Leaf transpiration of drought tolerant plant can be captured by hyperspectral reflectance using PLSR analysis
Leaf transpiration of drought tolerant plant can be captured by hyperspectral reflectance using PLSR analysis
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DOI：
10.3832/ifor1634-008
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发表时间：
2016-02
期刊：
影响因子：
--
通讯作者：
Q. Wang;J. Jin
中科院分区：
文献类型：
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作者：
Q. Wang;J. Jin
摘要：对植物蒸腾作用的清楚认识是水循环和气候模拟的关键步骤，特别是对于水分是主要限制因素之一的干旱生态系统。传统的叶尺度蒸腾量的野外测量方法在大时空尺度下往往是耗时且不可行的。以中亚干旱区的主要乡土植物梭梭为研究对象，采用偏最小二乘回归（PLSR）分析方法，通过高光谱反射率反演叶片蒸腾速率。结果表明，基于逐步回归分析所选波长的一阶导数光谱建立的PLSR模型能较好地跟踪叶片蒸腾速率，且具有较高的精度（R2 = 0.78，RMSE = 1.62 μmol g-1 s-1）。即使在10 nm的光谱分辨率下，精度也相对稳定，这非常接近于几个运行中的星载高光谱传感器的带宽。研究结果还表明，短波红外（SWIR）波段的一阶导数光谱，尤其是2435、2440、2445和2470 nm波段的一阶导数光谱，对PLSR模型预测叶片蒸腾作用具有重要意义。这些研究结果突出了一个有前途的战略，发展遥感方法，可能在广泛的尺度蒸腾特性。
Abstract: A clear understanding of plant transpiration is a crucial step for water cycle and climate modeling, especially for arid ecosystems in which water is one of the major constraints. Traditional field measurements of leaf scale transpiration are always time-consuming and often unfeasible in the context of large spatial and temporal scales. This study focused on a dominant native plant in the arid land of central Asia, Haloxylon ammondendron, with the aim of deriving the leaf-scale transpiration through hyperspectral reflectance using Partial Least Squares Regression (PLSR) analysis. The results revealed that the PLSR model based on the first-order derivative spectra at wavelengths selected through stepwise regression analysis can closely trace leaf transpiration with a high accuracy (R2 = 0.78, RMSE = 1.62 µmol g-1 s-1). The accuracy is also relatively stable even at a spectral resolution of 10 nm, which is very close to the bandwidths of several running satellite-borne hyperspectral sensors such as Hyperion. The results also proved that the first-order derivative spectra within the shortwave infrared (SWIR) domain, especially at 2435, 2440, 2445, and 2470 nm, were critical for PLSR models to predict leaf transpiration. These findings highlight a promising strategy for developing remote sensing methods to potentially characterize transpiration at broad scales.