Source detection of atmospheric releases using symbolic machine learning classification and remote sensing

Mark C. Bowman, Guido Cervone, Pascale Franzese

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publication2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009 - Proceedings
DOIs
StatePublished - Dec 1 2009
Event2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009 - Cape Town, South Africa
Duration: Jul 12 2009Jul 17 2009

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume3

Other

Other2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009
CountrySouth Africa
CityCape Town
Period7/12/097/17/09

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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  • Cite this

    Bowman, M. C., Cervone, G., & Franzese, P. (2009). Source detection of atmospheric releases using symbolic machine learning classification and remote sensing. In 2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009 - Proceedings [5417884] (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 3). https://doi.org/10.1109/IGARSS.2009.5417884