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Evaluation of two kernel-driven models for estimating directional brightness temperature in the thermal infrared

机译：评估两个用于估计热红外方向亮度温度的内核驱动模型

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Directional anisotropy limits the application of land surface temperature (LST) and a simplified parametric model to effectively estimate directional brightness temperature (DBT) in the thermal infrared is critical. This study used a widely validated four-stream scattering by arbitrarily inclined leaves (4SAIL) model as a benchmark to evaluate the performance of the kernel bidirectional reflectance distribution function (BRDF) model and the three-kernel-model. Results showed that the two kernel-driven models can fit the DBT well and the maximum root mean square error (RMSE) is 0.13°C. The kernel BRDF model has a wider application scope including canopies of uniform, spherical, plagiophile and planophile LIDF with low LAI and hotspot. When LIDF is planophile and plagiophile, two models can reach the best fitting effect and the worst effect is the canopy with erectrophile LIDF. Under a specified LIDF, the relationship between fitting accuracy and LAI is negative while hotspot parameter is positive.
机译：方向各向异性限制了地表温度（LST）的应用，简化的参数模型对于有效估算热红外中的方向亮度温度（DBT）至关重要。这项研究使用广泛验证的任意倾斜叶四流散射（4SAIL）模型作为基准，以评估内核双向反射分布函数（BRDF）模型和三核模型的性能。结果表明，两个内核驱动模型可以很好地拟合DBT，最大均方根误差（RMSE）为0.13°C。 BRDF核模型的应用范围更广，包括具有低LAI和热点的均匀，球形，嗜嗜性和嗜嗜性LIDF的冠层。当LIDF是嗜亲和嗜粉菌时，两个模型可以达到最佳拟合效果，而最差的效果是带有嗜异性LIDF的冠层。在指定的LIDF下，拟合精度与LAI之间的关系为负，而热点参数为正。

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