University of Hawai'i

David Askov

Douglas B Bausch

Ray Shirkhodai

Systems and methods are described for the global, rapid, and automatic detection of wildfire activity. Such systems and methods may also classify wildfires based on a new severity classification scheme. Wildfire activity may be tracked as wildfires migrate, grow, and combine. Additionally, because satellite systems currently collect over 4 million fire observations per year, a filtering mechanism is introduced to remove benign anthropogenic fires. To classify wildfire severity for generating alerts, the present disclosure also provides a logarithmic severity classification system based on 24-hour cumulative Fire Radiative Power (FRP).

Automated wildfire detection

Systems and methods are described for performing logical filtering of hazard alerts by an area of geography the hazard is expected to impact and issuing alerts based on that area. Based on a geographical location, a hazard type, and a hazard severity, one or more geographic areas the hazard is expected to impact may be determined. One or more automated alerts may be issued to alert users in those areas that could be affected by the hazard.

Growing community of inventors

Seattle, WA, United States of America

David Askov