Error Analysis of the Land Surface Temperature Retrieval Using HJ-1B Thermal Infrared Remote Sensing Data

Error analysis is playing an important role in the application of the remote sensing data and model. A theoretical analysis of error sensitivities in land surface temperature (LST) retrieval using radiance transfer model (RT) is introduced, which was applied to a new thermal infrared remote sensing data of HJ-1B satellite(IRS4). The modification of the RT model with MODTRAN 4 for IRS4 data is mentioned. Error sensitivities of the model are exhibited by analyzing the derivatives of parameters. It is shown that the greater the water vapor content and smaller the emissivity and temperature, the greater the LST retrieval error. The main error origin is from equivalent noise, uncertainty of water vapor content and emissivity, which lead to an error of 0. 7, 0. 6 and 0. 5 K on LST in typical condition, respectively. Hence, a total error of 1 K for LST has been found. It is confirmed that the LST retrieved from HJ-1B data is incredible when application requirement is more than 1K, unless more accurate in situ measurements for atmospheric parameters and emissivity are applied.