Holmgren, Johan and Lindberg, Eva
(2019).
Tree crown segmentation based on a tree crown density model derived from Airborne Laser Scanning.
Remote Sensing Letters. 10
, 1143-1152
[Research article]
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Abstract
This letter describes a new algorithm for automatic tree crown delineation based on a model of tree crown density, and its validation. The tree crown density model was first used to create a correlation surface, which was then input to a standard watershed segmentation algorithm for delineation of tree crowns. The use of a model in an early step of the algorithm neatly solves the problem of scale selection. In earlier studies, correlation surfaces have been used for tree crown segmentation, involving modelling tree crowns as solid geometric shapes. The new algorithm applies a density model of tree crowns, which improves the model's suitability for segmentation of Airborne Laser Scanning (ALS) data because laser returns are located inside tree crowns. The algorithm was validated using data acquired for 36 circular (40 m radius) field plots in southern Sweden. The algorithm detected high proportions of field-measured trees (40-97% of live trees in the 36 field plots: 85% on average). The average proportion of detected basal area (cross-sectional area of tree stems, 1.3 m above ground) was 93% (range: 84-99%). The algorithm was used with discrete return ALS point data, but the computation principle also allows delineation of tree crowns in ALS waveform data.
Authors/Creators: | Holmgren, Johan and Lindberg, Eva | ||||||
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Title: | Tree crown segmentation based on a tree crown density model derived from Airborne Laser Scanning | ||||||
Series Name/Journal: | Remote Sensing Letters | ||||||
Year of publishing : | 2019 | ||||||
Volume: | 10 | ||||||
Page range: | 1143-1152 | ||||||
Number of Pages: | 10 | ||||||
Publisher: | TAYLOR & FRANCIS LTD | ||||||
ISSN: | 2150-704X | ||||||
Language: | English | ||||||
Publication Type: | Research article | ||||||
Article category: | Scientific peer reviewed | ||||||
Version: | Published version | ||||||
Copyright: | Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0 | ||||||
Full Text Status: | Public | ||||||
Subjects: | (A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing (A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Forest Science | ||||||
URN:NBN: | urn:nbn:se:slu:epsilon-p-101610 | ||||||
Permanent URL: | http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-101610 | ||||||
Additional ID: |
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ID Code: | 23369 | ||||||
Faculty: | S - Faculty of Forest Sciences | ||||||
Department: | (S) > Dept. of Forest Resource Management (NL, NJ) > Dept. of Forest Resource Management | ||||||
Deposited By: | SLUpub Connector | ||||||
Deposited On: | 29 Apr 2021 11:07 | ||||||
Metadata Last Modified: | 03 May 2021 06:52 |
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