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Proceedings Paper

Multispectral thermal imager land surface temperature retrieval framework
Author(s): Lee K. Balick; Andrew P. Rodger; William B. Clodius
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Paper Abstract

This paper presents a framework for earth surface temperature retrievals from Multispectral thermal images acquired buy the US Dept. of Energy Multispectral Thermal Imager (MTI) satellite. The satellite has 15 spectral band including 5 bands in the thermal IR. Also there are three near IR bands for daytime retrieval of atmospheric water vapor to use for atmospheric compensation of the thermal IR measurements. Multispectral thermal IR techniques for retrieval of water surface temperature from MTI data have been implemented and made operational. The approach to temperature retrieval presented is amenable to land surface as well as water surface temperature retrievals. The approach uses the best available atmospheric profiles of temperature and humidity as inputs to MODTRAN4 to compute look up tables of the necessary atmospheric radiative transfer components. These profiles can come from any source but we make extensive use of grided data assimilation products for numerical weather prediction. For daytime images, the humidity profiles are scaled by the column water vapor retrieved from near IR bands on a pixel-by-pixel basis. Ground leaving radiance images can then be produced and apparent temperatures are computed given some source of emissivity information. To date, we have implemented the Normalized Emissivity Method (NEM) and the ASTER temperature emissivity separation approach adapted to MTI, and the ASTER and MODIS spectral libraries are available. A final retrieved temperature is determined from the temperatures retrieved for each band according to a specified rule. Validation of the techniques is presented for one water site and two land sites where the spectral emissivity is known and simultaneous ground measurements of skin temperatures were made. The daytime retrieval results are consistently within 1.1C of the ground measurements. Finally, we investigate the impact or using different global weather data products as the meteorological data source.

Paper Details

Date Published: 24 February 2004
PDF: 11 pages
Proc. SPIE 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V, (24 February 2004); doi: 10.1117/12.512745
Show Author Affiliations
Lee K. Balick, Los Alamos National Lab. (United States)
Andrew P. Rodger, Los Alamos National Lab. (United States)
William B. Clodius, Los Alamos National Lab. (United States)

Published in SPIE Proceedings Vol. 5232:
Remote Sensing for Agriculture, Ecosystems, and Hydrology V
Manfred Owe; Guido D'Urso; Jose F. Moreno; Alfonso Calera, Editor(s)

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