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Proceedings Paper

Atmospheric compensation for surface temperature and emissivity separation
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Paper Abstract

A new method for atmospheric compensation of longwave infrared (LWIR) hyperspectral images is presented. The technique exploits the large amount of data in hyperspectral images to obtain the most information about atmospheric and surface parameters of interest. This is done with Canonical Correlation Analysis (CCA) by casting the problem onto a multivariate framework. The procedure accounts for the joint effects of surface and atmospheric radiation, thus addressing the complex interaction between the Earth’s surface properties, thermodynamic state, and the atmosphere. After atmospheric compensation, the calculated surface radiance is used to estimate temperature and emissivity. The technique was tested with radiative transfer model simulations and airborne multispectral data. Results obtained from MODTRAN simulations and the MODerate resolution Imaging Spectrometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) (MASTER) airborne sensor show that it is feasible to retrieve land surface temperature and emissivity with 1°K and 0.01 accuracies, respectively.

Paper Details

Date Published: 23 August 2000
PDF: 11 pages
Proc. SPIE 4049, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, (23 August 2000); doi: 10.1117/12.410364
Show Author Affiliations
Erich D. Hernandez-Baquero, Rochester Institute of Technology (United States)
John R. Schott, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 4049:
Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI
Sylvia S. Shen; Michael R. Descour, Editor(s)

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