An Improved Atmospheric Correction Algorithm for Hyperspectral Remotely Sensed Imagery
An Improved Atmospheric Correction Algorithm for Hyperspectral Remotely Sensed Imagery
Files
Publication or External Link
Date
2004-04
Authors
Liang, Shunlin
Fang, Hongliang
Advisor
Citation
Liang, S., H. Fang, (2004), An Improved Atmospheric Correction Algorithm for Hyperspectral Remotely Sensed Imagery. IEEE Geoscience and Remote Sensing Letters, 1(2):112-117
DRUM DOI
Abstract
There is an increased trend toward quantitative
estimation of land surface variables from hyperspectral remote
sensing. One challenging issue is retrieving surface reflectance
spectra from observed radiance through atmospheric correction,
most methods for which are intended to correct water vapor and
other absorbing gases. In this letter, methods for correcting both
aerosols and water vapor are explored. We first apply the cluster
matching technique developed earlier for Landsat-7 ETM+
imagery to Airborne Visible/Infrared Imaging Spectrometer
(AVIRIS) data, then improve its aerosol estimation and incorporate
a new method for estimating column water vapor content
using the neural network technique. The improved algorithm
is then used to correct Hyperion imagery. Case studies using
AVIRIS and Hyperion images demonstrate that both the original
and improved methods are very effective to remove heterogeneous
atmospheric effects and recover surface reflectance spectra.