Some bands or band combination are used as the spectral indices of fuel moisture content based on analyzing the spectral characteristic and relation of spectrum and fuel moisture content. The optimal function models are respectively established between the fuel moisture content and spectral indices. By analyzing the spectral index and its relative error, it confirms the spectral index SR=R1600/R820 as the characteristic parameters of the model, where R1600 and R820 are the reflectivities at 1600 nm and 820 nm. Utilizing the measured vegetation spectral reflectance and fuel moisture content, the model relation between fuel moisture content and SR spectral index is established. According to the model of fuel moisture content, ETM and ASTER remote sensing data, the quantitative inversion are achieved by the programme based on IDL7.0 platform. The measured data and background data surveyed in the study area are used to evaluate and analyze the inversion results synthetically. The results show that the spectral index SR can eliminate the outside impact of the background environment, the canopy structure, and other factors. The remote sensing retrieval precision of fuel moisture content superior. It can reflect the variety characteristics of the fuel moisture content in the study area veritably.