Leaf photosynthetic parameters are important in understanding the role of photosynthesis in the carbon cycle. Conventional approaches to obtain information on the parameters usually involve long-term field work, even for one leaf sample, and are, thus, only applicable to a small area. The utilization of hyperspectral remote sensing especially of various vegetation indices is a promising approach that has been attracting increasing attention recently. However, most hyperspectral indices are only applicable to a specific area and specific forest stands, depending heavily on the conditions from which the indices are developed. In this study, we tried to develop new hyperspectral indices for tracing the two critical photosynthetic parameters (the maximum rate of carboxylation, Vcmax and the maximum rate of electron transport, Jmax) that are at least generally applicable for alpine deciduous forests, based on original hyperspectral reflectance, first-order derivatives, and apparent absorption spectra. In total, ten types of hyperspectral indices were screened to identify the best indices, and their robustness was determined using the ratio of performance to deviation (RPD) and Akaike’s Information Criterion corrected (AICc). The result revealed that the double differences (DDn) type of indices using the short-wave infrared (SWIR) region based on the first-order derivatives spectra performed best among all indices. The specific DDn type of indices obtained the RPD values of 1.43 (R2 = 0.51) for Vcmax and 1.68 (R2 = 0.64) for Jmax, respectively. These indices have also been tested using the downscaled dataset to examine the possibilities of using hyperspectral data derived from satellite-based information. These findings highlight the possibilities of tracing photosynthetic capacity using hyperspectral indices.

中文翻译：

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高光谱指数在高寒落叶林中跟踪叶片光合参数的研究

叶片光合作用参数对于理解光合作用在碳循环中的作用很重要。获取有关参数信息的常规方法通常涉及长期的野外工作，即使对于一片叶子样品也是如此，因此仅适用于一小块区域。利用高光谱遥感尤其是各种植被指数是一种很有前途的方法，近来已引起越来越多的关注。但是，大多数高光谱指数仅适用于特定区域和特定林分，这在很大程度上取决于该指数的开发条件。在这项研究中，我们尝试开发新的高光谱指数来追踪两个关键的光合作用参数（最大羧化速率，Vcmax和最大电子传输速率，基于原始高光谱反射率，一阶导数和表观吸收光谱，至少通常适用于高山落叶林。总共筛选了十种类型的高光谱指数以识别最佳指数，并使用性能偏差比（RPD）和Akaike信息校正标准（AICc）确定了它们的鲁棒性。结果表明，使用基于一阶导数光谱的短波红外（SWIR）区域的双差（DDn）类型在所有指数中表现最佳。特定的DDn指数对Vcmax的RPD值分别为1.43（R2 = 0.51），对Jmax的RPD值分别为1.68（R2 = 0.64）。还使用缩减的数据集对这些索引进行了测试，以检查使用基于卫星的信息得出的高光谱数据的可能性。这些发现凸显了使用高光谱指数追踪光合作用能力的可能性。