Identifying species of individual trees using airborne laser scanner
Identifying species of individual trees using airborne laser scanner
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DOI：
10.1016/s0034-4257(03)00140-8
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发表时间：
2004-04-30
影响因子：
13.5
通讯作者：
Persson, Å
中科院分区：
文献类型：
--
作者：
Holmgren, J;Persson, Å
使用高密度机载激光扫描仪数据可以检测到个别树木。此外，还可以测量表征检测到的树的变量，例如树高、树冠面积和树冠底部高度。斯堪的纳维亚北部针叶林主要由挪威云杉(Picea abies L.Karst.)、樟子松(Pinus cervestris L.)和落叶乔木组成。使用近红外图像可以区分针叶树和落叶树，但松树和云杉发出类似的光谱信号。机载激光扫描测量树冠的结构和形状可用于区分云杉和松树。这项研究的目的是使用从机载激光扫描数据中提取的特征，在单个树木水平上测试苏格兰松和挪威云杉的分类。现场测量用于培训和验证分类。在野外测量了12块矩形样地(50×20英寸)上所有树木的位置，并记录了树种。占主导地位的树种(80%)是挪威云杉(6块地)和苏格兰松(6块地)。实地测量的树木被自动链接到激光测量的树木。以其他样地的所有激光探测树木为训练数据，将每个样地上的激光探测树木分类为物种类。所有样地的树木分类正确率为95%。对单株树冠基高估计值也进行了估算(r=0.84)。本研究的分类结果证明了利用激光数据区分松树和云杉的能力。这种方法可以应用于业务环境中。在第一步中，使用激光数据对单个树冠进行分割。在第二步中，基于分段进行树种分类。未来可能会开发出将激光数据与数字近红外照片相结合的方法，对挪威云杉、苏格兰松和落叶乔木这三个类别进行分类。(C)2003 Elsevier Inc.保留所有权利。
Individual trees can be detected using high-density airborne laser scanner data. Also, variables characterizing the detected trees such as tree height, crown area, and crown base height can be measured. The Scandinavian boreal forest mainly consists of Norway spruce (Picea abies L. Karst.), Scots pine (Pinus sylvestris L.), and deciduous trees. It is possible to separate coniferous from deciduous trees using near-infrared images, but pine and spruce give similar spectral signals. Airborne laser scanning, measuring structure and shape of tree crowns could be used for discriminating between spruce and pine. The aim of this study was to test classification of Scots pine versus Norway spruce on an individual tree level using features extracted from airborne laser scanning data. Field measurements were used for training and validation of the classification. The position of all trees on 12 rectangular plots (50 X 20 in 2) were measured in field and tree species was recorded. The dominating species (>80%) was Norway spruce for six of the plots and Scots pine for six plots. The field-measured trees were automatically linked to the laser-measured trees. The laser-detected trees on each plot were classified into species classes using all laser-detected trees on the other plots as training data. The portion correctly classified trees on all plots was 95%. Crown base height estimations of individual trees were also evaluated (r=0.84). The classification results in this study demonstrate the ability to discriminate between pine and spruce using laser data. This method could be applied in an operational context. In the first step, a segmentation of individual tree crowns is performed using laser data. In the second step, tree species classification is performed based on the segments. Methods could be developed in the future that combine laser data with digital near-infrared photographs for classification with the three classes: Norway spruce, Scots pine, and deciduous trees. (C) 2003 Elsevier Inc. All rights reserved.