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The problem of temperature and spectral emissivity assessment from hyperspectral remotely sensed data is discussed with reference to monitoring of active fires and hot targets. A new algorithm, called similar pixel addition, was developed, which allows us to retrieve the temperature of burning areas by employing spectral data collected at thermal infrared (TIR) wavelengths. The new algorithm resolves the uncertainty connected with temperature-emissivity separation assuming a slow spatial variation of emissivity, hence reducing the number of unknowns involved in the inversion of a couple of similar pixels at once. Performance of this procedure is thoroughly discussed and compared with results from two other algorithms operating in the TIR and shortwave infrared spectral ranges. This paper shows results obtained applying the new algorithm to hyperspectral images gathered by the Multispectral Infrared and Visible Imaging Spectrometer in Northern Italy (Alps) over a natural fire that broke out in July 1999. This paper is completed with a theoretical discussion of the involved topics.