Extracting the individual trees of urban forests from high density airborne LiDAR data

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MORADI A.; SATARI M.; MOMENI M.

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Journal: Iranian journal of Forest Year:2018 | Volume:10 | Issue:1 Page(s): 27-42

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Information Journal Paper

Title

Extracting the individual trees of urban forests from high density airborne LiDAR data

Author(s)

MORADI A. | SATARI M. | MOMENI M. | Issue Writer Certificate

Keywords

OPTICs clusteringQ1

Point cloudQ1

Principal Components AnalysisQ1

Tree extractionQ1

Abstract

Airborne LiDAR (Light Detection and Ranging) has a high potential to provide 3D data for research and operational applications in a wide range of disciplines related to management of forest ecosystems and urban trees. Most proposed methods for extracting the individual trees first detect the points of tree top or bottom and then use them as starting points in a segmentation algorithm. Hence, in these methods, the number and the locations of detected peak points effect on the process of detecting individual trees heavily. In this study, a new method is presented to extract the individual tree segments using LiDAR points with 10 cm point density. In this method, a two-step strategy is performed for the extraction of individual tree LiDAR points: finding deterministic segments of individual trees points and allocation of other LiDAR points based on these segments. This research is performed on two study areas in Zeebrugge, Bruges, Belgium. The accuracy assessment of this method showed that with the increasing detection rate of young trees, it could correctly classified 74. 51% of trees with 21. 57% and 3. 92% under-and over-segmentation errors, respectively.

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APA: Copy

MORADI, A., SATARI, M., & MOMENI, M.. (2018). Extracting the individual trees of urban forests from high density airborne LiDAR data. IRANIAN JOURNAL OF FOREST, 10(1 ), 27-42. SID. https://sid.ir/paper/123134/en

Vancouver: Copy

MORADI A., SATARI M., MOMENI M.. Extracting the individual trees of urban forests from high density airborne LiDAR data. IRANIAN JOURNAL OF FOREST[Internet]. 2018;10(1 ):27-42. Available from: https://sid.ir/paper/123134/en

IEEE: Copy

A. MORADI, M. SATARI, and M. MOMENI, “Extracting the individual trees of urban forests from high density airborne LiDAR data,” IRANIAN JOURNAL OF FOREST, vol. 10, no. 1 , pp. 27–42, 2018, [Online]. Available: https://sid.ir/paper/123134/en

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