Publication Date

Spring 2024

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Meteorology and Climate Science

Advisor

Craig Clements; Miguel Valero; Adam Kochanski

Abstract

Wildland fire is one of the most complex environmental physical processes to quantify. The way in which we observe and measure wildland fire is critical in understanding how these processes drive fire dynamics. Fire behavior can be observed in several ways including the use of ground sensors and remote sensing packages aboard aircraft and satellites. Airborne sensors provide high spatial resolution and can provide high temporal resolution. Infrared thermography takes advantage of radiant heat transfer allowing for the study of fire characteristics such as fire spread and intensity. Aircraft observations utilizing infrared cameras have been a well-established method of fire observation, yet there is still a significant lack of comprehensive data available. Presented in this research are several advances in the use of infrared remote sensing techniques to evaluate fire behavior. First, a synthesis of knowledge and methods regarding the use of infrared camera systems to measure fire behavior is discussed and analyzed. Second, is the use of airborne infrared data collected during tactical firefighting operations to develop an automated method of extracting active fire edges for fire spread analysis. Third, is an analysis of high-resolution fire behavior data collected during several wildfires in the 2022 fire season and the new methods used to process the images, calculate fire radiative power, and evaluate fire spread. These methods are a contribution to the advancement of being able to use operational firefighting data for research applications, furthering automated methods of processing large data quantities to evaluate fire spread, and evaluating high-resolution landscape scale wildfire behavior.

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