when creating this project?)

Browser Application Feature: Followed the steps that New Relic One prompted me to do. It helped me add a script file to my React app and that's it. I could see everything is plugged in within seconds 🚀 and noticed analytics like Initial page load, Front end vs Back end, page load times, page views and javascript errors.