HJ-1B热红外遥感数据陆表温度反演误差分析

误差问题制约着遥感数据和模型的应用。结合HJ-1B热红外波段(IRS4)遥感数据,基于热红外辐射传输(radiant transfer,RT)模型,对陆表温度(land surface temperature,LST)反演误差源做精确理论分析,并就减小误差提出建议。首先利用MODTRAN 4修正IRS4 LST反演RT模型,通过建立偏微分方程,研究误差产生规律和各参量误差对模型总误差的贡献。分析发现,LST反演误差与随地表温度和比辐射率的升高而降低,随大气总水汽含量升高而升高;LST主要误差源为等效噪声温差、水汽估算误差和比辐射率误差,典型情况下将分别造成0.6,0.6和0.5 K的LST误差。总体而言,利用IRS4反演LST的误差在1 K左右,除非用地面探测手段将水汽误差和比辐射误差分别降低到5%和0.5%,否则IRS4数据无法满足精度高于1 K的LST应用。

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.