FloodArk - Environmental Monitoring

FloodArk

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Air Quality

🌍 FloodArk

Think of FloodArk as Earth's early warning system.

We watch nature's signals — like birds suddenly changing their migration routes, plants getting stressed, or air quality dropping — because these changes often happen before disasters strike.

🔍 Why does this matter?

Most disasters don't just "happen" — they build up quietly. By tracking these early warning signs, we can predict problems before they become emergencies.

🦅

Bird Migration

Animals sense danger first

🌱

Vegetation Health

Plants show stress early

🌬️

Air Quality

Pollution reveals problems

🛰️

Satellite Data

Real-time Earth monitoring

Our goal is simple: warn earlier, respond smarter, save more lives.

☕ Support This Mission

FloodArk is free for everyone, but running real-time Earth monitoring isn't cheap.

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📈 FloodArk Roadmap

🧠

Brain: FloodArk (Central Integration)

The intelligent nervous system for our planet

Think of FloodArk as Earth's intelligent nervous system. Just like your brain processes signals from your senses, FloodArk collects environmental signals from across the globe, analyzes them for quality and patterns, then delivers clear, actionable insights to help people make better decisions.

🔗 Signal Fusion

Combines data from birds, plants, rivers, weather, fires, lightning, and traffic cameras into one coherent picture.

✅ Truth Verification

Cross-checks multiple independent sources — when different sensors tell the same story, confidence goes up.

📢 Smart Alerts

Delivers clear, timely notifications only when human attention is needed — no false alarm fatigue.

FloodArk planetary nervous system diagram showing data flow from sensors through validation to outputs

System Architecture

Connections at a glance

🦅 Birds 🌱 Vegetation 🌊 Rivers 🌩️ Lightning 🔥 Fires 📷 Cameras → 🔎 QC & Cleaning → 🔗 Cross‑check & Fuse → 📈 Confidence Score → 🗺️ Map Highlight 🔔 Alerts 👀 Analyst Review

How everything connects

Sensors observe change — birds, plants, rivers, weather, fire, lightning, traffic cameras.
Clean + verify — remove noise and obvious errors.
Cross‑check & fuse — align in space/time; independent sources agreeing raise confidence.
Confidence scoring — recency, agreement, and coverage drive a 0–100 score.
Surface what matters — analysts review, the map highlights, and alerts go out when needed.

Why these signals connect

Earlier warnings — animals and vegetation react before humans notice.
Stronger evidence — independent sensors backing the same event.
Fewer false alarms — low‑quality or lone signals get down‑weighted.
Local context — traffic cameras and weather fill in the “what’s happening now.”

Confidence score, explained

The score goes up when multiple independent sensors agree in the same area and timeframe, and goes down with noisy, conflicting, or stale data. It’s a simple way to express how much to trust a signal.

Sensory Layer

eBird migration — crowd‑sourced bird movement.
Movebank tracking — tagged wildlife routes.
WeatherSTEM — school‑based weather stations.
USGS rivers — water stage and flow.
GLM lightning — storm electricity activity.
FIRMS fires — active fire detections.
NDVI anomalies — plant stress from satellites.
FL511 cameras — visual ground truth.

Signal Transmission

QC/Validation — filter noise, keep quality.
Cross‑source comparison — align stories across sensors.
Event confidence score — simple measure of trust.

Outputs

Analyst review & verification — human eyes when it counts.
FloodArk alerts — clear, timely notifications.

Tip: On the map, click Explain to see a short, plain‑language reason for each signal.

Data: eBird • NASA FIRMS • ERA5 (ECMWF) • Cesium

Camera Snapshot

FL511 —

Assistant

ERA5 Variables

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Resolution