Université du Québec à Montréal
Development and evaluation of automated learning algorithms for the classification of FIRR-2 atmospheric scenes — The HAWC satellite mission, currently under development, plans to place into orbit three Canadian atmospheric observation instruments, including TICFIRE, a radiometer designed to capture radiances emitted toward space in the thermal infrared and far-infrared. One of the first steps in processing TICFIRE data will be to classify the observed atmospheric scenes, which may consist of clear sky, aerosols, ice clouds, liquid clouds, or mixed-phase clouds. Measurements collected during the PONEX campaign by the FIRR-2 instrument, a precursor to TICFIRE, will be used to develop and evaluate artificial intelligence algorithms for atmospheric scene classification. This type of algorithm, which allows for the consideration of a wide range of variables affecting infrared emissions, is currently being considered in several satellite missions as a replacement for traditional classification approaches based on threshold systems using a limited number of variables.