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MODIS Aerosol Optical Depth Bias Adjustment Using Machine Learning Algorithms

Author
Leptoukh, Gregory
Published
December 05, 2011.
Physical Description
1 electronic document
Additional Creators
Wei, Jennifer, Petrenko, Maksym, Lary, David, and Albayrak, Arif
Online Version

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Unclassified, Unlimited, Publicly available.
Free-to-read Unrestricted online access
Summary
To monitor the earth atmosphere and its surface changes, satellite based instruments collect continuous data. While some of the data is directly used, some others such as aerosol properties are indirectly retrieved from the observation data. While retrieved variables (RV) form very powerful products, they don't come without obstacles. Different satellite viewing geometries, calibration issues, dynamically changing atmospheric and earth surface conditions, together with complex interactions between observed entities and their environment affect them greatly. This results in random and systematic errors in the final products.
Other Subject(s)
Collection
NASA Technical Reports Server (NTRS) Collection.
Note
Document ID: 20120003753.
GSFC.CPR.5806.2011.
American Geophysical Union 2011 Fall Meeting; 5-9 Dec. 2011; San Francisco, CA; United States.
Terms of Use and Reproduction
Copyright, Distribution as joint owner in the copyright.
View MARC record | catkey: 15980103