DISASTER RISK SENDAI FRAMEWORK COUNTRIES & REGIONS THEMES HAZARDS KNOWLEDGE BASE

Forest fires on the rise as JRC study warns of danger to air quality

JRC

The EC Joint Research Centre confirms in its annual forest fires report that there is a trend towards longer and more intense fire seasons in Europe, as a result of hotter and drier conditions induced by climate change. Smoke from wildfires poses a health risk as it causes severe air pollution. With extending wildfire seasons, health impacts are expected to grow.

  • Machine learning used to predict earthquakes in a lab setting

    Univ of Cambridge

    Researchers have used machine learning techniques to successfully predict earthquakes by identifying a hidden signal leading up to an earthquake. The results can also be applied to landslides and avalanches, and shows great potential to be applied as an early warning system that predicts an earthquake long in advance.

  • Tsunami risk reduction in Central America for building disaster resilience

    UNESCO San Jose

    Tsunami early warning systems use seismic monitoring to determine location, depth, and magnitude of an earthquake in order to predict the tsunami arrival time and expected wave heights. UNESCO is working on tsunami risk reduction in Central America as well as on raising public awareness and preparedness in cooperation with several donors.

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Sendai Framework for Disaster Risk Reduction 2015-2030

Documents, tools and processes Background, indicators, data readiness review