【摘要】 为提高现场获取地表温度与发射率的精度，在ASTER TES（Advanced Spaceborne Thermal Emission and Reflection Radiometer Temperature Emissivity Separation）算法的基础上提出了一种基于目标温度一致的地表温度与发射率分离（BTI TES）算法。首先，通过引入与温度无关的α剩余法作为先验条件，对最大发射率进行约束与估算，有效提升了算法对复杂地表的适用性。其次，基于自主研制的红外通道式野外辐射计，建立了最小发射率(ε_min)与最大-最小发射率差的经验关系模型，显著优化了温度与发射率反演精度。同时，增设多通道地表温度一致的迭代收敛条件，增强了算法物理合理性。实验结果表明：与ASTER TES算法相比，BTI TES算法反演的各通道平均发射率偏差小于0.004，地表温度偏差降低至0.07℃，且各通道温度标准偏差下降3个量级，更符合热辐射传输理论。与红外光谱仪反演参考真值的对比结果表明，BTI TES反演的地表发射率偏差为0.002±0.0018，优于ASTER TES算法的0.004±0.0019，反演的地表温度偏差为±0.055℃，优于ASTER TES算法的±0.11℃。研究表明，BTI TES算法显著提升了地表温度和发射率的反演精度，且反演得到的多通道温度一致性更高，为热红外遥感地表参数精确反演提供了新的技术手段。更多还原

【Abstract】 Objective Land surface temperature and emissivity are key parameters in the thermal radiation characteristics of the Earth’s surface, with significant applications in climate research, ecological monitoring, and agricultural yield estimation. Thermal infrared remote sensing plays a crucial role in obtaining surface temperature and emissivity, directly influencing the reliability of related research. The Advanced Spaceborne Thermal Emission and Reflection Radiometer TemperatureEmissivity Separation（ASTER TES） algorithm is one of the most widely used multi-channel surface temperature and emissivity separation methods, though there is still room for improvement in inversion accuracy and the physical reasonableness of the algorithm under complex surface conditions. Therefore, there is an urgent need to develop more efficient and accurate algorithms.Methods In this paper, we address the problem of accurately inverting surface temperature and emissivity in thermal infrared remote sensing by proposing the BTI TES algorithm, based on the temperature identity. First, to enhance the applicability of the algorithm for complex surfaces, the BTI TES algorithm introduces the temperature-independent α residual method as a prior condition to constrain and estimate the maximum emissivity. Based on the theory of thermal radiation transmission, we analyze the radiant energy distribution characteristics on the ground surface and effectively eliminate the interference from temperature factors, thus allowing for a more accurate determination of the maximum emissivity range and significantly improving the algorithm’s adaptability to different surface types. Second, using the self-developed infrared channel field radiometer, the BTI TES algorithm conducts a large number of field measurement experiments. Based on the experimental data, an empirical relationship model is built between the minimum emissivity(ε_min) and the maximum-minimum emissivity difference. The model accounts for the radiation characteristics of different surface materials and constructs a precise relationship through mathematical fitting. This optimization improves the inversion accuracy, making the results closer to the actual value. Finally, the BTI TES algorithm adds an iterative convergence condition in which the surface temperatures across multiple channels are consistent. This ensures that the surface temperatures obtained from each channel’s inversion match each other through repeated iterative calculations, in line with the principle of energy conservation in thermal radiation theory. This improvement strengthens the algorithm’s physical mechanism, preventing errors caused by temperature differences between channels and enhancing its physical validity.Results and Discussions In the paper, an area with typical complex surface features is selected as the experimental site, and both the BTI TES and ASTER TES algorithms are used to invert surface temperature and emissivity simultaneously. The inversion results from a high-precision infrared spectrometer serve as reference values for evaluating the algorithm’s performance. The experimental data show that, compared to the ASTER TES algorithm, the BTI TES algorithm significantly improves inversion accuracy. The average emissivity deviation for each channel in the BTI TES algorithm is less than 0.004, while the ASTER TES algorithm shows relatively larger deviations. For surface temperature inversion, the BTI TES algorithm reduces the deviation to 0.07 ℃, with the standard deviation of channel temperatures decreasing by three orders of magnitude, reflecting its higher precision in temperature inversion. In addition, when compared with the reference values from the infrared spectrometer, the deviation of the surface emissivity for the BTI TES inversion is 0.002±0.0018, better than the ASTER TES algorithm’s 0.004±0.0019. The deviation in surface temperature inversion is ±0.055 ℃, better than the ASTER TES algorithm’s ±0.11 ℃.Conclusions Our BTI TES algorithm significantly enhances the inversion accuracy of surface temperature and emissivity through a series of innovative improvements. The consistency in multi-channel temperature inversion is also improved. This successful development provides a new technical approach for the accurate inversion of thermal infrared remote sensing surface parameters, which is expected to play an important role in Earth science and environmental monitoring. In the future, the algorithm’s application scope can be expanded, and its performance further optimized by integrating new sensor data.更多还原