数字农科院2.0

An effective method for LST decomposition based on the linear spectral mixing model

文献类型： 外文期刊

作者： Song Cai-Ying;Wang Fei;Qin Zhi-Hao

作者机构：

关键词： landsat TM;linear spectral mixing model (LSMM);temperature vegetation index (TVX);lanol surface temperature(LST) decomposition;Beijing

期刊名称： JOURNAL OF INFRARED AND MILLIMETER WAVES

ISSN： 1001-9014

年卷期： 2015 年 34 卷 4 期

页码：

收录情况： SCI

摘要： This paper proposed a new pixel decomposition model of Temperature Unmixing with Spectral (TUS). Landsat TM data acquired in Beijing were used for the study. Firstly, land surface fraction was obtained based on the Linear Spectral Mixing Model. Secondly and LST of typical endmember was selected through Temperature Vegetation Index. Finally, pixel decomposition of LST can be achieved integrated emissivity with different surface components. Our results indicated that TUS can effectively improve the spatial resolution of land surface temperature, reflecting the spatial differences of surface components, with MAE and RMSE 1.25K and 2.27K respectively. Therefore we conclude that TUS model is applicable for decomposition of LST images for high spatial resolution in the complex surface coverage area.

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