Land Surface Temperature（ LST） plays an important role in energy exchange between the land surface and the atmosphere. LST is a key variable in many applications

such as land surface modeling. Many satellite-based algorithms have been proposed to retrieve LST

such as Split-Window（ SW）

dual-angle

and single-channel algorithms. In this study

four satellitebased LST retrieval algorithms

including two SW algorithms（ Juan C. Jiménez-Muoz and Offer Rozenstein SW algorithms） and two mono-window algorithms（ Juan C. Jiménez-Muoz and Qin Zhihao mono-window algorithms）

were compared with Landsat-8satellite data over the region around Wuxi City. The accuracy of the four algorithms was evaluated against the ground measurements from 16 floating stations over Lake Tai. The results showed that the performance of the two SW algorithms

which have an average error of 0. 7 K

was better than that of the SW algorithms

which have an average error of 1. 3—1. 4 K

when compared with ground measurements. The sensitivity analysis of these algorithms showed that the Juan C. Jiménez-Muoz SW algorithm was the least sensitive to key input parameters（ emissivity and water vapor）

whereas the Offer Rozenstein SW algorithm and the Qin Zhihao mono-window algorithm showed high sensitivity to input parameters. The limitations of these four LST retrieving algorithms were also discussed.