Name
Abstract | ||
|---|---|---|
•A new bottom-up hierarchical clustering algorithm to the nonphotosynthetic component extraction from MLS point clouds is proposed.•An energy function for grouping target points based on the Euclidean distance and principal direction is formulated.•The optimal combination in the clustering based on minimizing the proposed energy function is achieved.•A promising method for the stem detection and individual tree segmentation based on our extraction result is presented. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.jag.2018.02.016 | International Journal of Applied Earth Observation and Geoinformation |
Keywords | Field | DocType |
Nonphotosynthetic components,Stem,Individual tree,MLS,Urban environment,Clustering | Hierarchical clustering,Cluster (physics),Pattern recognition,Segmentation,Matrix (mathematics),Euclidean distance,Remote sensing,Correctness,Lidar,Artificial intelligence,Point cloud,Geography | Journal |
Volume | ISSN | Citations |
69 | 0303-2434 | 1 |
PageRank | References | Authors |
0.35 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sheng Xu | 1 | 507 | 71.47 |
| Shanshan Xu | 2 | 35 | 5.42 |
| Ning Ye | 3 | 223 | 15.70 |
| Fa Zhu | 4 | 55 | 5.27 |