Estimation of land surface emissivity for Landsat TM6 and its application to Lingxian Region in north China

Abstract

Landsat TM has a thermal band (TM6) operating in 10.45-12.6mm, which can be used for land surface temperature (LST) retrieval. Land surface emissivity (LSE) is an essential parameter for LST retrieval. However, LSE information is generally no available for many applications. In this paper we intend to develop an applicable approach for LSE estimation so that LST can be retrieved from Landsat TM6 data. Spatial resolution of TM6 is 120m under nadir. Pixels under this scale can be viewed as composed of three land cover patterns for most natural surfaces: vegetation, bare soil/rock and water. Emissivities of these land cover patterns are relatively stable and well known, which enables us to propose a method for LSE estimation using the visible and near infrared (NIR) bands. The composition ratio of vegetation and bare soil or building under pixel scale can be estimated from bands 3 and 4 (TM3 and TM4). LSE for TM6 can then be estimated through thermal radiance equation with the composition ratio and the emissivities of the patterns known. The proposed methodology for LSE estimation is simple and easy to use, hence provides opportunity to promote the application of TM6 data to agriculture and environments. Finally we apply this methodology to Lingxian region of Shangdong Province in North China Plain, the most important agricultural region in China, for LSE estimation and LST retrieval, which has produced a reasonable estimation of thermal variation of the region.