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Structured Pointcloud Segmentation for Individual Mangrove Tree Modeling
- Source :
- Lecture Notes in Computer Science ISBN: 9783030490751, MCPR
- Publication Year :
- 2020
- Publisher :
- Springer International Publishing, 2020.
-
Abstract
- Tree structure parameters of mangrove forests are hard to measure in the field and therefore inventories of this type of forests are impossible to keep up to date. In this article, we tested a structured pointcloud segmentation method for extracting individual mangrove trees. Structure parameters of individual trees were estimated from the segmented pointcloud and its 3d geometry was generated using revolution surfaces. Estimated parameters were then assessed at both plot and tree levels using field data. It was observed that the number of segments in each test plot agreed well with the number of trees observed in the field. Nonetheless, the estimated parameters exhibited mixed accuracy with top height being the most accurate.
- Subjects :
- Test plot
0211 other engineering and technologies
02 engineering and technology
Field (geography)
Plot (graphics)
Tree (data structure)
Tree structure
Statistics
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Segmentation
3d geometry
Mangrove
021101 geological & geomatics engineering
Mathematics
Subjects
Details
- ISBN :
- 978-3-030-49075-1
- ISBNs :
- 9783030490751
- Database :
- OpenAIRE
- Journal :
- Lecture Notes in Computer Science ISBN: 9783030490751, MCPR
- Accession number :
- edsair.doi...........eb1dad427d57378168e52855c3700f7a