Proposal: Visualizing the hidden”. Creating climate action through data art

  1. Proposal in one sentence: “Visualizing the hidden”. Creating climate action through data art, I will visualize key climate change data levels of air pollution, temperatures increases, CO2, rainfall next to landmarks of key cities and I will then forecast cities that will be impacted the worst and least by climate change.

Description of the project and what problem is it solving:

It is not surprising that climate change data and AI model predictions can feel highly abstract to people and has lead to overwhelming emotions and inertia. People feel helpless and are often unsure in how to take actions on climate issues especially with industry bodies and policy makers.

  1. This project will be a visualization of climate data over the last 100 years to today e.g. air quality, temperatures, rainfall and CO2 emission.
  2. The data will be visualized next to photos of global landmark e.g. Big Ben or Taj Mahal.
  3. I will then forecast cities that are impacted the worst and least by climate change 2030, 2050, 2060.

Through this visualization, climate change will not only become more relatable to people but importantly, allows them to take actions. The data art with the photos can be easily shared on social media, with industry bodies and policy makers.

This project aims to: Enables people to (i) relate to climate change data (ii) understand climate change data and forecasted impacts through Machine Learning (iii) take action with data in a visual way.

Grant Deliverables:

  • Review climate data sources and prepare for visualization.
  • Wireframes

Data sources:

  • Air quality PM2.5
  • Global temperature C
  • CO2 emissions PPM

Future Deliverables

  • Designs
  • Match photos of landmarks with climate data over time.
  • Train AI model to predict lowest and highest impacted cities.
  • Create data art NFT.

Squad:
Silentspring30, Product Manager and FastAI student.

Advisors:
Richard Blythmann, Machine Scientists

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