2 August 2002 Temperature/emissivity separation of MTI data using the Terra/ASTER TES algorithm
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Surface temperatures and emissivities can be estimated using multispectral thermal infrared (TIR) data, from various instruments. In this paper the temperature-emissivity separation algorithm (TES) is modified to recover surface temperatures and emissivities using Multispectral Thermal Imager (MTI) data from two mid infrared (MIR) and three TIR bands. As TES was originally designed for use with the five TIR bands from the Advanced Spaceborne Thermal Emission and Reflection (ASTER) instrument, broadening its application to MIR wavelengths requires careful evaluation of possible atmospheric and reflected daytime solar illumination effects. Numerical simulations show that TES results for MTI data, assuming error-free atmospheric corrections, are statistically similar to TES results for ASTER data, with surface temperature recovery within +/- 1.5K and emissivity recovery within +/- 0.02. However, strong atmospheric absorption (as high as 61%), and expected daytime reflected solar illumination (as high as 50% of measured radiance) in the MIR bands suggest that TES results for MTI data are more sensitive to errors in atmospheric compensation. Furthermore, the relatively steep slope of Planck's radiation curve for typical terrestrial temperatures in the MIR wavelengths, suggests that inverting temperatures from measured MIR radiance using Planck's law will be more sensitive to error. Numerical simulations and preliminary image analysis suggest that the three TIR MTI bands are not sufficient to obtain the desired TES results. However, omitting one of the MIR bands and using a four-band configuration decreases sensitivity to atmospheric effects, while still maintaining acceptable theoretical TES performance.
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Amit Mushkin, Amit Mushkin, Lee K. Balick, Lee K. Balick, Alan R. Gillespie, Alan R. Gillespie, } "Temperature/emissivity separation of MTI data using the Terra/ASTER TES algorithm", Proc. SPIE 4725, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII, (2 August 2002); doi: 10.1117/12.478764; https://doi.org/10.1117/12.478764


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