GreenGlobe

Alleviating climate anxiety by providing current information and statistical predictions of a country's future sustainability using credible data sources

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Inspiration

Issues like climate change, resource depletion, environmental inequality, and CO2 emissions have not only permeated headlines but also the minds of individuals worldwide. Environmental anxiety, a grim reality faced by many, has left a significant portion of the population grappling with feelings of fear and depression due to concerns regarding global warming.1 2

Katie Hayes, a Canadian lead author of a climate anxiety study, stated, "If we're not pairing climate change communications about the risks with the actions we can take, that can increase a lot of anxiety for people" 3. In response, we created GreenGlobe, which acknowledges the current global reality of environmental sustainability. Our platform not only offers current information but also statistical predictions of a country's future sustainability, spanning up to 50 years into the future. This way, individuals can be informed of the overall state of sustainability in different geographical regions, providing them with information to plan and adapt to the changing world.

What it does

  • Web application displaying a dynamic map, colour-coded by each country's current overall sustainability
  • Predicted future sustainability up to 50 years in the future based on past historical data
  • AI-generated overviews of each country's state of sustainability
  • Blue-orange percentage scale that dynamically changes to showcase data, accessible to those who are colourblind
  • All data displayed originating from credible sources (i.e. the UN)

How we built it

  • Vue framework for frontend
  • Cloudfare Workers and Pages
  • .Tech domain name
  • OpenAI API for text description of sustainability
  • SciPy, pandas, numpy libraries for data analysis
  • Google Colab
  • OpenLayers library for displaying a map and calculating the distance between the buyer and the seller
  • Figma for UI/UX design
Programming Languages Used: JavaScript, Python, HTML, CSS

Challenges we ran into

  • Using different map layers to colour-code the map was a troublesome process of debugging
  • There is no data with clear historical markers of what it means to be "sustainable"
  • The data sets that exists surrounding environmental and sustainability concerns have thousands of data points, including missing values, which would take longer than 37/48hrs to do sufficient data cleansing and preprocessing
  • Learning vue and using js to make the site responsive
  • Designing the overall application + the responsive percent bar below it
  • Understanding the data prediction with graph
  • Feature selection and combinations to consider

Accomplishments that we're proud of

  • Hosted first domain name and worked with the DNS
  • Established cloudflare workers and a cloudflare site without any prior cloudflare or aws experience
  • Queried OpenAI API through cloudflare successfully
  • Successfully using Vue for the first time
  • Achieved the linear graph for the data points already provided
  • Learned and worked with the python library SciPy for data analysing and extending the graph to predict further years sustainability using few data points

What we learned

  • Creating maps using OpenLayers, and its various associated features
  • Using Figma and Vue extensively

What's next for GreenGlobe

We'd like to continue working on our website, implementing features like a sliding bar for users to choose up to what year they'd like to predict a country for.
We'd like to also continue to improve to UI of the website, with features like a light-dark mode toggle. We believe that our website will be extremely useful in the real-world, and we hope that our predictions and information can help alleviate climate anxiety of individuals around the world.

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