Aerosol Characterization Using Machine Learning
Author:
Affiliation:
1. California Institute of Technology,Earth Science Section Jet Propulsion Laboratory,Pasadena,CA,USA,91109
2. California Institute of Technology,Division of Geological and Planetary Sciences,Pasadena,CA,USA,91125
Funder
Jet Propulsion Laboratory
California Institute of Technology
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9883023/9883024/09884336.pdf?arnumber=9884336
Reference22 articles.
1. Polarization of skylight in the O_2A band: effects of aerosol properties
2. Retrieval of the optical depth and vertical distribution of particulate scatterers in the atmosphere using O<sub>2</sub> A- and B-band SCIAMACHY observations over Kanpur: a case study
3. Retrieval of aerosol parameters from the oxygen A band in the presence of chlorophyll fluorescence
4. Retrieving aerosol height from the oxygen A band: a fast forward operator and sensitivity study concerning spectral resolution, instrumental noise, and surface inhomogeneity
5. Tropospheric aerosol profile information from high-resolution oxygen A-band measurements from space
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