基于苹果树冠层计盒维数的光照分布预测  

Illumination spatial distribution prediction method based on apple tree canopy box-counting dimension

作　　者：郭彩玲[1,2] 张伟洁 刘刚[1] 冯娟[3] Guo Cailing;Zhang Weijie;Liu Gang;Feng Juan(Key Lab of Modern Precision Agriculture System Integration Research,Ministry of Education of China,Key Lab of Agricultural Information Acquisition Technology,Ministry of Agricultural of China,China Agricultural University,Beijing 100083,China;Department of Electromechanical Engineering,Tangshan University,Tangshan 063000,China;College of Information Science&Technology,Hebei Agricultural University,Baoding 071001,China)

机构地区：[1]现代精细农业系统集成研究教育部重点实验室,农业部农业信息获取技术重点实验室,中国农业大学,北京100083 [2]唐山学院机电工程系,唐山063000 [3]河北农业大学信息科学与技术学院,保定071001

出　　处：《农业工程学报》2018年第16期177-183,共7页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家自然科学基金资助项目(31371532);河北省自然科学基金项目(C2015204043);河北省高等学校科学技术研究项目(QN2017417);河北省科技计划项目(16227211)。

摘　　要：果园精细管理中,苹果树冠层结构决定了叶幕期光照分布情况,而叶幕期光照分布又是关系到果实产量和质量的重要因素之一。该文以纺锤体苹果树为研究对象,提出了基于苹果树冠层计盒维数的光照分布预测方法。在冠层尺度内,按照网格法划分休眠期苹果树冠层三维点云数据,通过分析该数据构成的果树冠层空间结构,提出用计盒维数量化果树冠层结构的方法;通过分析休眠期冠层结构特征和叶幕期冠层相对光照分布特点,研究了休眠期苹果树三维冠层网格空间计盒维数与叶幕期冠层光照空间分布之间的关系,预测了叶幕成形期苹果树冠层光照分布。通过连续3 a的数据分析,叶幕期苹果树冠层阳面光照分布平均预测精度为76.11%,阴面平均光照分布预测精度为74.10%,该方法可为苹果树自动化修剪合理性评判提供技术支持。The fruit tree canopy structure determines the canopy illumination spatial distribution(CISD)in every growth stage,and especially in the stable stage,the CISD degree is one of the most important factors related to fruit yield and quality.In the fine management of orchards,in the quiescent stage,trees were trimmed to ideal structures in order to get the high quality CISD in the stable stage.As we all know,the trimming effect directly affects the distribution of the CISD.To analyze the CISD associated with the spring pruning in the apple tree canopy,spindle-shaped apple tree was taken as the research object,and a predicting methodology,the illumination spatial distribution prediction method considering apple tree canopy fractal features,was proposed based on the three-dimensional(3D)canopy structure.In this study,the canopy was divided into cell grids regularly.The Trimble TX8 was used to get the 3D apple tree canopy point clouds,and then the tree canopy point clouds were cut into cell grids as the same size as in the orchards,too.To describe the different structures within the canopy,each cell grid was projected on a horizontal surface,which was perpendicular to the tree trunk and parallel to the ground.The projection of each grid was different,but similar with each other.Because of these characteristics,a new box-counting dimension based on 3D point clouds projection approach of the cell grid was used to describe different cell grids’spatial structure.Onset light intensity acquisition system was used to obtain the illumination intensity in each cell grid in the stable growth stage from June to September.Further,the average illumination intensity of corresponding cell grid was calculated.In the prediction research work,a practical new hybrid model to predict trimming effect based on the relative CISD in apple tree canopy was proposed.The model was based on particle swarm optimization(PSO)in combination with support vector machines(SVMs).This optimization mechanism involved kernel parameter setting in the SVM tra

关 键 词：林业 预测 光照 三维点云 苹果树冠层计盒维数 PSO-SVM 

分 类 号：F762.5[经济管理—产业经济] P225[天文地球—大地测量学与测量工程]