AI in Wildfire Detection Quiz

Answers and explanations appear as you take the quiz.

1. What is one technical challenge for camera-based wildfire detection?
   • Distinguishing smoke from look-alikes such as fog, dust or clouds
   • Guaranteeing that every alert is a real fire
   • Determining legal liability for a utility
   • Predicting the exact path of every wildfire
2. What information does NOAA’s GOES-R Fire/Hot Spot Characterization product provide?
   • A forecast of the exact evacuation route
   • Fire location and sub-pixel characteristics such as temperature, size and radiative power
   • A guarantee that a new fire is contained
   • An automatic liability judgment for utilities
3. How do weather satellites like NOAA's GOES detect active fires?
   • By listening for crackling sounds
   • By measuring wind speed only
   • By sensing infrared heat anomalies
   • By counting trees
4. Why can earlier wildfire detection help response teams?
   • It guarantees the fire will not spread
   • It makes satellite sensors unnecessary
   • It prevents weather from affecting fire behavior
   • It can give crews more opportunity to respond while a fire is still small
5. How do temporal models improve detection confidence?
   • By comparing consecutive frames so a drifting, growing plume stands out from static haze
   • By ignoring all previous images
   • By deleting the camera feed
   • By only looking once per week
6. What is the purpose of new constellations like Google's FireSat?
   • To replace all firefighters
   • To image nearly every point on Earth frequently and detect very small fires
   • To broadcast television
   • To map ocean currents only
7. Which satellite measurements does the GOES-R fire and hot-spot product use?
   • Only microphone recordings from ground stations
   • Radar measurements of tree height alone
   • Visible and infrared ABI spectral bands
   • Ultraviolet images of cloud tops only
8. Why do camera-based wildfire alert systems pair model output with human verification?
   • Human review is needed because cameras cannot capture images
   • Smoke models can identify the exact cause of every ignition
   • Verification makes the camera network independent of weather
   • Look-alikes such as fog, dust, and clouds can create false alerts