Inspiration

As sea levels rise and flooding intensifies, Florida's "climate havens"—safe, elevated neighborhoods—are becoming increasingly expensive. We asked: who gets displaced when safety becomes unaffordable?

This isn't future speculation. Low-risk areas in Florida have appreciated 2.3x faster than flood-prone zones since 2017. Climate gentrification is happening now.

What it does

ClimateHaven predicts which Florida neighborhoods will gentrify due to climate change by combining:

  • FEMA flood risk data (963 ZIP codes)
  • Redfin housing prices (9.6M transactions)
  • US Census demographics (income, population, ethnicity)
  • NOAA sea level projections (1-6ft scenarios)

Our Gentrification Risk Score identifies neighborhoods with low flood risk, current affordability, and rapid price momentum—the perfect storm for displacement.

Key Findings

  • 15.2 million Floridians live in high flood-risk ZIP codes
  • Hispanic communities are twice as likely to live in gentrification hotspots
  • Only 47 affordable climate havens remain in Florida—down 40% from 2020
  • There's a -0.34 correlation between income and flood risk: wealth already equals safety

How we built it

We used Zerve to rapidly iterate across datasets, test hypotheses, and deploy a production-ready Streamlit application. The workflow included data cleaning, feature engineering, risk score modeling, and interactive visualization—all in one integrated environment.

Challenges

Merging disparate data sources (FEMA, Redfin, Census) required significant cleaning and ZIP code normalization. Balancing analytical depth with clear storytelling for non-technical audiences was also challenging.

What we learned

Climate change doesn't just create physical risk—it creates economic displacement. Those least responsible for climate change face both the highest flood risk AND displacement when they seek safety.

What's next

Expand beyond Florida to coastal states nationwide. Partner with housing authorities to integrate predictions into affordable housing policy.

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