单子叶植物叶片双向反射分布的测量与分析  

Measurement and Analysis of Bidirectional Reflectance Distribution in Monocotyledonous Leaves

作　　者：刘丁瑜 易加维 张徐洲[1] 张畅[1] 刘飞[1,2] 方慧 何勇[1,2] LIU Ding-yu;YI Jia-wei;ZHANG Xu-zhou;ZHANG Chang;LIU Fei;FANG Hui;HE Yong(College of Biosystems Engineering and Food Science,Zhejiang University,Hangzhou 310058,China;Key Laboratory of Spectrum Detection,Ministry of Agriculture and Rural Affairs,Hangzhou 310058,China)

机构地区：[1]浙江大学生物系统工程与食品科学学院,浙江杭州310058 [2]农业部光谱检测重点实验室,浙江杭州310058

出　　处：《光谱学与光谱分析》2019年第7期2100-2106,共7页Spectroscopy and Spectral Analysis

基　　金：国家高技术研究发展计划(863计划)项目(2013AA10230401);浙江省重点研发计划项目(2017C02031)资助

摘　　要：作物的生物含量与作物的光学特性有直接的关系,而植物叶片的双向反射分布函数(BRDF)又直接影响植物的光学特性。植物叶片的BRDF体现了叶片在各个方向不同的能量反射能力,直接影响植物叶片的光谱检测结果,也是植被冠层宏观光学特征的影响因素之一。对植物叶片的BRDF光学特性及表现出的规律性展开研究和讨论,能够有效提高植物无损检测光谱模型的稳定性和可靠性,提升利用作物光谱模型反演理化特性的准确性和可靠性。首先介绍了植物叶片的BRDF快速获取方法及自主研发的方向性光谱检测仪器,该仪器能够在入射光的方位角和天顶角、接收探头的方位角和天顶角这四个维度进行调整,实现多入射角和反射角的反射光谱数据采集。单子叶植物的叶脉呈纵向分布,因而体现出较为显著的各向异性,玉米和小麦是两种较为典型的单子叶农作物。通过自主研发仪器获取不同波段范围下的玉米和小麦的反射光谱信息,并分析总结其反射分布规律。采用文中所介绍的BRDF计算方法对光谱数据以及白板校正数据进行计算,再结合MATLAB程序对光谱反射数据的图像映射,对反射结果与叶绿素含量和叶片含水量这两个叶片典型理化参数的相关性进行分析,最后探讨了采用ANIX系数对叶片的各向异性进行量化分析的方法。选取小麦在可见光波段以及玉米在近红外波段的数据,结果表明,小麦和玉米在各波段下的fr分布均关于入射天顶角两侧微小空间对称,在相同波段下,不同入射天顶角下的fr值大小基本一致;在相同入射天顶角下,小麦在800nm波段下的fr值最大,680nm波段下的fr值最小,这是由于680nm波长附近是叶绿素强吸收的特征波段,而800nm附近是叶绿素反射的特征波段,且在相同波段下,叶绿素浓度的升高会导致fr值的增大;在水的强吸收特征波段1450nm下,玉米的fr值随着含水量�The biological content of crops is directly related to the optical properties of the crops, which are affected by the bidirectional reflectance distribution function(BRDF) of plants. The BRDF of plant leaves reflects the energy reflection ability of leaves in different directions and directly affects the spectral detection results of plant leaves, also one of the influencing factors of macroscopic optical characteristics of vegetation canopy. Studying the BRDF optical properties of plant leaves can effectively improve the stability and reliability of the plant NDT spectral model, thus improving the accuracy and reliability of using the crop spectral model to invert the physicochemical properties. In this paper, we first introduced the BRDF rapid acquisition method for plant leaves and the independently developed directional spectral detection instrument which can adjust the four dimensions of incident light azimuth and zenith angle, receiver probe azimuth and zenith angle to receive the reflectance data under multi-incidence and multi-reflectance angle. The leaf veins of monocotyledonous plants are longitudinally distributed, thus showing more significant anisotropy. Maize and wheat are two typical monocotyledonous crops. Then the self-developed instruments were used to obtain the reflectance spectra of corn and wheat under different wavebands, and their reflection distribution was analyzed and summarized. The spectral data and whiteboard correction data were calculated by using the BRDF calculation method described in this paper. In combination with the image mapping of spectral reflectance data from MATLAB program, the correlation of the reflectance results with two typical physicochemical parameters of leaves, chlorophyll content and water content was analyzed. After analysis, the method of using ANIX coefficient to quantitatively analyze the anisotropy of blade was discussed. The data of wheat in the visible light band and corn in the near infrared band were selected for final analysis. The results show that

关 键 词：双向反射分布 双向反射分布函数 反射光分布检测 方向性 量化分析 

分 类 号：O433.1[机械工程—光学工程]