Zhao Li-Min, Yu Tao, Tian Qing-Jiu, Gu Xing-Fa, Li Jia-Guo, Wan Wei
International Institute for Earth System Science, Nanjing University, Nanjing 210093, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2010 Dec;30(12):3359-62.
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.
误差分析在遥感数据与模型的应用中发挥着重要作用。介绍了利用辐射传输模型（RT）反演陆地表面温度（LST）时误差敏感性的理论分析，该分析应用于HJ-1B卫星（IRS4）的新型热红外遥感数据。提及了用MODTRAN 4对IRS4数据的RT模型进行修正。通过分析参数的导数来展示模型的误差敏感性。结果表明，水汽含量越高、发射率和温度越低，LST反演误差越大。主要误差来源是等效噪声、水汽含量和发射率的不确定性，在典型条件下分别导致LST误差为0.7 K、0.6 K和0.5 K。因此，发现LST的总误差为1 K。证实了当应用要求高于1 K时，从HJ-1B数据反演的LST不可信，除非对大气参数和发射率进行更精确的现场测量。
