苏 伟,郭 皓,赵冬玲,张明政,张 蕊,吴代英.基于地基激光雷达的玉米真实叶面积提取方法研究[J].农业机械学报,2016,47(7):345-353.
Su Wei,Guo Hao,Zhao Dongling,Zhang Mingzheng,Zhang Rui,Wu Daiying.Estimation of Actual Leaf Area of Maize Based on Terrestrial Laser Scanning[J].Transactions of the Chinese Society for Agricultural Machinery,2016,47(7):345-353.
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基于地基激光雷达的玉米真实叶面积提取方法研究   [下载全文]
Estimation of Actual Leaf Area of Maize Based on Terrestrial Laser Scanning   [Download Pdf][in English]
投稿时间:2016-01-20  
DOI:10.6041/j.issn.1000-1298.2016.07.047
中文关键词:  玉米  地基激光雷达  真实叶面积  体素化
基金项目:国家自然科学基金项目(41371327)
作者单位
苏 伟 中国农业大学 
郭 皓 中国农业大学 
赵冬玲 中国农业大学 
张明政 中国农业大学
山东农业大学 
张 蕊 中国农业大学 
吴代英 中国农业大学 
中文摘要:叶面积指数(LAI)是定量描述植物叶片生长状态的重要参数,相较于受叶片聚集情况影响较大的有效LAI,真实LAI更能准确反映作物真实的生长状态。地基激光雷达(TLS)可以快速获取高精度植物的高度、密度、叶倾角、叶面积等作物结构信息,但在叶面积信息获取上主要得到的是有效LAI。借鉴体素化的思想,提出了基于体素内叶片及其投影数学关系的真实叶面积获取方法。该方法充分利用TLS在获取垂直结构信息上的优势,将表征玉米真实生长状态的点云数据作为数据源,利用体素将玉米叶片回波点云分割成一系列叶片单元,基于体素内叶片及其投影数学关系求取叶片单元面积,进而实现玉米真实叶面积的获取。通过利用不同激光雷达扫描仪分别于北京和河北两地获取的不同品种、不同尺度的4个样本点的玉米TLS点云数据进行验证:样本点1、2、3的试验数据为单木尺度,采用不同体素大小计算叶面积。结果表明,该方法计算所得叶面积与实测叶面积具有较高的相关性,决定系数均在0.8以上,方法可信度较高;最优体素大小分别为0.17、0.15、0.15cm,在相应最优体素大小下,RMSE分别为61898、44058、42844cm2,植株总叶面积之间的相对误差分别为-2.678%、0.619%、-0.474%,误差较小,精度较高。样本点4的玉米点云数据属于群体尺度,叶面积计算结果与实测叶面积之间的绝对误差为-14.663%,计算结果偏小。由此可知,基于体素内叶片及其投影数学关系的真实叶面积获取方法切实可行,且精度较高。
Su Wei  Guo Hao  Zhao Dongling  Zhang Mingzheng  Zhang Rui  Wu Daiying
China Agricultural University,China Agricultural University,China Agricultural University,China Agricultural University;Shandong Agricultural University,China Agricultural University and China Agricultural University
Key Words:maize  terrestrial laser scanning  actual leaf area  voxelization
Abstract:Leaf area index (LAI) is one of important parameters of quantitative description of leaf growth situation. Compared with effective LAI which is influenced by gathering condition among leaves greatly, actual LAI can reflect the real crop growth status more accurately. Terrestrial laser scanning (TLS) can obtain high precision crop structure information quickly such as height and biomass. But in terms of leaf area information, the major part is effective LAI. Reference to the idea of voxelization, the method was put forward for estimating actual leaf area of maize according to the leaf and its projective plane’s mathematical relationship in voxel, which makes full use of TLS’s advantage of gathering vertical information. The point data which can perform maize actual growth state as the data source directly. And the maize point cloud was divided into a series of leaf unit by voxel. The leaf unit area based on the leaf and its projective plane’s mathematical relationship in voxel were calculated. Then the maize actual leaf area was calculated. The different TLS was used to obtain four sample’s maize point clouds which were different in varieties and scales in both Beijing City and Hebei Province, respectively. The point obtained from sample points (No. 1, 2, 3) is individual maize point, and the actual LAI was calculated in different voxel sizes. The main conclusions are as follow: calculated LAI has a good correlation with measured LAI as all of decision coefficients are greater than 0.8, it proved that this method is credibly. The optimal voxel size is 0.17cm, 0.15cm and 0.15cm, respectively. Relevant with the optimal voxel size, RMSE is 61898cm2,44058cm2 and 42844cm2 respectively, the relative error between the plant total leaf area is -2.678%, 0.619% and -0.474% accordingly. The result means that this method has a high accuracy. In the sample point No.4, the relative error between calculated LAI and measured LAI is -14.663%, the calculated LAI is smaller than measured LAI. All in all, the method about estimating actual leaf area of maize according to the leaf and its projective plane’s mathematical relationship in voxel is feasible with high precision.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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