Forest data collection using terrestrial image-based point clouds from a handheld camera compared to terrestrial and personal laser scanning

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Forest data collection using terrestrial image-based point clouds from a handheld camera compared to terrestrial and personal laser scanning. / Liang, Xinlian; Wang, Yunsheng; Jaakkola, Anttoni; Kukko, Antero; Kaartinen, Harri; Hyyppä, Juha; Honkavaara, Eija; Liu, Jingbin.

In: IEEE Transactions on Geoscience and Remote Sensing, Vol. 53, No. 9, 7109840, 01.09.2015, p. 5117-5132.

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Liang, Xinlian ; Wang, Yunsheng ; Jaakkola, Anttoni ; Kukko, Antero ; Kaartinen, Harri ; Hyyppä, Juha ; Honkavaara, Eija ; Liu, Jingbin. / Forest data collection using terrestrial image-based point clouds from a handheld camera compared to terrestrial and personal laser scanning. In: IEEE Transactions on Geoscience and Remote Sensing. 2015 ; Vol. 53, No. 9. pp. 5117-5132.

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@article{743dd7fb87354aa3b3fe5a7cf8dd2abd,
title = "Forest data collection using terrestrial image-based point clouds from a handheld camera compared to terrestrial and personal laser scanning",
abstract = "Stereo images have long been the main practical data source for the high-accuracy retrieval of 3-D information over large areas. However, stereoscopy has been surpassed by laser scanning (LS) techniques in recent years, particularly in forested areas, because the reflection of laser points from object surfaces directly provides 3-D geometric features and because the laser beam has good penetration capacity through forest canopies. In the last few years, image-based point clouds have become a more widely available data source because of advances in matching algorithms and computer hardware. This paper explores the possibility of using consumer cameras for forest field data collection and presents an application of terrestrial image-based point clouds derived from a handheld camera to forest plot inventories. In the experiment, the sample forest plot was photographed in a stop-and-go mode using different routes and camera settings. Five data sets were generated from photographs taken in the field, representing different photographic conditions. The stem detection accuracy ranged between 60{\%} and 84{\%}, and the root-mean-square errors of the estimated diameters at breast height were between 2.98 and 6.79 cm. The performance of image-based point clouds in forest data collection was compared with that of point clouds derived from two LS techniques, i.e., terrestrial LS (the professional level) and personal LS (an emerging technology). The study indicates that the construction of image-based point clouds of forest field data requires only low-cost, low-weight, and easy-to-use equipment and automated data processing. Photographic measurement is easy and relatively fast. The accuracy of tree attribute estimates is close to an acceptable level for forest field inventory but is lower than that achieved with the tested LS techniques.",
keywords = "Forest inventory, handheld camera, image-based point cloud, laser scanning (LS), Light Detection And Ranging (LiDAR), point cloud, structure from motion, terrestrial",
author = "Xinlian Liang and Yunsheng Wang and Anttoni Jaakkola and Antero Kukko and Harri Kaartinen and Juha Hyypp{\"a} and Eija Honkavaara and Jingbin Liu",
year = "2015",
month = "9",
day = "1",
doi = "10.1109/TGRS.2015.2417316",
language = "English",
volume = "53",
pages = "5117--5132",
journal = "IEEE Transactions on Geoscience and Remote Sensing",
issn = "0196-2892",
number = "9",

}

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TY - JOUR

T1 - Forest data collection using terrestrial image-based point clouds from a handheld camera compared to terrestrial and personal laser scanning

AU - Liang, Xinlian

AU - Wang, Yunsheng

AU - Jaakkola, Anttoni

AU - Kukko, Antero

AU - Kaartinen, Harri

AU - Hyyppä, Juha

AU - Honkavaara, Eija

AU - Liu, Jingbin

PY - 2015/9/1

Y1 - 2015/9/1

N2 - Stereo images have long been the main practical data source for the high-accuracy retrieval of 3-D information over large areas. However, stereoscopy has been surpassed by laser scanning (LS) techniques in recent years, particularly in forested areas, because the reflection of laser points from object surfaces directly provides 3-D geometric features and because the laser beam has good penetration capacity through forest canopies. In the last few years, image-based point clouds have become a more widely available data source because of advances in matching algorithms and computer hardware. This paper explores the possibility of using consumer cameras for forest field data collection and presents an application of terrestrial image-based point clouds derived from a handheld camera to forest plot inventories. In the experiment, the sample forest plot was photographed in a stop-and-go mode using different routes and camera settings. Five data sets were generated from photographs taken in the field, representing different photographic conditions. The stem detection accuracy ranged between 60% and 84%, and the root-mean-square errors of the estimated diameters at breast height were between 2.98 and 6.79 cm. The performance of image-based point clouds in forest data collection was compared with that of point clouds derived from two LS techniques, i.e., terrestrial LS (the professional level) and personal LS (an emerging technology). The study indicates that the construction of image-based point clouds of forest field data requires only low-cost, low-weight, and easy-to-use equipment and automated data processing. Photographic measurement is easy and relatively fast. The accuracy of tree attribute estimates is close to an acceptable level for forest field inventory but is lower than that achieved with the tested LS techniques.

AB - Stereo images have long been the main practical data source for the high-accuracy retrieval of 3-D information over large areas. However, stereoscopy has been surpassed by laser scanning (LS) techniques in recent years, particularly in forested areas, because the reflection of laser points from object surfaces directly provides 3-D geometric features and because the laser beam has good penetration capacity through forest canopies. In the last few years, image-based point clouds have become a more widely available data source because of advances in matching algorithms and computer hardware. This paper explores the possibility of using consumer cameras for forest field data collection and presents an application of terrestrial image-based point clouds derived from a handheld camera to forest plot inventories. In the experiment, the sample forest plot was photographed in a stop-and-go mode using different routes and camera settings. Five data sets were generated from photographs taken in the field, representing different photographic conditions. The stem detection accuracy ranged between 60% and 84%, and the root-mean-square errors of the estimated diameters at breast height were between 2.98 and 6.79 cm. The performance of image-based point clouds in forest data collection was compared with that of point clouds derived from two LS techniques, i.e., terrestrial LS (the professional level) and personal LS (an emerging technology). The study indicates that the construction of image-based point clouds of forest field data requires only low-cost, low-weight, and easy-to-use equipment and automated data processing. Photographic measurement is easy and relatively fast. The accuracy of tree attribute estimates is close to an acceptable level for forest field inventory but is lower than that achieved with the tested LS techniques.

KW - Forest inventory

KW - handheld camera

KW - image-based point cloud

KW - laser scanning (LS)

KW - Light Detection And Ranging (LiDAR)

KW - point cloud

KW - structure from motion

KW - terrestrial

UR - http://www.scopus.com/inward/record.url?scp=84933044107&partnerID=8YFLogxK

U2 - 10.1109/TGRS.2015.2417316

DO - 10.1109/TGRS.2015.2417316

M3 - Article

VL - 53

SP - 5117

EP - 5132

JO - IEEE Transactions on Geoscience and Remote Sensing

JF - IEEE Transactions on Geoscience and Remote Sensing

SN - 0196-2892

IS - 9

M1 - 7109840

ER -

ID: 9810888