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首页> 外文期刊>Journal of Korean Forest Society >A Study on the Selection of Parameter Values of FUSION Software for Improving Airborne LiDAR DEM Accuracy in Forest Area
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A Study on the Selection of Parameter Values of FUSION Software for Improving Airborne LiDAR DEM Accuracy in Forest Area

机译：融合软件参数值选择，改善林区空气流雷达姆的融合软件

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摘要

This study aims to evaluate whether the accuracy of LiDAR DEM is affected by the changes of the five input levels ('r,'3','5','7' and '9') of median parameter (Fmd), mean parameter (Fmn) of the Filtering Algorithm (FA) in the GroundFilter module and median parameter (Imd), mean parameter (Imn) of the Interpolation Algorithm (IA) in the GridSurfaceCreate module of the FUSION in order to present the combination of parameter levels producing the most accurate LiDAR DEM. The accuracy is measured by the residuals calculated by difference between the field elevation values and their corresponding DEM elevation values. A multi-way ANOVA is used to statistically examine whether there are effects of parameter level changes on the means of the residuals. TheTukey HSD is conducted as a post-hoc test. The results of the multi- way ANOVA test show that the changes in the levels of Fmd, Fmn, Imn have significant effects on the DEM accuracy with the significant interaction effect between Fmd and Fmn. Therefore,the level of Fmd, Fmn, and the interaction between two variables are considered to be factors affecting the accuracy of LiDAR DEM as well as the level of Imn. As the results of the Tukey HSD test on the combination levels of Fmd*Fmn, the mean of residuals of the '9*3' combination provides the highest accuracy while the '1*1' combination provides the lowest one. Regarding I_(MN) levels, the mean of residuals of the both '3' and '1' provides the highest accuracy. This study can contribute to improve the accuracy of the forest attributes as well as the topographic information extracted from the LiDAR data.
机译：本研究旨在评估LIDAR DEM的准确性是否受到中位数（FMD）的五个输入水平（'r，'3'，'5'，'和'9'）的变化的影响，平均参数（FMN）在融合器的GridSurfaceCreate模块中的接地模块和中位数（IMD）中的过滤算法（FA），平均参数（IA）的平均参数（IMN），以呈现参数水平产生的组合最准确的激光器dem。精度由通过现场高度值与其对应的DEM高程值之间的差异计算的残差来测量。多种方式ANOVA用于统计检查是否存在参数级别的效果对残差的手段。 TheTukey HSD作为HOC测试后进行。多向ANOVA测试的结果表明，FMD，FMN，IMN水平的变化对DEM精度具有显着影响，FMD和FMN之间的显着相互作用效果。因此，FMD，FMN和两个变量之间的相互作用的水平被认为是影响LIDAR DEM的准确性以及IMN水平的因素。由于Tuke HSD测试对FMD * FMN的组合级别的结果，“9 * 3”组合的残差的平均值提供了最高的精度，而“1 * 1”组合提供最低的精度。关于I_（MN）级别，“3”和“1”的残差的平均值提供了最高的精度。该研究可以有助于提高林业属性的准确性以及从激光雷达数据中提取的地形信息。

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