Average leaf inclination angle (θ¯L) is an important canopy structure variable that influences light regime, photosynthesis, and evapotranspiration of plants. θ¯L can be measured through direct methods (e.g., protractor), which are labor-intensive and time-consuming, or through indirect optical instruments, which are more efficient than the direct methods. However, uncertainties of different indirect optical instruments for quantifying θ¯L remain largely unquantified. In this study, we evaluated and compared the performances of three major indirect optical instruments: (1) LAI-2200, (2) 30°-tilted camera, and (3) digital hemispherical photography (DHP), in different crop fields over a growing season, benchmarked with direct measurements. LAI-2200 and 30°-tilted camera showed higher agreement with direct θ¯ measurements (R2 = 0.54, RMSE = 7.37°; R2 = 0.58, RMSE = 8.08°) than DHP (R2 = 0.14, RMSE = 13.96°). Different performances of indirect optical instruments could be attributed to the accuracy of gap fraction measurement and the performance of the θ¯L quantification algorithms. When using the LAI-2200 algorithm, larger gap fraction gradients over view zenith angles led to larger θ¯L values, and smaller gap fraction gradients led to smaller θ¯L values. Such error propagation was larger in sparse canopy than in dense canopy. The Wilson G function of the LAI-2200 algorithm performed better in estimating θ¯L than the G function based on the ellipsoidal LAD function used by the CAN_EYE algorithm. We also proposed a modification of the LAI-2200 algorithm, which further improved the performance of LAI-2200 and 30°-tilted cameras in estimating θ¯L. We envision that the low-cost 30°-tilted cameras provide a promising sensor solution to continuously monitor canopy structure for various ecosystems.

中文翻译：

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在农田中通过间接光学仪器量化的平均叶片倾角评估


平均叶片倾角 （θ ̄L） 是一个重要的冠层结构变量，它影响植物的光照状态、光合作用和蒸散。θ ̄L 可以通过直接方法（例如量角器）进行测量，这种方法既费力又费时，也可以通过间接光学仪器进行测量，这种仪器比直接方法更有效。然而，用于定量 θ ̄L 的不同间接光学仪器的不确定性在很大程度上仍未量化。在这项研究中，我们评估和比较了三种主要间接光学仪器的性能：（1） LAI-2200，（2） 30° 倾斜相机和 （3） 数字半球摄影 （DHP），在一个生长季节的不同农田，以直接测量为基准。LAI-2200 和 30° 倾斜相机与直接 θ ̄ 测量显示出更高的一致性（R2 = 0.54，RMSE = 7.37°;R2 = 0.58，RMSE = 8.08°）比 DHP（R2 = 0.14，RMSE = 13.96°）多。间接光学仪器的不同性能可归因于间隙分数测量的准确性和 θ ̄L 量化算法的性能。使用 LAI-2200 算法时，视天顶角上的间隙分数梯度越大，θ ̄L 值越大，间隙分数梯度越小，θ ̄L 值越小。这种误差在稀疏冠层中的传播大于在密集冠层中。LAI-2200 算法的 Wilson G 函数在估计 θ ̄L 方面比基于 CAN_EYE 算法使用的椭球 LAD 函数的 G 函数表现更好。我们还提出了对 LAI-2200 算法的修改，进一步提高了 LAI-2200 和 30° 倾斜相机在估计 θ ̄L 方面的性能。 我们设想低成本的 30° 倾斜相机提供了一种有前途的传感器解决方案，以持续监测各种生态系统的树冠结构。