A Study on the Selection of Parameter Values of FUSION Software for Improving Airborne LiDAR DEM Accuracy in Forest Area
2017
Cho, S., Kyungpook National University, Daegu, Republic of Korea | Park, J., Kyungpook National University, Daegu, Republic of Korea
This study aims to evaluate whether the accuracy of LiDAR DEM is affected by the changes of the five input levels ('1','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. The Tukey 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 Imn 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.
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