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Why We’re Still Bad at Predicting Wildfires
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Вміст надано Matt Forrest. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Matt Forrest або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.
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Wildfires are getting more intense, yet many people in Los Angeles had no idea the fire was near them—until they saw the smoke. Despite all our advancements in geospatial technology, disaster response still struggles with timely alerts, real-time data access, and predictive modeling.
In this episode, I sit down with Mina Nada, a remote sensing specialist, to explore what went wrong during the recent LA wildfires and how geospatial tools like satellite imagery, fire modeling, and risk mapping can improve future disaster response. We break down why current wildfire alerts are failing, what GIS professionals can do to fix it, and how earth observation data plays a critical role in mitigating fire disasters.
If you’re in GIS, remote sensing, emergency management, or just curious about the future of fire detection, this conversation is packed with insights you don’t want to miss.
🔥 Topics Covered:
✔️ Why wildfire alerts failed during the LA fires
✔️ How satellite imagery tracks wildfires in real-time
✔️ The role of GIS in predicting and responding to fires
✔️ Challenges in making wildfire data more accessible
✔️ What we need to do to prevent future wildfire disasters
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