Paper
23 August 2000 Atmospheric compensation for surface temperature and emissivity separation
Author Affiliations +
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Erich D. Hernandez-Baquero and John R. Schott "Atmospheric compensation for surface temperature and emissivity separation", Proc. SPIE 4049, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, (23 August 2000); https://doi.org/10.1117/12.410364
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Cited by 12 scholarly publications.
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KEYWORDS
Databases

Sensors

Simulation of CCA and DLA aggregates

Atmospheric modeling

Data modeling

Black bodies

Earth's atmosphere

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