Canopy radiative transfer (RT) modeling is critical for the quantitative retrieval of vegetation biophysical parameters and has been under intensive research over the decades. RT models of discontinuous canopies, such as three-dimensional (3D) RT models, posed challenges for the early one-dimensional (1D) hypothesis. Although 3D RT models have higher accuracy, theoretically, they suffer from two problems: detailed scene parameters and complex computational steps. To overcome these problems, the stochastic radiative transfer (SRT) theory, which is known to have the accuracy of 3D RT while being as simple as 1D RT, has been adapted from atmospheric research to the study of vegetation canopies. While the SRT model has been adopted into the operational production of vegetation parameters, its accuracy needs further improvement because of the insufficient consideration of hotspot effects. Additionally, the evaluation and validation of SRT process are still preliminary, which hinders its further development and application. To provide the community with missing information and a scientific basis for subsequent model improvement, we modified, evaluated, and validated the SRT model in this study. First, we proposed the new version of SRT model to better achieve the coupling of SRT process and hotspot effect by dividing the previous SRT into four subproblems. Then, we evaluated the performance of the modified SRT by comparing multiple intermediate variables in the SRT process with 3D computer simulations, and analyzed the model sensitivity to key input parameters as well as the spatial distribution and conservation of radiation energy. Our findings reconfirmed that the SRT theory can well describe the radiation regime of discontinuous canopies with balanced efficiency and accuracy. Moreover, the newly proposed coupling scheme of hotspot effect further improves the model performance in the hotspot regions. Finally, the unmanned aerial vehicle (UAV) observations served as a reference to validate the modeled canopy reflectance, which shows a high concordance. These results provide a detailed theoretical basis for applications and further improvements of the SRT model.

冠层辐射传输 (RT) 建模对于植被生物物理参数的定量检索至关重要，几十年来一直在深入研究。不连续檐篷的 RT 模型，例如三维 (3D) RT 模型，对早期的一维 (1D) 假设提出了挑战。3D RT模型虽然精度更高，但理论上存在两个问题：详细的场景参数和复杂的计算步骤。为了克服这些问题，已知具有 3D RT 精度同时又像 1D RT 一样简单的随机辐射传输 (SRT) 理论已从大气研究应用于植被冠层研究。虽然 SRT 模型已被用于植被参数的业务生产，由于没有充分考虑热点效应，其准确性需要进一步提高。此外，SRT工艺的评估和验证仍处于初步阶段，阻碍了其进一步发展和应用。为了向社区提供缺失的信息和后续模型改进的科学依据，我们修改、评估和验证了本研究中的 SRT 模型。首先，我们提出了新版本的 SRT 模型，通过将之前的 SRT 划分为四个子问题，更好地实现 SRT 过程和热点效应的耦合。然后，我们通过比较 SRT 过程中的多个中间变量与 3D 计算机模拟来评估改进的 SRT 的性能，并分析模型对关键输入参数的敏感性以及辐射能量的空间分布和守恒。我们的研究结果再次证实，SRT 理论可以很好地描述不连续檐篷的辐射状况，同时兼顾效率和准确性。此外，新提出的热点效应耦合方案进一步提高了热点区域的模型性能。最后，无人机 (UAV) 观测作为验证建模的冠层反射率的参考，显示出高度的一致性。这些结果为SRT模型的应用和进一步改进提供了详细的理论基础。无人机 (UAV) 观测结果作为验证模拟冠层反射率的参考，显示出高度的一致性。这些结果为SRT模型的应用和进一步改进提供了详细的理论基础。无人机 (UAV) 观测结果作为验证模拟冠层反射率的参考，显示出高度的一致性。这些结果为SRT模型的应用和进一步改进提供了详细的理论基础。