Author Affiliations
Department of Surveying and Mapping Engineering, School of Traffic & Transportation Engineering, Changsha University of Science and Technology, Changsha, Hunan 410004, Chinashow less
Fig. 1. Progressive filtering algorithm implementation process
Fig. 2. Contour generation flow chart
Fig. 3. Aerial photography of the survey area
Fig. 4. Contour to determine the shape of the stadium
Fig. 5. Point cloud contour filling distribution in the building area
Fig. 6. LiDAR point cloud distribution in the building area
Fig. 7. Tilt angle to determine the same height difference
Fig. 8. Isometric line-morphological filtering algorithm flow chart
Fig. 9. Contour determination window threshold
Fig. 10. Distribution of point cloud
Fig. 11. Samp23 survey area before and after filtering. (a) Before filtering; (b) after filtering
Fig. 12. Filtering accuracy of different height difference thresholds (window threshold is 30 m)
Fig. 13. Filtering accuracy of different window thresholds (height difference threshold is 20 m)
Fig. 14. Filtering results of different algorithms in the FSite8_red2 survey area. (a) TIN algorithm; (b) morphology algorithm
Samp23 surveypoint cloud | Number ofsample points | Number ofground points | Number offeatures | TypeI error /% | TypeII error /% |
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Sample point | 25095 | 13223 | 11872 | | | Calculated point | 25095 | 11452 | 13643 | 13.3 | 14.9 |
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Table 1. Number of point cloud points in Samp23 survey area and two types of error statistics
Samp41 surveypoint cloud | Number ofsample points | Number ofground points | Number offeatures | Type Ierror /% | Type IIerror /% |
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Sample point | 11231 | 5602 | 5629 | | | Morphology filtering | 11231 | 6294 | 4937 | 12.3 | 12.2 | TIN filtering | 11231 | 6732 | 4499 | 20.1 | 20.0 |
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Table 2. Two algorithms in Samp41 data point ground point, feature point, type I error, and type II error