[1]LI Dou,LI Pengfei,MU Xingmin,et al.Accuracy of Airborne LiDAR Point Cloud Filtering for Areas with Complex Terrain[J].Research of Soil and Water Conservation,2021,28(04):171-178.
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Accuracy of Airborne LiDAR Point Cloud Filtering for Areas with Complex Terrain
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
28
Number of periods:
2021 04
Page number:
171-178
Column:
Public date:
2021-08-10
- Title:
- Accuracy of Airborne LiDAR Point Cloud Filtering for Areas with Complex Terrain
- Keywords:
- Airborne LiDAR; filtering algorithms; terrain expression; microtopographic change monitoring; the Loess Plateau
- CLC:
- P237
- DOI:
- -
- Abstract:
- In order to explore the filtering algorithm which is suitable for the airborne LIADR point cloud data in the complex terrain area and provide an effective means for the monitoring of microtopographic changes and surface processes. In this article, five commonly-used algorithms(MCC, ETEW, ATIN, PM, and SBF)were employed to filter the point cloud data of 12 sample areas in a small catchment(i.e. Dongzhuanggou)of the gullied Loess Plateau. The accuracy of the five algorithms was evaluated based on the method suggested by the International Society for Photogrammetry and Remote Sensing, while its relationship with impacting factors(slope gradient, vegetation coverage, point density)were also assessed. Results showed that the type Ⅰ errors(misclassification ratio of ground points)of MCC and PM were generally lowest, type Ⅰ error of the ETEW and SBF were highest, and those of ATIN were in the middle. The sequence of type Ⅱ(misclassification ratio of non-ground points)and total errors(misclassification ratio of total points)of the algorithms were roughly opposite to that of the type I error. The PM, compared to other algorithms, yielded the best filtering results for steep-sloping areas. Slope gradients and vegetation coverage significantly affected type Ⅰ errors of the employed algorithms rather than type Ⅱ and total errors. The increase(decrease)rate of type Ⅰ error with slope gradients(vegetation coverage)was lowest for MCC and PM, and highest for ETEW, with that of SBF and ATIN being in the middle. With the increase of the point density, the type Ⅰ errors of MCC, ATIN and PM did not change apparently, and the type Ⅱ and total errors slowly decreased, while the type Ⅰ errors of SBF and ETEW increased, and the type Ⅱ errors and total errors decreased.
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Last Update:
2021-08-20