Title :
Source detection of atmospheric releases using symbolic machine learning classification and remote sensing
Author :
Bowman, Mark C. ; Cervone, Guido ; Franzese, Pascale
Author_Institution :
George Mason Univ., Fairfax, VA, USA
Abstract :
This paper introduces the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and its use for the identification of the source of atmospheric pollutants. NPOESS is the next generation satellite program, and can be used for the source detection of atmospheric pollutants. The iterative methodology proposed herein uses a combination of ground measurements, atmospheric models, machine learning and remote sensing to identify the characteristics of an unknown atmospheric emission.
Keywords :
air pollution; atmospheric techniques; remote sensing; NPOESS program; National Polar-orbiting Operational Environmental Satellite System; atmospheric pollutants source detection; atmospheric releases; iterative methodology; remote sensing; symbolic machine learning classification; Atmospheric measurements; Atmospheric modeling; Chemical industry; Data analysis; Iterative methods; Machine learning; Pollution measurement; Remote sensing; Satellites; Sensor phenomena and characterization; AQ; Aerosol; Machine Learning; NPOESS;
Conference_Titel :
Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009
Conference_Location :
Cape Town
Print_ISBN :
978-1-4244-3394-0
Electronic_ISBN :
978-1-4244-3395-7
DOI :
10.1109/IGARSS.2009.5417884
