SIMULATING VARIOUS TERRESTRIAL and UAV LIDAR SCANNING CONFIGURATIONS for UNDERSTORY FOREST STRUCTURE MODELLING

M. Hämmerle, N. Lukač, K. C. Chen, Z. S. Koma, Chi-Kuei Wang, K. Anders, B. Höfle

Research output: Contribution to journalConference article

3 Citations (Scopus)

Abstract

Information about the 3D structure of understory vegetation is of high relevance in forestry research and management (e.g., for complete biomass estimations). However, it has been hardly investigated systematically with state-of-the-art methods such as static terrestrial laser scanning (TLS) or laser scanning from unmanned aerial vehicle platforms (ULS). A prominent challenge for scanning forests is posed by occlusion, calling for proper TLS scan position or ULS flight line configurations in order to achieve an accurate representation of understory vegetation. The aim of our study is to examine the effect of TLS or ULS scanning strategies on (1) the height of individual understory trees and (2) understory canopy height raster models. We simulate full-waveform TLS and ULS point clouds of a virtual forest plot captured from various combinations of max. 12 TLS scan positions or 3 ULS flight lines. The accuracy of the respective datasets is evaluated with reference values given by the virtually scanned 3D triangle mesh tree models. TLS tree height underestimations range up to 1.84 m (15.30 % of tree height) for single TLS scan positions, but combining three scan positions reduces the underestimation to maximum 0.31 m (2.41 %). Combining ULS flight lines also results in improved tree height representation, with a maximum underestimation of 0.24 m (2.15 %). The presented simulation approach offers a complementary source of information for efficient planning of field campaigns aiming at understory vegetation modelling.

Original languageEnglish
Pages (from-to)59-65
Number of pages7
JournalISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Volume4
Issue number2W4
DOIs
Publication statusPublished - 2017 Sep 12
EventISPRS Geospatial Week 2017 - Wuhan, China
Duration: 2017 Sep 182017 Sep 22

Fingerprint

Optical radar
Unmanned aerial vehicles (UAV)
optical radar
lidar
understory
laser
Scanning
scanning
configurations
Lasers
modeling
lasers
vegetation
flight
raster
pilotless aircraft
canopies
occlusion
Forestry
biomass

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences (miscellaneous)
  • Environmental Science (miscellaneous)
  • Instrumentation

Cite this

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title = "SIMULATING VARIOUS TERRESTRIAL and UAV LIDAR SCANNING CONFIGURATIONS for UNDERSTORY FOREST STRUCTURE MODELLING",
abstract = "Information about the 3D structure of understory vegetation is of high relevance in forestry research and management (e.g., for complete biomass estimations). However, it has been hardly investigated systematically with state-of-the-art methods such as static terrestrial laser scanning (TLS) or laser scanning from unmanned aerial vehicle platforms (ULS). A prominent challenge for scanning forests is posed by occlusion, calling for proper TLS scan position or ULS flight line configurations in order to achieve an accurate representation of understory vegetation. The aim of our study is to examine the effect of TLS or ULS scanning strategies on (1) the height of individual understory trees and (2) understory canopy height raster models. We simulate full-waveform TLS and ULS point clouds of a virtual forest plot captured from various combinations of max. 12 TLS scan positions or 3 ULS flight lines. The accuracy of the respective datasets is evaluated with reference values given by the virtually scanned 3D triangle mesh tree models. TLS tree height underestimations range up to 1.84 m (15.30 {\%} of tree height) for single TLS scan positions, but combining three scan positions reduces the underestimation to maximum 0.31 m (2.41 {\%}). Combining ULS flight lines also results in improved tree height representation, with a maximum underestimation of 0.24 m (2.15 {\%}). The presented simulation approach offers a complementary source of information for efficient planning of field campaigns aiming at understory vegetation modelling.",
author = "M. H{\"a}mmerle and N. Lukač and Chen, {K. C.} and Koma, {Z. S.} and Chi-Kuei Wang and K. Anders and B. H{\"o}fle",
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SIMULATING VARIOUS TERRESTRIAL and UAV LIDAR SCANNING CONFIGURATIONS for UNDERSTORY FOREST STRUCTURE MODELLING. / Hämmerle, M.; Lukač, N.; Chen, K. C.; Koma, Z. S.; Wang, Chi-Kuei; Anders, K.; Höfle, B.

In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 4, No. 2W4, 12.09.2017, p. 59-65.

Research output: Contribution to journalConference article

TY - JOUR

T1 - SIMULATING VARIOUS TERRESTRIAL and UAV LIDAR SCANNING CONFIGURATIONS for UNDERSTORY FOREST STRUCTURE MODELLING

AU - Hämmerle, M.

AU - Lukač, N.

AU - Chen, K. C.

AU - Koma, Z. S.

AU - Wang, Chi-Kuei

AU - Anders, K.

AU - Höfle, B.

PY - 2017/9/12

Y1 - 2017/9/12

N2 - Information about the 3D structure of understory vegetation is of high relevance in forestry research and management (e.g., for complete biomass estimations). However, it has been hardly investigated systematically with state-of-the-art methods such as static terrestrial laser scanning (TLS) or laser scanning from unmanned aerial vehicle platforms (ULS). A prominent challenge for scanning forests is posed by occlusion, calling for proper TLS scan position or ULS flight line configurations in order to achieve an accurate representation of understory vegetation. The aim of our study is to examine the effect of TLS or ULS scanning strategies on (1) the height of individual understory trees and (2) understory canopy height raster models. We simulate full-waveform TLS and ULS point clouds of a virtual forest plot captured from various combinations of max. 12 TLS scan positions or 3 ULS flight lines. The accuracy of the respective datasets is evaluated with reference values given by the virtually scanned 3D triangle mesh tree models. TLS tree height underestimations range up to 1.84 m (15.30 % of tree height) for single TLS scan positions, but combining three scan positions reduces the underestimation to maximum 0.31 m (2.41 %). Combining ULS flight lines also results in improved tree height representation, with a maximum underestimation of 0.24 m (2.15 %). The presented simulation approach offers a complementary source of information for efficient planning of field campaigns aiming at understory vegetation modelling.

AB - Information about the 3D structure of understory vegetation is of high relevance in forestry research and management (e.g., for complete biomass estimations). However, it has been hardly investigated systematically with state-of-the-art methods such as static terrestrial laser scanning (TLS) or laser scanning from unmanned aerial vehicle platforms (ULS). A prominent challenge for scanning forests is posed by occlusion, calling for proper TLS scan position or ULS flight line configurations in order to achieve an accurate representation of understory vegetation. The aim of our study is to examine the effect of TLS or ULS scanning strategies on (1) the height of individual understory trees and (2) understory canopy height raster models. We simulate full-waveform TLS and ULS point clouds of a virtual forest plot captured from various combinations of max. 12 TLS scan positions or 3 ULS flight lines. The accuracy of the respective datasets is evaluated with reference values given by the virtually scanned 3D triangle mesh tree models. TLS tree height underestimations range up to 1.84 m (15.30 % of tree height) for single TLS scan positions, but combining three scan positions reduces the underestimation to maximum 0.31 m (2.41 %). Combining ULS flight lines also results in improved tree height representation, with a maximum underestimation of 0.24 m (2.15 %). The presented simulation approach offers a complementary source of information for efficient planning of field campaigns aiming at understory vegetation modelling.

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U2 - 10.5194/isprs-annals-IV-2-W4-59-2017

DO - 10.5194/isprs-annals-IV-2-W4-59-2017

M3 - Conference article

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SP - 59

EP - 65

JO - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

JF - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

SN - 2194-9042

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