FLAASH and MODTRAN4: state-of-the-art atmospheric correction for hyperspectral data

FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes) is a MODTRAN-based "atmospheric correction" software package which is being developed by the Air Force Research Laboratory, Hanscom AFB, and Spectral Sciences, Inc., to support current and planned SWIR/visible/UV hyperspectral and multispectral sensors, typically in image format. The AF intent is to provide surface reflectance and emissivity image cubes of sufficient accuracy for input into subsequent analyses of surface properties, effectively removing the atmospheric component. The main objectives are (1) accurate, physics-based descriptions of surface and atmospheric properties (such as surface albedo, relative elevation, water vapor column, aerosol and cloud optical properties, and temperatures), (2) minimal computational time requirements, and (3) interactive, user-friendly interface for generating MODTRAN4-based look-up tables. Validation and development exercises are being carried out on data from the airborne AVIRTS and HYDICE sensors, which cover the 0.4-2.5 /spl mu/m region; applications are also planned for infrared sensors. The algorithms for deriving the surface and atmospheric properties utilize the full MODTRAN4 accuracy (thermal and solar) and account for adjacency effects associated with atmospheric scattering. A new line-tail treatment and a correlated-k (CK) radiative transfer algorithm provide improved accuracy, especially under conditions of partial cloud cover and/or heavy aerosol loading.

[1]  Jinxue Wang,et al.  Validation of FASE (FASCODE for the Environment) and MODTRAN3: updates and comparisons with clear-sky measurements , 1995, Remote Sensing.

[2]  Wallace M. Porter,et al.  The airborne visible/infrared imaging spectrometer (AVIRIS) , 1993 .

[3]  W. Paul Menzel,et al.  Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (MODIS) , 1992, IEEE Trans. Geosci. Remote. Sens..

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

[5]  Zhao-Liang Li,et al.  A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data , 1997, IEEE Trans. Geosci. Remote. Sens..

[6]  Dar A. Roberts,et al.  Characterization and Compensation of the Atmosphere for the Inversion of AVIRIS Calibrated Radiance to Apparent Surface Reflectance , 1996 .

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

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

[9]  Rudolf Richter Atmospheric correction of DAIS hyperspectral image data , 1996 .

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

[11]  Robert W. Basedow,et al.  HYDICE system: implementation and performance , 1995, Defense, Security, and Sensing.

[12]  F. X. Kneizys,et al.  Convolution algorithm for the Lorentz function. , 1979, Applied optics.