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

Volume

3

fYear

2009

fDate

12-17 July 2009

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/IGARSS.2009.5417884

Filename

5417884