Efficient Algorithms for Atmospheric Correction of Remotely Sensed Data
Efficient Algorithms for Atmospheric Correction of Remotely Sensed Data
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Date
1998-10-15
Authors
Fallah-Adl, Hassan
JaJa, Joseph
Liang, Shunlin
Kaufman, Yoram J.
Townshend, John
Advisor
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Abstract
Remotely sensed imagery has been used for developing and validating
vairous studies regarding land cover dynamics such as global carbon modeling,
biogeochemical cycling, hydrological modeling, and ecosystem response
modeling. However, the large amounts of imagery collected by the satellites
are largely contaminated by the effects of atmospheric particles through
absorption and scattering of the radiation from the earth surface. The
objective of atmospheric correction is to retrieve the surface
reflectance (that characterizes the surface properties) from remotely sensed
imagery by removing the atmospheric effects. Atmospheric correction has been
shown to significantly improve the accuracy of image classification.
(Also cross-referenced as UMIACS-TR-95-53)