Forecasting Wildfire Behavior: Earth Observation and GIS
Advances in GIS, remote sensing, and machine learning are leveraging land and weather data to improve fire prediction models.
Advances in GIS, remote sensing, and machine learning are leveraging land and weather data to improve fire prediction models.
Synthetic-aperture radar (SAR) is being used to map post-fire vegetation recovery.
With fires raging in California, Oregon, and Washington, scientists, activists, geospatial companies, and others are using GIS and spatial data to better inform and protect communities.
New satellites and improved image processing methods are better enabling the ability to provide real-time and near real-time mapping of wildfires.
Researchers have made 38-years worth of global fire danger reanalysis available as an open dataset.