Climate Delta

Snippet of Landing Page

Inspiration

Climate change data is often complex, fragmented, and difficult for individuals or communities to interpret. While global reports exist, most people lack localized insights into how their specific region is changing. This app bridges that gap by providing an accessible, visual way to understand local climate effects and anticipate future scenarios. It empowers users, policymakers, and researchers to make informed decisions about sustainability, infrastructure, and adaptation strategies.

What it does

This project creates an interactive climate insights app that helps users visualize and understand the impact of climate change at the county level. The app combines historical environmental data, real-time satellite imagery, and machine learning (ML) predictions to show how temperature, pollution, rainfall, and other key indicators have changed over time, as well as how they are projected to evolve over the next 10, 25, and 50 years.

How we built it

Built with React, Vercel, FastAPI, Tailwind CSS, GRU neural networks, PyTorch, and GeoPandas. APIs used: NCEI, NOAA, Google Earth Engine, Open-Meteo, OpenStreetMap.

Challenges we ran into

Connecting multiple APIs, resolving merge conflicts, managing a database in a serverless app, and working under tight time constraints.

Accomplishments that we're proud of

Learning new technologies, collaborating effectively, and successfully connecting all major components.

What we learned

How to collaborate efficiently while pushing code, adapt to new technologies quickly, and train machine learning models from scratch.

What's next for Climate Delta

Adding more secondary datasets such as CO₂, NDBI, smog, and UV data. We also plan to train a more accurate model and integrate a robust database for better scalability and performance.