Spectral mixture analysis of simulated thermal infrared spectrometry data:An initial temperature estimate bounded TESSMA search approach

At-sensor thermal infrared (TIR) radiation varies depending on the temperat ure and emissivity of surface materials and the modifying impact of atmosph eric absorption and emission. TIR imaging spectrometry often involves extra cting temperature, emissivity, and/or surface composition, which are useful in diverse studies ranging from climatology to land use analyses. A two-st age application of temperature emissivity separation (TES) using spectral m ixture analysis (SMA) or TESSMA, was employed to characterize isothermal mi xtures on a subpixel basis. This two-stage approach first uses the relation ship between a virtual cold endmember fraction and surface temperature to e xtract initial image temperature estimates. Second, an isothermal SMA appli cation searches the region within the maximum temperature error range of th e initial estimate, selecting the best subpixel spectral mixture fit. Work presented includes characterizations of synthetically generated temperature and constituent mixture gradient test images, and a discussion of errors a ssociated with selecting temperature search ranges 25% and 75% smaller than the initial temperature calculation error range. Results using this two-st age approach indicate improved overall temperature estimates, constituent e stimates, and constituent fraction estimates using simulated TIR data.