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LASER-BASED FIELD MEASUREMENTS IN TREE-LEVEL FOREST DATA ACQUISITION

机译:树级森林数据采集中基于激光的野外测量

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Remote-sensing (RS) methods, such as airborne laser scanning (ALS), are capable of acquiring tree-level forest information with high accuracy. However, these methods need more detailed reference data from sample plots than standwise mean characteristics. Field-measured treewise characteristics must be matched with ALS data on the measured position of the tree. In addition to tree position and species, diameter-at-breast height (dbh) measurements are an essential part of these reference data, since dbh at the individual tree level cannot be measured directly from the ALS data. Here we compare the accuracy in treewise field measurements with different laser-based methods in practice. The characteristics under observation include dbh, tree height and stem position. The comparable instruments used include the Terrestrial laser scanner (TLS), laser-relascope and laser-camera. The data consist of 122 trees from sample plots in Saunalahti and Nuuksio. The standard errors in dbh measurements were 8.3 mm (4.5%), 8.5 mm (4.9%) and 14.3 mm (8.3%) with the TLS, laser-camera and laser-relascope, respectively. The standard errors in positional accuracy of the tree were 0.1 m with the TLS and 0.7 m with the laser-relascope. A bias of -0.6 m (-5.2%) and standard error of 1.0 m (10.1%) were present in tree height measurements with the laser-relascope. The results of the study can be utilized e.g. in developing new cost-efficient methods for collecting ground truth data for ALS-based inventories.
机译:遥感(RS)方法,例如机载激光扫描(ALS),能够以高精度获取树级森林信息。但是,这些方法需要样本图中比常规平均特征更详细的参考数据。现场测量的树状特征必须与树的测量位置上的ALS数据匹配。除了树木的位置和种类以外,胸径(dbh)的直径测量也是这些参考数据的重要组成部分,因为不能直接从ALS数据中测量单个树木级别的dbh。在这里,我们在实践中使用不同的基于激光的方法来比较树状场测量的精度。被观察的特征包括dbh,树高和茎的位置。所使用的可比较仪器包括地面激光扫描仪(TLS),激光相对论仪和激光相机。数据由Saunalahti和Nuuksio的样地中的122棵树组成。使用TLS,激光相机和激光相对论仪的dbh测量的标准误差分别为8.3 mm(4.5%),8.5 mm(4.9%)和14.3 mm(8.3%)。 TLS定位树的标准精度的标准误差为0.1 m,激光相对反射镜为0.7 m。用激光相对论仪测量树高时,存在-0.6 m(-5.2%)的偏差和1.0 m(10.1%)的标准误差。研究结果可以利用例如。开发新的具有成本效益的方法来收集基于ALS的库存的地面真实数据。

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