Terrestrial structure from motion photogrammetry for deriving forest inventory data

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Terrestrial structure from motion photogrammetry for deriving forest inventory data. / Piermattei, Livia; Karel, Wilfried; Wang, Di; Wieser, Martin; Mokroš, Martin; Surový, Peter; Koreň, Milan; Tomaštík, Julián; Pfeifer, Norbert; Hollaus, Markus.

In: Remote Sensing, Vol. 11, No. 8, 950, 01.04.2019.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Piermattei, L, Karel, W, Wang, D, Wieser, M, Mokroš, M, Surový, P, Koreň, M, Tomaštík, J, Pfeifer, N & Hollaus, M 2019, 'Terrestrial structure from motion photogrammetry for deriving forest inventory data', Remote Sensing, vol. 11, no. 8, 950. https://doi.org/10.3390/rs11080950

APA

Piermattei, L., Karel, W., Wang, D., Wieser, M., Mokroš, M., Surový, P., ... Hollaus, M. (2019). Terrestrial structure from motion photogrammetry for deriving forest inventory data. Remote Sensing, 11(8), [950]. https://doi.org/10.3390/rs11080950

Vancouver

Author

Piermattei, Livia ; Karel, Wilfried ; Wang, Di ; Wieser, Martin ; Mokroš, Martin ; Surový, Peter ; Koreň, Milan ; Tomaštík, Julián ; Pfeifer, Norbert ; Hollaus, Markus. / Terrestrial structure from motion photogrammetry for deriving forest inventory data. In: Remote Sensing. 2019 ; Vol. 11, No. 8.

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@article{19b039154b654398862400ced8d16e94,
title = "Terrestrial structure from motion photogrammetry for deriving forest inventory data",
abstract = "The measurements of tree attributes required for forest monitoring and management planning, e.g., National Forest Inventories, are derived by rather time-consuming field measurements on sample plots, using calipers and measurement tapes. Therefore, forest managers and researchers are looking for alternative methods. Currently, terrestrial laser scanning (TLS) is the remote sensing method that provides the most accurate point clouds at the plot-level to derive these attributes from. However, the demand for even more efficient and effective solutions triggers further developments to lower the acquisition time, costs, and the expertise needed to acquire and process 3D point clouds, while maintaining the quality of extracted tree parameters. In this context, photogrammetry is considered a potential solution. Despite a variety of studies, much uncertainty still exists about the quality of photogrammetry-based methods for deriving plot-level forest attributes in natural forests. Therefore, the overall goal of this study is to evaluate the competitiveness of terrestrial photogrammetry based on structure from motion (SfM) and dense image matching for deriving tree positions, diameters at breast height (DBHs), and stem curves of forest plots by means of a consumer grade camera. We define an image capture method and we assess the accuracy of the photogrammetric results on four forest plots located in Austria and Slovakia, two in each country, selected to cover a wide range of conditions such as terrain slope, undergrowth vegetation, and tree density, age, and species. For each forest plot, the reference data of the forest parameters were obtained by conducting field surveys and TLS measurements almost simultaneously with the photogrammetric acquisitions. The TLS data were also used to estimate the accuracy of the photogrammetric ground height, which is a necessary product to derive DBHs and tree heights. For each plot, we automatically derived tree counts, tree positions, DBHs, and part of the stem curve from both TLS and SfM using a software developed at TUWien (Forest Analysis and Inventory Tool, FAIT), and the results were compared. The images were oriented with errors of a few millimetres only, according to checkpoint residuals. The automatic tree detection rate for the SfM reconstruction ranges between 65{\%} and 98{\%}, where the missing trees have average DBHs of less than 12 cm. For each plot, the mean error of SfM and TLS DBH estimates is -1.13 cm and -0.77 cm with respect to the caliper measurements. The resulting stem curves show that the mean differences between SfM and TLS stem diameters is at maximum -2.45 cm up to 3 m above ground, which increases to almost +4 cm for higher elevations. This study shows that with the adopted image capture method, terrestrial SfM photogrammetry, is an accurate solution to support forest inventory for estimating the number of trees and their location, the DBHs and stem curve up to 3 m above ground.",
keywords = "Diameter at breast height, Plot-based forest inventory, Structure from motion, Terrestrial laser scanning, Terrestrial photogrammetry, plot-based forest inventory, terrestrial photogrammetry, HEIGHT, ACCURACY, terrestrial laser scanning, DIAMETER, structure from motion, MODELS, BIOMASS, HAND-HELD CAMERA, diameter at breast height, LASER SCANNER",
author = "Livia Piermattei and Wilfried Karel and Di Wang and Martin Wieser and Martin Mokroš and Peter Surov{\'y} and Milan Koreň and Juli{\'a}n Tomašt{\'i}k and Norbert Pfeifer and Markus Hollaus",
year = "2019",
month = "4",
day = "1",
doi = "10.3390/rs11080950",
language = "English",
volume = "11",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "8",

}

RIS - Download

TY - JOUR

T1 - Terrestrial structure from motion photogrammetry for deriving forest inventory data

AU - Piermattei, Livia

AU - Karel, Wilfried

AU - Wang, Di

AU - Wieser, Martin

AU - Mokroš, Martin

AU - Surový, Peter

AU - Koreň, Milan

AU - Tomaštík, Julián

AU - Pfeifer, Norbert

AU - Hollaus, Markus

PY - 2019/4/1

Y1 - 2019/4/1

N2 - The measurements of tree attributes required for forest monitoring and management planning, e.g., National Forest Inventories, are derived by rather time-consuming field measurements on sample plots, using calipers and measurement tapes. Therefore, forest managers and researchers are looking for alternative methods. Currently, terrestrial laser scanning (TLS) is the remote sensing method that provides the most accurate point clouds at the plot-level to derive these attributes from. However, the demand for even more efficient and effective solutions triggers further developments to lower the acquisition time, costs, and the expertise needed to acquire and process 3D point clouds, while maintaining the quality of extracted tree parameters. In this context, photogrammetry is considered a potential solution. Despite a variety of studies, much uncertainty still exists about the quality of photogrammetry-based methods for deriving plot-level forest attributes in natural forests. Therefore, the overall goal of this study is to evaluate the competitiveness of terrestrial photogrammetry based on structure from motion (SfM) and dense image matching for deriving tree positions, diameters at breast height (DBHs), and stem curves of forest plots by means of a consumer grade camera. We define an image capture method and we assess the accuracy of the photogrammetric results on four forest plots located in Austria and Slovakia, two in each country, selected to cover a wide range of conditions such as terrain slope, undergrowth vegetation, and tree density, age, and species. For each forest plot, the reference data of the forest parameters were obtained by conducting field surveys and TLS measurements almost simultaneously with the photogrammetric acquisitions. The TLS data were also used to estimate the accuracy of the photogrammetric ground height, which is a necessary product to derive DBHs and tree heights. For each plot, we automatically derived tree counts, tree positions, DBHs, and part of the stem curve from both TLS and SfM using a software developed at TUWien (Forest Analysis and Inventory Tool, FAIT), and the results were compared. The images were oriented with errors of a few millimetres only, according to checkpoint residuals. The automatic tree detection rate for the SfM reconstruction ranges between 65% and 98%, where the missing trees have average DBHs of less than 12 cm. For each plot, the mean error of SfM and TLS DBH estimates is -1.13 cm and -0.77 cm with respect to the caliper measurements. The resulting stem curves show that the mean differences between SfM and TLS stem diameters is at maximum -2.45 cm up to 3 m above ground, which increases to almost +4 cm for higher elevations. This study shows that with the adopted image capture method, terrestrial SfM photogrammetry, is an accurate solution to support forest inventory for estimating the number of trees and their location, the DBHs and stem curve up to 3 m above ground.

AB - The measurements of tree attributes required for forest monitoring and management planning, e.g., National Forest Inventories, are derived by rather time-consuming field measurements on sample plots, using calipers and measurement tapes. Therefore, forest managers and researchers are looking for alternative methods. Currently, terrestrial laser scanning (TLS) is the remote sensing method that provides the most accurate point clouds at the plot-level to derive these attributes from. However, the demand for even more efficient and effective solutions triggers further developments to lower the acquisition time, costs, and the expertise needed to acquire and process 3D point clouds, while maintaining the quality of extracted tree parameters. In this context, photogrammetry is considered a potential solution. Despite a variety of studies, much uncertainty still exists about the quality of photogrammetry-based methods for deriving plot-level forest attributes in natural forests. Therefore, the overall goal of this study is to evaluate the competitiveness of terrestrial photogrammetry based on structure from motion (SfM) and dense image matching for deriving tree positions, diameters at breast height (DBHs), and stem curves of forest plots by means of a consumer grade camera. We define an image capture method and we assess the accuracy of the photogrammetric results on four forest plots located in Austria and Slovakia, two in each country, selected to cover a wide range of conditions such as terrain slope, undergrowth vegetation, and tree density, age, and species. For each forest plot, the reference data of the forest parameters were obtained by conducting field surveys and TLS measurements almost simultaneously with the photogrammetric acquisitions. The TLS data were also used to estimate the accuracy of the photogrammetric ground height, which is a necessary product to derive DBHs and tree heights. For each plot, we automatically derived tree counts, tree positions, DBHs, and part of the stem curve from both TLS and SfM using a software developed at TUWien (Forest Analysis and Inventory Tool, FAIT), and the results were compared. The images were oriented with errors of a few millimetres only, according to checkpoint residuals. The automatic tree detection rate for the SfM reconstruction ranges between 65% and 98%, where the missing trees have average DBHs of less than 12 cm. For each plot, the mean error of SfM and TLS DBH estimates is -1.13 cm and -0.77 cm with respect to the caliper measurements. The resulting stem curves show that the mean differences between SfM and TLS stem diameters is at maximum -2.45 cm up to 3 m above ground, which increases to almost +4 cm for higher elevations. This study shows that with the adopted image capture method, terrestrial SfM photogrammetry, is an accurate solution to support forest inventory for estimating the number of trees and their location, the DBHs and stem curve up to 3 m above ground.

KW - Diameter at breast height

KW - Plot-based forest inventory

KW - Structure from motion

KW - Terrestrial laser scanning

KW - Terrestrial photogrammetry

KW - plot-based forest inventory

KW - terrestrial photogrammetry

KW - HEIGHT

KW - ACCURACY

KW - terrestrial laser scanning

KW - DIAMETER

KW - structure from motion

KW - MODELS

KW - BIOMASS

KW - HAND-HELD CAMERA

KW - diameter at breast height

KW - LASER SCANNER

UR - http://www.scopus.com/inward/record.url?scp=85065047023&partnerID=8YFLogxK

U2 - 10.3390/rs11080950

DO - 10.3390/rs11080950

M3 - Article

VL - 11

JO - Remote Sensing

JF - Remote Sensing

SN - 2072-4292

IS - 8

M1 - 950

ER -

ID: 33693145