不同含水量条件下树种叶片光谱差异分析

叶片含水量是影响树种光谱特征的一个重要因素，探索不同叶片含水量条件下相同树种叶片光谱特征的变化规律及相同叶片含水量条件下不同树种叶片的光谱差异，不仅是高光谱植被遥感信息识别的关键，也为研究植被光谱随着叶片含水量变化产生的差异提供理论支撑。利用地物光谱仪对6个树种叶片进行观测，获取了不同含水量叶片的反射光谱，同时进行一阶微分光谱变换，从而分析不同叶片含水量条件下各树种叶片的光谱变化特征，对比了相同叶片含水量条件下不同树种叶片的光谱差异，探索高光谱遥感识别树种叶片含水量的可能波段。结果表明：各树种叶片光谱都随着叶片含水量的改变而产生较大差异，但变化规律各有不同;相同叶片含水量条件下，不同树种叶片的光谱在部分波长范围差异较大，为实现树种高精度识别提供了可能。本研究旨在为植被叶片光谱库的构建以及植被的高光谱识别提供理论支撑和基础数据。

Spectrum Variance Analysis of Tree Leaves under the Condition of Different Leaf water Content

Leaf water content is an important factor affecting tree spectral characteristics. So Exploring the leaf spectral characteristics change rule of the same tree under the condition of different leaf water content and the spectral differences of different tree leaves under the condition of the same leaf water content are not only the keys of hyperspectral vegetation remote sensing information identification but also the theoretical support of research on vegetation spectrum change as the differences in leaf water content. The spectrometer was used to observe six species of tree leaves, and the reflectivity and first order differential spectrum of different leaf water content were obtained. Then, the spectral characteristics of each tree species leaves under the condition of different leaf water content were analyzed, and the spectral differences of different tree species leaves under the condition of the same leaf water content were compared to explore possible bands of the leaf water content identification by hyperspectral remote sensing. Results show that the spectra of each tree leaf have changed a lot with the change of the leaf water content, but the change laws are different. Leaf spectral of different tree species has lager differences in some wavelength range under the condition of same leaf water content, and it provides some possibility for high precision identification of tree species.