Peril Watch is a real-time monitoring platform that combines natural hazard risk assessment with active event tracking. The platform integrates multiple data sources to provide comprehensive situational awareness for weather events, natural disasters, and civil unrest. Currently focused on the continental US with worldwide expansion coming soon.
The colored contour maps display FEMA National Risk Index (NRI) data at the county level. Each hazard type (Tornado, Flood, Hurricane, Wildfire, etc.) has its own risk assessment based on expected annual losses, social vulnerability, and community resilience. Risk scores range from 0 (very low) to 100 (very high).
Real-time event data is aggregated from multiple authoritative sources:
Click on any hazard category to view its risk map and active events. Click on map markers or table rows to see detailed event information including severity, timing, location, and technical parameters like Fire Radiative Power (FRP) for wildfires.
No, we do not store historical event data. The platform displays only currently active events from live data feeds. Weather alerts expire according to their official expiration times set by the National Weather Service, and wildfire detections represent the most recent satellite passes (typically within the last 3-24 hours depending on orbital coverage).
Event data is fetched in real-time when you load or refresh the page. NOAA weather alerts are updated continuously as the National Weather Service issues, updates, or cancels warnings. NASA FIRMS wildfire data is updated every 3 hours as satellites complete their orbits.
Risk scores from the FEMA National Risk Index represent expected annual losses relative to other counties nationwide. They combine hazard frequency and intensity with social vulnerability and community resilience factors. A score of 80-100 indicates very high risk, while 0-20 indicates very low risk for that specific hazard type.
The FEMA NRI dataset covers all 3,109 counties in the continental United States. However, some hazards (like hurricanes or earthquakes) may show very low or zero risk scores in regions where those events are extremely rare or impossible.
Confidence levels for wildfire detections indicate the satellite sensor's certainty that the thermal anomaly represents an actual fire. The platform filters to show only detections with ≥90% confidence to reduce false positives from industrial heat sources or other non-fire thermal anomalies.