Next Article in Journal
Digital Terrain Models Generated with Low-Cost UAV Photogrammetry: Methodology and Accuracy
Previous Article in Journal
Could Historical Mortality Data Predict Mortality Due to Unexpected Events?
Article

Marker-Less UAV-LiDAR Strip Alignment in Plantation Forests Based on Topological Persistence Analysis of Clustered Canopy Cover

by 1, 1,*, 2 and 2
1
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
2
Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, 159 Longpan Road, Nanjing 210037, China
*
Author to whom correspondence should be addressed.
Academic Editors: Andrew Skidmore and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2021, 10(5), 284; https://doi.org/10.3390/ijgi10050284
Received: 9 February 2021 / Revised: 25 March 2021 / Accepted: 26 April 2021 / Published: 29 April 2021
A holistic strategy is established for automated UAV-LiDAR strip adjustment for plantation forests, based on hierarchical density-based clustering analysis of the canopy cover. The method involves three key stages: keypoint extraction, feature similarity and correspondence, and rigid transformation estimation. Initially, the HDBSCAN algorithm is used to cluster the scanned canopy cover, and the keypoints are marked using topological persistence analysis of the individual clusters. Afterward, the feature similarity is calculated by considering the linear and angular relationships between each point and the pointset centroid. The one-to-one feature correspondence is retrieved by solving the assignment problem on the similarity score function using the Kuhn–Munkres algorithm, generating a set of matching pairs. Finally, 3D rigid transformation parameters are determined by permutations over all conceivable pair combinations within the correspondences, whereas the best pair combination is that which yields the maximum count of matched points achieving distance residuals within the specified tolerance. Experimental data covering eighteen subtropical forest plots acquired from the GreenValley and Riegl UAV-LiDAR platforms in two scan modes are used to validate the method. The results are extremely promising for redwood and poplar tree species from both the Velodyne and Riegl UAV-LiDAR datasets. The minimal mean distance residuals of 31 cm and 36 cm are achieved for the coniferous and deciduous plots of the Velodyne data, respectively, whereas their corresponding values are 32 cm and 38 cm for the Riegl plots. Moreover, the method achieves both higher matching percentages and lower mean distance residuals by up to 28% and 14 cm, respectively, compared to the baseline method, except in the case of plots with extremely low tree height. Nevertheless, the mean planimetric distance residual achieved by the proposed method is lower by 13 cm. View Full-Text
Keywords: UAV-LiDAR; strip alignment; hierarchical DBSCAN clustering; canopy analysis; forest UAV-LiDAR; strip alignment; hierarchical DBSCAN clustering; canopy analysis; forest
Show Figures

Figure 1

MDPI and ACS Style

Fekry, R.; Yao, W.; Cao, L.; Shen, X. Marker-Less UAV-LiDAR Strip Alignment in Plantation Forests Based on Topological Persistence Analysis of Clustered Canopy Cover. ISPRS Int. J. Geo-Inf. 2021, 10, 284. https://doi.org/10.3390/ijgi10050284

AMA Style

Fekry R, Yao W, Cao L, Shen X. Marker-Less UAV-LiDAR Strip Alignment in Plantation Forests Based on Topological Persistence Analysis of Clustered Canopy Cover. ISPRS International Journal of Geo-Information. 2021; 10(5):284. https://doi.org/10.3390/ijgi10050284

Chicago/Turabian Style

Fekry, Reda, Wei Yao, Lin Cao, and Xin Shen. 2021. "Marker-Less UAV-LiDAR Strip Alignment in Plantation Forests Based on Topological Persistence Analysis of Clustered Canopy Cover" ISPRS International Journal of Geo-Information 10, no. 5: 284. https://doi.org/10.3390/ijgi10050284

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop