Segmentation of Individual Tree Points by Combining Marker-Controlled Watershed Segmentation and Spectral Clustering Optimization Article Swipe
YOU?
·
· 2024
· Open Access
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· DOI: https://doi.org/10.3390/rs16040610
Accurate identification and segmentation of individual tree points are crucial for assessing forest spatial distribution, understanding tree growth and structure, and managing forest resources. Traditional methods based on Canopy Height Models (CHM) are simple yet prone to over- and/or under-segmentation. To deal with this problem, this paper introduces a novel approach that combines marker-controlled watershed segmentation with a spectral clustering algorithm. Initially, we determined the local maxima within a series of variable windows according to the lower bound of the prediction interval of the regression equation between tree crown radius and tree height to preliminarily segment individual trees. Subsequently, using this geometric shape analysis method, the under-segmented trees were identified. For these trees, vertical tree crown profile analysis was performed in multiple directions to detect potential treetops which were then considered as inputs for spectral clustering optimization. Our experiments across six plots showed that our method markedly surpasses traditional approaches, achieving an average Recall of 0.854, a Precision of 0.937, and an F1-score of 0.892.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs16040610
- https://www.mdpi.com/2072-4292/16/4/610/pdf?version=1707266365
- OA Status
- gold
- Cited By
- 20
- References
- 58
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391564560
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391564560Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/rs16040610Digital Object Identifier
- Title
-
Segmentation of Individual Tree Points by Combining Marker-Controlled Watershed Segmentation and Spectral Clustering OptimizationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-06Full publication date if available
- Authors
-
Yuchan Liu, Dong Chen, Shihan Fu, P. Takis Mathiopoulos, Mingming Sui, Jiaming Na, Jiju PeethambaranList of authors in order
- Landing page
-
https://doi.org/10.3390/rs16040610Publisher landing page
- PDF URL
-
https://www.mdpi.com/2072-4292/16/4/610/pdf?version=1707266365Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2072-4292/16/4/610/pdf?version=1707266365Direct OA link when available
- Concepts
-
Watershed, Segmentation, Cluster analysis, Spectral clustering, Tree (set theory), Artificial intelligence, Pattern recognition (psychology), Computer science, Mathematics, Machine learning, CombinatoricsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
20Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 13, 2024: 7Per-year citation counts (last 5 years)
- References (count)
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58Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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