Chris Giesige

I work with thermal sensors and geospatial data to measure and analyze fire behavior. Collect and analyze data from wildfires that can be used to show various aspects of fire intensity. Building automated data processing and analysis pipelines. Explore machine learning methods. Fluent in image processing techniques such as segmentation, feature extraction, transformations, and contouring.

Research and monitor for early detection and prediction of lightning and wildfire behavior. Review satellite imagery, monitor solar and weather patterns, and take environmental readings on wind, solar irradiance, and magnetism to forecast weather events. Map the topography in western United States to understand the interactions between the earth and weather systems, and how a wildfire will behave under certain conditions.

During the internship we worked with satellite remote sensing data to evaluate several different fire radiative power products. Analysis of the products were carried out for multiple fires that produced pyroCb activity. A fire sampled during the FIREX-AQ field campaign was also used to compare satellite and airborne fire radiative power grids.

During the program I worked with the remote sensing team to put together a camera imaging system that flew over wildfires to collect fire behavior data during several research campaigns, and perform the analysis associated with the data collected.