ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2014, Vol. 11, No. 4, pp. 360-368

The effectiveness of atmospheric correction for Hyperion hyperspectral images in regions with developed vegetation cover

A.A. Derkacheva  , O.V. Tutubalina 
M.V. Lomonosov Moscow State University, Moscow, Russia
We review the most significant sources of atmospheric influence in remotely sensed imagery and various algorithms for image atmospheric correction, including IARD, QUAC, FLAASH, and EL. These algorithms are applied to an EO-1 Hyperion image of 27 July 2013 of a forested territory in central Kola Peninsula, north-west Russia. We conclude that the empirical line (EL) regression algorithm, which uses field spectroradiometric data for two signatures, yielded the best results, on the basis of the assessment with other field data. We provide recommendations for choosing ground signature areas: they should be sufficient in area, homogeneous, have sufficient range of spectral radiance values (as a set of signatures in total), be stable over time.
Keywords: hyperspectral images, atmospheric correction algorithms, ground spectroradiometry data
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  1. Zabelin S.A., Tulegulov A.D., Metodika atmosfernoi korrektsii snimkov Landsat (Technique of atmospheric correction for Landsat imagery), Vestnik ENU im. L.N. Gumileva, 2011 (6), pp.147-154.
  2. Schowengerdt R.A., Distantsionnoe zondirovanie. Modeli i metody obrabotki izobrazheniy (Remote sensing: Models and methods for image processing), Moscow: Tekhnosfera, 2010, 560 p.
  3. Adler-Golden S., Bernstein L., Matthew M., Atmospheric compensation of extreme off-nadir hyperspectral imagery, SPIE, Proceedings, Algorithms and Technologies for Multispectral, Hyperspectral and Ultraspectral Imagery XIII, 2007.
  4. Beck R. EO-1 User Guide, v. 2.3, Satellite Systems Branch USGS EDS, 2003.
  5. Exelis Visual Information Solutions, Atmospheric Correction, Exelis VIS, 2014.
  6. Kawishwar P. Atmospheric Correction Models for Retrievals of Calibrated Spectral Profiles from Hyperion, India: Dehra Dun, Indian Institute of remote sensing, National Remote Sensing Agency, 2007.
  7. San B.T., Suzen M.L., Evaluation of different atmospheric correction algorithms for EO-1 Hyperion imagery, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, Volume XXXVIII, Part 8, Kyoto, 2010, pp. 392-397.
  8. Tuominen J., T. Lipping T., Atmospheric correction of hyperspectral data using combined empirical and model based method, Tampere University of Technology, 2004.
  9. Xu Y., Wang R., Liu Sh., Yang S., Yan B., Atmospheric correction of hyperspectral data using MODTRAN model, Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China, 2008.