Operational Modular Imaging Spectrometer （OMIS） is a new type of airbome remote sensor. It has 128 spectral bands ranging from visibl e to thermal infrared wavelength. Its application fields include geography

agri culture

forest and ocean etc. For the convenience of the wide use of OMIS Data and the instrument improvement

quantitative evaluation of OMIS data is indispen sable. Signal-Noise-Ratio（ SNR ） is an important evaluation scale. According to R. E. Roger’s view

for a complex instrument such as AVIRIS

it is not reasonabl e to assume that the noise included is random and not correlative

especially in visible spectral bands. In this paper

through the analysis of the noise charac ters in OMIS data the authors point out that the noise mixed in OMIS data is a k ind of additive noise and not correlative. Based on athrough analysis of the fou r available SNR estimation methods

a conclusion can be drawn that the spati al a nd spectral decorrelation method is the most reasonable one for OMIS data. The e xperimental results are also presented. It is also pointed out that after radiom etric correction

the SNR of the acquired data can effeciently reflect the SNR character of the remote sensor.