The Estimation of Land Surface Emissivity for Landsat Tm6

Land surface emissivity (LSE) is an essential parameter for land surface temperature (LST) retrieval from thermal remote sensing data. Up till now, three methods have been proposed for LST retrieval from TM6 data, namely, atmospheric correction, mono-window algorithm and single channel algorithm, which all require LSE as a parameter. In this paper the authors have first reviewed the three methods and then dealt emphatically with the estimation of this parameter. The method was applied to Lingxian area of Shangdong Province in North China Plain, the most important agricultural area in China, for LSE estimation and LST retrieval. The result shows that the method can yield a reasonable estimation of thermal variation of that area.