A novel technique for tree stem height estimation by fusing low density LiDAR data and optical images

Claudia Paris; Lorenzo Bruzzone

doi:10.1109/IGARSS.2013.6723462

A novel technique for tree stem height estimation by fusing low density LiDAR data and optical images

Claudia Paris
, Lorenzo Bruzzone

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

1 Citation (Scopus)

Abstract

Light detection and ranging (LiDAR) is one of the most efficient remote sensing technologies for the estimation of forest parameters. However, when acquired with a low laser sampling density, LiDAR data fail in providing accurate tree height measures. In order to address this issue, in this paper we propose a novel technique for the reconstruction of tree-top height based on the joint use of low-density LiDAR data and high resolution optical images. The proposed method is based on the following steps: i) detection of all the tree crowns present in the scene by fusing the two remotely sensed data sources; ii) reconstruction of the tree-top height for those crown hit by at least one LiDAR point; iii) estimation of the tree-top height for those crowns without LiDAR points. The proposed technique has been tested on a coniferous forest located in the Italian Alps. The experimental results points out the effectiveness of the proposed method.

Original language	English
Title of host publication	International Geoscience and Remote Sensing Symposium (IGARSS)
Publisher	IEEE
Pages	3022-3025
Number of pages	4
ISBN (Electronic)	978-1-4799-1114-1
DOIs	https://doi.org/10.1109/IGARSS.2013.6723462
Publication status	Published - 27 Jan 2014
Externally published	Yes
Event	33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013: Building a Sustainable Earth through Remote Sensing - Melbourne, Australia Duration: 21 Jul 2013 → 26 Jul 2013 Conference number: 33 http://www.igarss2013.org/

Publication series

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

Conference

Conference	33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013
Abbreviated title	IGARSS
Country/Territory	Australia
City	Melbourne
Period	21/07/13 → 26/07/13
Internet address	http://www.igarss2013.org/

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10.1109/IGARSS.2013.6723462

Cite this

@inproceedings{2c9734966fae46b4b026702e6f6a7449,

title = "A novel technique for tree stem height estimation by fusing low density LiDAR data and optical images",

abstract = "Light detection and ranging (LiDAR) is one of the most efficient remote sensing technologies for the estimation of forest parameters. However, when acquired with a low laser sampling density, LiDAR data fail in providing accurate tree height measures. In order to address this issue, in this paper we propose a novel technique for the reconstruction of tree-top height based on the joint use of low-density LiDAR data and high resolution optical images. The proposed method is based on the following steps: i) detection of all the tree crowns present in the scene by fusing the two remotely sensed data sources; ii) reconstruction of the tree-top height for those crown hit by at least one LiDAR point; iii) estimation of the tree-top height for those crowns without LiDAR points. The proposed technique has been tested on a coniferous forest located in the Italian Alps. The experimental results points out the effectiveness of the proposed method.",

author = "Claudia Paris and Lorenzo Bruzzone",

year = "2014",

month = jan,

day = "27",

doi = "10.1109/IGARSS.2013.6723462",

language = "English",

publisher = "IEEE",

pages = "3022--3025",

booktitle = "International Geoscience and Remote Sensing Symposium (IGARSS)",

address = "United States",

note = "33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 : Building a Sustainable Earth through Remote Sensing, IGARSS ; Conference date: 21-07-2013 Through 26-07-2013",

url = "http://www.igarss2013.org/",

}

Paris, C & Bruzzone, L 2014, A novel technique for tree stem height estimation by fusing low density LiDAR data and optical images. in International Geoscience and Remote Sensing Symposium (IGARSS)., 6723462, IEEE, pp. 3022-3025, 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013, Melbourne, Victoria, Australia, 21/07/13. https://doi.org/10.1109/IGARSS.2013.6723462

TY - GEN

T1 - A novel technique for tree stem height estimation by fusing low density LiDAR data and optical images

AU - Paris, Claudia

AU - Bruzzone, Lorenzo

N1 - Conference code: 33

PY - 2014/1/27

Y1 - 2014/1/27

N2 - Light detection and ranging (LiDAR) is one of the most efficient remote sensing technologies for the estimation of forest parameters. However, when acquired with a low laser sampling density, LiDAR data fail in providing accurate tree height measures. In order to address this issue, in this paper we propose a novel technique for the reconstruction of tree-top height based on the joint use of low-density LiDAR data and high resolution optical images. The proposed method is based on the following steps: i) detection of all the tree crowns present in the scene by fusing the two remotely sensed data sources; ii) reconstruction of the tree-top height for those crown hit by at least one LiDAR point; iii) estimation of the tree-top height for those crowns without LiDAR points. The proposed technique has been tested on a coniferous forest located in the Italian Alps. The experimental results points out the effectiveness of the proposed method.

AB - Light detection and ranging (LiDAR) is one of the most efficient remote sensing technologies for the estimation of forest parameters. However, when acquired with a low laser sampling density, LiDAR data fail in providing accurate tree height measures. In order to address this issue, in this paper we propose a novel technique for the reconstruction of tree-top height based on the joint use of low-density LiDAR data and high resolution optical images. The proposed method is based on the following steps: i) detection of all the tree crowns present in the scene by fusing the two remotely sensed data sources; ii) reconstruction of the tree-top height for those crown hit by at least one LiDAR point; iii) estimation of the tree-top height for those crowns without LiDAR points. The proposed technique has been tested on a coniferous forest located in the Italian Alps. The experimental results points out the effectiveness of the proposed method.

UR - https://www.scopus.com/pages/publications/84894285457

U2 - 10.1109/IGARSS.2013.6723462

DO - 10.1109/IGARSS.2013.6723462

M3 - Conference contribution

SP - 3022

EP - 3025

BT - International Geoscience and Remote Sensing Symposium (IGARSS)

PB - IEEE

T2 - 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013

Y2 - 21 July 2013 through 26 July 2013

ER -

A novel technique for tree stem height estimation by fusing low density LiDAR data and optical images

Abstract

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