Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Volume emission rate tomography from a satellite platform.

Douglas A Degenstein1, Edward J Llewellyn, Nicholas D Lloyd

  • 1Institute of Space and Atmospheric Studies, Department of Physics and Engineering Physics, 116 Science Place, University of Saskatchewan, Saskatoon, SK, S7N 5E2, Canada.

Applied Optics
|March 21, 2003
PubMed
Summary

Scientists developed a new algorithm to retrieve atmospheric structure from satellite limb images. This method successfully reconstructs both horizontal and vertical atmospheric details, even with significant noise.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Response to comments on "Large volcanic aerosol load in the stratosphere linked to Asian monsoon transport".

Science (New York, N.Y.)·2013
Same author

Large volcanic aerosol load in the stratosphere linked to Asian monsoon transport.

Science (New York, N.Y.)·2012
See all related articles

Area of Science:

  • Atmospheric science
  • Remote sensing
  • Image processing

Background:

  • Satellite-based limb imaging provides a unique perspective for atmospheric profiling.
  • Retrieving detailed atmospheric structure from limb images presents significant challenges due to geometric and optical factors.

Purpose of the Study:

  • To investigate the feasibility of retrieving horizontal atmospheric structure from satellite limb imaging.
  • To develop and validate an algorithm for atmospheric structure retrieval.

Main Methods:

  • A maximum likelihood expectation maximization algorithm was developed for image analysis.
  • The algorithm was tested using simulated limb images with varying signal-to-noise ratios (S/N).

Main Results:

Related Experiment Videos

  • The developed algorithm successfully retrieved horizontal atmospheric structure from limb images.
  • Accurate retrieval of both horizontal and vertical atmospheric structure was achieved even with a S/N of 10 for single observations.
  • The algorithm demonstrated robustness against substantial observational noise.

Conclusions:

  • The maximum likelihood expectation maximization algorithm is effective for retrieving atmospheric structure from satellite limb images.
  • This technique holds promise for detailed atmospheric profiling despite noisy observational data.