Using a massive dataset, researchers are developing tools to help them predict when and where wildfires are most likely to start.
The team, led by a Boise State University civil engineering researcher, looked at half a million wildfire starts, and hundreds of attributes about them. Beyond the obvious weather variables like wind speed, temperature and humidity, they also considered human factors like density of development.
Yavar Pourmohamad, a researcher with Boise State University’s civil engineering department, and lead author of a recent paper on the prediction model said the breadth and depth of data points is part of what sets the research apart, and makes it potentially useful to land managers…