GEOECOZ

GeoEcoz Inspiration

Every year, critical environmental threats like deforestation, wildfire, coral bleaching, and poaching get noticed too late. Not because the data doesn't exist, but because it's scattered across satellite feeds, climate APIs, and field notebooks that never talk to each other. We wanted to build the thing conservation teams actually need: one shared, live register that turns raw environmental signal into a clear, actionable risk picture before the damage is irreversible.

What it does

GeoEcoz is a live earth observation control panel that scores environmental risk across monitored regions worldwide and puts it on one interactive map. Each region gets a 0 to 100 risk score driven by real signal types: fire density, temperature anomaly, and deforestation rate, color coded by severity. Click into any region and you get its risk score, primary threat type, a 30 day trend, and a plain language field note explaining what's happening on the ground. Anyone can also log a new threat directly from the field through a simple report form, feeding straight into the same register everyone else is watching. Right now it's tracking 16 regions across 6 continents, flagging active threats from the Amazon Basin to the Sumatran peatlands in real time.

How we built it

We built GeoEcoz as a full stack Next.js 14 app using the App Router and TypeScript, with Next.js Route Handlers powering the backend. The map runs on react leaflet with a dark, cartographic tile theme, and Recharts renders the 30 day risk trends. At the core is a weighted risk scoring function that combines fire density, temperature anomaly, and deforestation rate into a single score per region, built so it can be swapped to consume real satellite or climate data, like NASA FIRMS or Open Meteo, without touching the rest of the app. We deliberately designed away from the generic AI dashboard look. Dark charcoal base, parchment field log panels, monospace for all data values, so it reads like real field monitoring software, not a template.

Challenges we ran into

Balancing "looks like a real product" against "buildable in a hackathon" was the biggest tension. It would have been much faster to reach for a default SaaS card layout with shadows, but we wanted GeoEcoz to feel credible to the conservationists it's actually for. Designing a risk scoring formula that felt meaningful rather than arbitrary took several passes, since bad weighting would make every region look equally urgent. We also had to think carefully about the field report flow, making it simple enough for a non technical user in the field to log a threat in seconds.

Accomplishments that we're proud of

We're proud that GeoEcoz doesn't look or feel like a typical hackathon project. The design has a clear point of view instead of a generic template, and the data tells a coherent, believable story: you can trace a specific region from a risk score, to a threat type, to a trend, to a plain language explanation of what's happening. The scoring engine is real, not decorative. It's structured to plug into live data sources with no architectural rework.

What we learned

We learned how much of "impact" in an environmental tool comes down to legibility. A risk score means nothing without context, trend, and a plain language reason attached to it. We also learned that resisting the default AI generated aesthetic (cream backgrounds, rounded card grids, gradient accents) takes deliberate, upfront design decisions, not just better code.

What's next for GeoEcoz Connect live satellite and climate data feeds (NASA FIRMS, Open Meteo) in place of mock data Persist regions and field reports to a real database Push alerts when a region crosses into critical risk Historical playback to visualize how risk has evolved over time Verified partner access so on the ground NGOs and rangers can contribute trusted field reports

Built With

• css
• html
• leaflet.js
• nextjs
• nodejsjavascript
• react
• react-leaflet
• recharts
• tailwindcss
• typescript
• vercel