In this study, we retrieved the land surface temperature (LST) of Guangzhou on Jan 14, 2013 from HJ-1B satellite data. The retrieval was based on the characteristics of HJ-1B thermal infrared band and revised QK&B algorithm was adopted. The established partial differential equation showed that emissivity error of 0.01 resulted in LST error of around 0.6 K. The LST error was inversely proportional to the atmospheric transmittance and proportional to the atmospheric transmittance error; The transmittance error of 0.1 resulted in LST error of around 1 K. Meanwhile, the atmospheric water vapor error and the LST error exhibited a linear relationship; The atmospheric water vapor error of 0.1 g/cm2 resulted in LST error of around 0.2 K. The LST retrieval error was proportional to both the nearsurface air temperature error and the average atmospheric error; The near-surface air temperature error of 1 K led to the LST retrieval error of around 1 K. Overall, at a constant ratio relation between emissivity and atmospheric transmittance, the LST retrieval error are related to the average atmospheric temperature error as well as the nearsurface air temperature error. The retrieved land surface temperature of Guangzhou was in strong spatial accordance with the MOD11_L2 LST product. The temperature difference curve exhibited a normal distribution, concentrating in the range of -0.9K to 0.9K. Six observation areas in Guangzhou were chosen to compare the LST obtained by the revised QK&B algorithm with the measured average land surface temperature. The difference between the LST obtained using the algorithm and the measured temperature was around 0.31 K, whereas the MOD11_L2 product had a difference of around 0.65 K with the measured surface temperature, both of them are less than 1 K. By deriving the partial differential equations of the revised QK&B algorithm, a more detailed and precise analysis was performed on the LST retrieval from HJ-1B/IRS data. This study offers a reference for similar LST retrieval algorithms based on thermal infrared band of environmental satellites, as well as a scientific basis for future accuracy improvement of LST retrieval.