A hierarchical approach to the segmentation of single dominant and dominated trees in forest areas by using high-density LiDAR data

Claudia Paris; Davide Valduga; Lorenzo Bruzzone

doi:10.1109/IGARSS.2015.7325698

A hierarchical approach to the segmentation of single dominant and dominated trees in forest areas by using high-density LiDAR data

Claudia Paris, Davide Valduga, Lorenzo Bruzzone

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

4 Citations (Scopus)

Abstract

In this paper we present a hierarchical approach to the segmentation of high-density LiDAR data which aims to automatically detect and delineate the single tree crowns of both the dominant and the dominated layers of the forest. First, we detect the dominant tree crowns by using both the image derived from the LiDAR data and the LiDAR point cloud. Hence, the detected crowns are delineated directly in the LiDAR point cloud by means of a radial angular analysis. Second, the dominated crowns are detected by analyzing the vertical profile of the dominant trees. Finally, we extract the dominated trees, thus reconstructing the structure of the forest. Experiments carried out in a forest area located in the Southern Italian Alps by using very high density LiDAR data (up to 50 points/m 2 ) point out the effectiveness of the proposed approach.

Original language	Undefined
Title of host publication	2015 IEEE International Geoscience & Remote Sensing Symposium
Subtitle of host publication	Proceedings
Publisher	IEEE
Pages	65-68
Number of pages	4
ISBN (Electronic)	978-1-4799-7929-5, 978-1-4799-7928-8
DOIs	https://doi.org/10.1109/IGARSS.2015.7325698
Publication status	Published - 12 Nov 2015
Externally published	Yes
Event	IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015: Remote Sensing: Understanding the Earth for a Safer World - Milan, Italy Duration: 26 Jul 2015 → 31 Jul 2015 http://www.igarss2015.org/

Publication series

Name
ISSN (Print)	2153-6996
ISSN (Electronic)	2153-7003

Conference

Conference	IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
Abbreviated title	IGARSS 2015
Country/Territory	Italy
City	Milan
Period	26/07/15 → 31/07/15
Internet address	http://www.igarss2015.org/

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10.1109/IGARSS.2015.7325698

Cite this

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title = "A hierarchical approach to the segmentation of single dominant and dominated trees in forest areas by using high-density LiDAR data",

abstract = "In this paper we present a hierarchical approach to the segmentation of high-density LiDAR data which aims to automatically detect and delineate the single tree crowns of both the dominant and the dominated layers of the forest. First, we detect the dominant tree crowns by using both the image derived from the LiDAR data and the LiDAR point cloud. Hence, the detected crowns are delineated directly in the LiDAR point cloud by means of a radial angular analysis. Second, the dominated crowns are detected by analyzing the vertical profile of the dominant trees. Finally, we extract the dominated trees, thus reconstructing the structure of the forest. Experiments carried out in a forest area located in the Southern Italian Alps by using very high density LiDAR data (up to 50 points/m 2 ) point out the effectiveness of the proposed approach.",

author = "Claudia Paris and Davide Valduga and Lorenzo Bruzzone",

year = "2015",

month = nov,

day = "12",

doi = "10.1109/IGARSS.2015.7325698",

language = "Undefined",

publisher = "IEEE",

pages = "65--68",

booktitle = "2015 IEEE International Geoscience & Remote Sensing Symposium",

note = "null ; Conference date: 26-07-2015 Through 31-07-2015",

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}

Paris, C, Valduga, D & Bruzzone, L 2015, A hierarchical approach to the segmentation of single dominant and dominated trees in forest areas by using high-density LiDAR data. in 2015 IEEE International Geoscience & Remote Sensing Symposium: Proceedings., 7325698, IEEE, pp. 65-68, IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015, Milan, Italy, 26/07/15. https://doi.org/10.1109/IGARSS.2015.7325698

A hierarchical approach to the segmentation of single dominant and dominated trees in forest areas by using high-density LiDAR data. / Paris, Claudia; Valduga, Davide; Bruzzone, Lorenzo.

2015 IEEE International Geoscience & Remote Sensing Symposium: Proceedings. IEEE, 2015. p. 65-68 7325698.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - A hierarchical approach to the segmentation of single dominant and dominated trees in forest areas by using high-density LiDAR data

AU - Paris, Claudia

AU - Valduga, Davide

AU - Bruzzone, Lorenzo

PY - 2015/11/12

Y1 - 2015/11/12

N2 - In this paper we present a hierarchical approach to the segmentation of high-density LiDAR data which aims to automatically detect and delineate the single tree crowns of both the dominant and the dominated layers of the forest. First, we detect the dominant tree crowns by using both the image derived from the LiDAR data and the LiDAR point cloud. Hence, the detected crowns are delineated directly in the LiDAR point cloud by means of a radial angular analysis. Second, the dominated crowns are detected by analyzing the vertical profile of the dominant trees. Finally, we extract the dominated trees, thus reconstructing the structure of the forest. Experiments carried out in a forest area located in the Southern Italian Alps by using very high density LiDAR data (up to 50 points/m 2 ) point out the effectiveness of the proposed approach.

AB - In this paper we present a hierarchical approach to the segmentation of high-density LiDAR data which aims to automatically detect and delineate the single tree crowns of both the dominant and the dominated layers of the forest. First, we detect the dominant tree crowns by using both the image derived from the LiDAR data and the LiDAR point cloud. Hence, the detected crowns are delineated directly in the LiDAR point cloud by means of a radial angular analysis. Second, the dominated crowns are detected by analyzing the vertical profile of the dominant trees. Finally, we extract the dominated trees, thus reconstructing the structure of the forest. Experiments carried out in a forest area located in the Southern Italian Alps by using very high density LiDAR data (up to 50 points/m 2 ) point out the effectiveness of the proposed approach.

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BT - 2015 IEEE International Geoscience & Remote Sensing Symposium

PB - IEEE

Y2 - 26 July 2015 through 31 July 2015

ER -

A hierarchical approach to the segmentation of single dominant and dominated trees in forest areas by using high-density LiDAR data

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