Evaluation of different methods for extracting relative spectral emissivity information from simulated thermal infrared multispectral scanner data

The performance of five published methods for extracting relative spectral emissivity information from thermal infrared multispectral data has been ev aluated. In the first part of this article, we have recalled those five met hods and shown mathematically that they are almost equivalent to each other . Then, using simulated data built up wit the TIMS (Thermal Infrared Multis pectral Scanner) instrument, we have analyzed the sensitivity of those meth ods to different sources of error which may occur in real data such as erro rs due to 1) method simplification, 2) instrumental noise and systematic ca libration error, 3) uncertainties on the estimation of downwelling atmosphe ric radiance, and 4) uncertainties of atmospheric parameters in atmospheric corrections. In terms of resulting errors in relative emissivity, the resu lts show that: a) All methods are very sensitive to the uncertainties of at mosphere. An error of 20% of water vapor in midlatitude summer atmosphere ( 2.9 cm) may lead to an error of 0.03 (rms) for Channel 1 of TIMS. b) The ef fect of the atmospheric reflection term is very important. If this term is neglected in method development, this may lead to an error of 0.03 (rms) fo r Channel 1 and midlatitude summer atmosphere. This is the cae for the alph a method. c) Instrumental noise commonly expressed by noise equivalent diff erence temperature (NE Delta T) from 0.1 K to 0.3 K results in an error of relative emissivity ranging from 0.002 to 0.005 for all methods. d) Error i n relative emissivity due to the instrument calibration error (systematic e rror) is negligible. The stud also shows that the relative emissivity deriv ed wit an incorrect atmosphere is linearly related to its actual value deri ved with correct atmospheric parameters. Based on this property, we propose three methods to correct for the errors caused by atmospheric corrections under horizontally invariant atmospheric conditions. A practical analysis w ith the real TIMS data acquired for Hapex-Sahel experiment in 1992 supports the results of this simulation. (C) Elsevier Science Inc., 1999.