Speed and accuracy improvements in FLAASH atmospheric correction of hyperspectral imagery

Abstract. Remotely sensed spectral imagery of the earth’s surface can be used to fullest advantage when the influence of the atmosphere has been removed and the measurements are reduced to units of reflectance. Here, we provide a comprehensive summary of the latest version of the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes atmospheric correction algorithm. We also report some new code improvements for speed and accuracy. These include the re-working of the original algorithm in C-language code parallelized with message passing interface and containing a new radiative transfer look-up table option, which replaces executions of the MODTRAN® model. With computation times now as low as ~10  s per image per computer processor, automated, real-time, on-board atmospheric correction of hyper- and multi-spectral imagery is within reach.

[1]  Alexander Berk,et al.  Retrieval of atmospheric properties from hyper and multispectral imagery with the FLAASH atmospheric correction algorithm , 2005, SPIE Remote Sensing.

[2]  E. Vermote,et al.  Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer , 1997 .

[3]  Gail P. Anderson,et al.  Atmospheric correction of spectral imagery: evaluation of the FLAASH algorithm with AVIRIS data , 2003, SPIE Defense + Commercial Sensing.

[4]  James Slusser,et al.  Validation and refinement of hyperspectral/multispectral atmospheric compensation using shadowband radiometers , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[5]  R. Richter,et al.  Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric/topographic correction , 2002 .

[6]  Lorraine Remer,et al.  The MODIS 2.1-μm channel-correlation with visible reflectance for use in remote sensing of aerosol , 1997, IEEE Trans. Geosci. Remote. Sens..

[7]  Gail P. Anderson,et al.  Analysis of Hyperion data with the FLAASH atmospheric correction algorithm , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[8]  Steven M. Adler-Golden,et al.  Improvements in Aerosol Retrieval for Atmospheric Correction , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

[9]  K. Stamnes,et al.  Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media. , 1988, Applied optics.

[10]  D. C. Robertson,et al.  MODTRAN cloud and multiple scattering upgrades with application to AVIRIS , 1998 .

[11]  Gail P. Anderson,et al.  Atmospheric correction for shortwave spectral imagery based on MODTRAN4 , 1999, Optics & Photonics.

[12]  C. Justice,et al.  Atmospheric correction of visible to middle-infrared EOS-MODIS data over land surfaces: Background, operational algorithm and validation , 1997 .

[13]  David P. Miller,et al.  Status of atmospheric correction using a MODTRAN4-based algorithm , 2000, SPIE Defense + Commercial Sensing.

[14]  Didier Tanré,et al.  Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: an overview , 1997, IEEE Trans. Geosci. Remote. Sens..

[15]  Norman T. O'Neill,et al.  Reflectance Extraction from CASI Spectra Using Radiative Transfer Simulations and a Rooftop Irradiance Collector , 1992 .

[16]  S. Adler-Golden,et al.  Atmospheric Correction for Short-wave Spectral Imagery Based on MODTRAN 4 , 2000 .

[17]  Marcos J. Montes,et al.  NRL Atmospheric Correction Algorithms for Oceans: Tafkaa User's Guide , 2004 .

[18]  James A. Gardner,et al.  MODTRAN5: a reformulated atmospheric band model with auxiliary species and practical multiple scattering options , 2004, SPIE Asia-Pacific Remote Sensing.

[19]  Z. Ahmad,et al.  Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space. , 2000, Applied optics.

[20]  John Cipar,et al.  Active volcano monitoring using a space-based short-wave infrared imager , 2011, 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).

[21]  Steven M. Adler-Golden,et al.  Atmospheric compensation of extreme off-nadir hyperspectral imagery from Hyperion , 2007, SPIE Defense + Commercial Sensing.

[22]  Bo-Cai Gao,et al.  A New and Fast Method for Smoothing Spectral Imaging Data , 1998 .

[23]  Paul E. Lewis,et al.  MODTRAN5: a reformulated atmospheric band model with auxiliary species and practical multiple scattering options , 2004, SPIE Defense + Commercial Sensing.