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    An Improved Atmospheric Correction Algorithm for Hyperspectral Remotely Sensed Imagery

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    IEEE.ac2004.hyperspectral.pdf (331.9Kb)
    No. of downloads: 1306

    Date
    2004-04
    Author
    Liang, Shunlin
    Fang, Hongliang
    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
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    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.
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    http://hdl.handle.net/1903/4320
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    Copyright Institute of Electrical and Electronics Engineers.

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