Land surface temperature (LST) is the key parameter for characterizing the water and energy balance of the Earth’ surface. At present, thermal infrared (TIR) remote sensing provides the most efficient way to obtain accurate LST regionally and globally. Among existing satellites, the Landsat-9 could observe the Earth's surface via two TIR channels, making it possible to generate the global LST product with a remarkable spatial resolution of 100 m. Currently, the single channel method and split window method generally were used to recover LST from the Landsat-9 TIR measurements. However, accurate land surface emissivity (LSE) is needed in both algorithms, which is very difficult to obtain at the pixel scale. To overcome this issue, an improved LST and LSE separation method was proposed in this study. Firstly, the traditional water vapor scaling (WVS) method was refined to address the atmospheric effects in the satellite measurements. Then, the traditional temperature and emissivity separation method (TES) was adapted to the Landsat-9 observations with only two TIR channels. Finally, an iterative process was designed to retrieve the LST and LSE simultaneously. Validations using in-situ measured LST indicated that the root mean square error (RMSE) of the retrieved LST was around 2.92 K, outperforming the official Landsat-9 LST product with an RMSE of about 4.20 K. Taking ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) products as the references, the RMSE of our retrieved LST and LSE was found to be < 1.55 K and < 0.015, respectively. Overall, conclusions can be made that the proposed method was able to retrieve accurate LST and LSE simultaneously from the Landsat-9 TIR measurements with high spatial resolution, which may greatly facilitate the relevant applications.

中文翻译：

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Landsat-9 热红外数据对地表温度和发射率反演的改进


地表温度 （LST） 是表征地球表面水和能量平衡的关键参数。目前，热红外 （TIR） 遥感提供了在区域和全球范围内获得精确 LST 的最有效方法。在现有的卫星中，Landsat-9 可以通过两个 TIR 通道观测地球表面，从而可以生成具有 100 m 非凡空间分辨率的全球 LST 产品。目前，单通道法和裂窗法通常用于从 Landsat-9 TIR 测量中恢复 LST。然而，这两种算法都需要精确的地表发射率 （LSE），这在像素尺度上很难获得。为了克服这个问题，本研究提出了一种改进的 LST 和 LSE 分离方法。首先，改进传统的水汽标度 （WVS） 方法以解决卫星测量中的大气影响。然后，将传统的温度和发射率分离方法 （TES） 应用于只有两个 TIR 通道的 Landsat-9 观测。最后，设计了一个迭代过程来同时检索 LST 和 LSE。使用原位测量的 LST 的验证表明，检索到的 LST 的均方根误差 （RMSE） 约为 2.92 K，优于官方的 Landsat-9 LST 产品，RMSE 约为 4.20 K。以生态系统空间站星载热辐射计实验 （ECOSTRESS） 产品为参考，我们检索到的 LST 和 LSE 的 RMSE 为 < 1.55 K 和 < 0.015， 分别。 总体而言，可以得出结论，所提出的方法能够以高空间分辨率同时从 Landsat-9 TIR 测量中检索准确的 LST 和 LSE，这可能极大地促进了相关应用。