{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T13:57:04Z","timestamp":1777039024897,"version":"3.51.4"},"reference-count":31,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T00:00:00Z","timestamp":1733356800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Climate Solutions Exchange\u2019s BEAMS (Biocarbon Europe: Advancing Measurement Standards) project","award":["101039795"],"award-info":[{"award-number":["101039795"]}]},{"name":"Climate Solutions Exchange\u2019s BEAMS (Biocarbon Europe: Advancing Measurement Standards) project","award":["10004871"],"award-info":[{"award-number":["10004871"]}]},{"DOI":"10.13039\/501100000781","name":"European Union","doi-asserted-by":"publisher","award":["101039795"],"award-info":[{"award-number":["101039795"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000781","name":"European Union","doi-asserted-by":"publisher","award":["10004871"],"award-info":[{"award-number":["10004871"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006041","name":"Innovate UK","doi-asserted-by":"publisher","award":["101039795"],"award-info":[{"award-number":["101039795"]}],"id":[{"id":"10.13039\/501100006041","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006041","name":"Innovate UK","doi-asserted-by":"publisher","award":["10004871"],"award-info":[{"award-number":["10004871"]}],"id":[{"id":"10.13039\/501100006041","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Terrestrial laser scanning (TLS) provides highly detailed 3D information of forest environments but is limited to small spatial scales, as data collection is time consuming compared to other remote sensing techniques. Furthermore, TLS data collection is heavily dependent on wind conditions, as the movement of trees negatively impacts the acquired data. Hardware advancements resulting in faster data acquisition times have the potential to be valuable in upscaling efforts but might impact overall data quality. In this study, we investigated the impact of the pulse repetition rate (PRR), or pulse frequency, which is the number of laser pulses emitted per second by the scanner. Increasing the PRR reduces the scan time required for a single scan but decreases the power (amplitude) of the emitted laser pulses commensurately. This trade-off could potentially impact the quality of the acquired data. We used a RIEGL VZ400i laser scanner to test the impact of different PRR settings on the point cloud quality and derived tree structural metrics from individual tree point clouds (diameter, tree height, crown projected area) as well as quantitative structure models (total branch length, tree volume). We investigated this impact across five field plots of different forest complexity and canopy density for three different PRR settings (300, 600 and 1200 kHz). The scan time for a single scan was 180, 90 and 45 s for 300, 600 and 1200 kHz, respectively. Differences among the raw acquired scans from different PRR replicates were largely removed by several necessary data processing steps, notably the removal of uncertain points with a low reflectance attribute. We found strong agreement between the individual tree structural metrics derived from each of the PRR replicates, independent of the forest complexity. This was the case for both point cloud-based metrics and those derived from quantitative structural models (QSMs). The results demonstrate that the PRR in high-end TLS instruments can be increased for data collection with negligible impact on a selection of derived structural metrics that are commonly used in the context of aboveground biomass estimation.<\/jats:p>","DOI":"10.3390\/rs16234560","type":"journal-article","created":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T06:24:44Z","timestamp":1733379884000},"page":"4560","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Implications of Pulse Frequency in Terrestrial Laser Scanning on Forest Point Cloud Quality and Individual Tree Structural Metrics"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3138-1558","authenticated-orcid":false,"given":"Tom E.","family":"Verhelst","sequence":"first","affiliation":[{"name":"Q-ForestLab\u2014Laboratory of Quantitative Forest Ecosystem Science, Department of Environment, Ghent University, 9000 Ghent, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4562-2538","authenticated-orcid":false,"given":"Kim","family":"Calders","sequence":"additional","affiliation":[{"name":"Q-ForestLab\u2014Laboratory of Quantitative Forest Ecosystem Science, Department of Environment, Ghent University, 9000 Ghent, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrew","family":"Burt","sequence":"additional","affiliation":[{"name":"Sylvera Ltd., London EC1V 8BT, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5492-2874","authenticated-orcid":false,"given":"Miro","family":"Demol","sequence":"additional","affiliation":[{"name":"Sylvera Ltd., London EC1V 8BT, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8136-8899","authenticated-orcid":false,"given":"Barbara","family":"D\u2019hont","sequence":"additional","affiliation":[{"name":"Q-ForestLab\u2014Laboratory of Quantitative Forest Ecosystem Science, Department of Environment, Ghent University, 9000 Ghent, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7061-4305","authenticated-orcid":false,"given":"Joanne","family":"Nightingale","sequence":"additional","affiliation":[{"name":"Climate and Earth Observation Group, National Physical Laboratory, Hampton Road, Teddington TW11 0LW, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8405-2788","authenticated-orcid":false,"given":"Louise","family":"Terryn","sequence":"additional","affiliation":[{"name":"Q-ForestLab\u2014Laboratory of Quantitative Forest Ecosystem Science, Department of Environment, Ghent University, 9000 Ghent, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1490-0168","authenticated-orcid":false,"given":"Hans","family":"Verbeeck","sequence":"additional","affiliation":[{"name":"Q-ForestLab\u2014Laboratory of Quantitative Forest Ecosystem Science, Department of Environment, Ghent University, 9000 Ghent, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1007\/s10712-019-09510-6","article-title":"The role and need for space-based forest biomass-related measurements in environmental management and policy","volume":"40","author":"Herold","year":"2019","journal-title":"Surv. Geophys."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"937","DOI":"10.1007\/s10712-019-09527-x","article-title":"Innovations in Ground and Airborne Technologies as Reference and for Training and Validation: Terrestrial Laser Scanning (TLS)","volume":"40","author":"Disney","year":"2019","journal-title":"Surv. Geophys."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"e12197","DOI":"10.1002\/2688-8319.12197","article-title":"Laser scanning reveals potential underestimation of biomass carbon in temperate forest","volume":"3","author":"Calders","year":"2022","journal-title":"Ecol. Solut. Evid."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"112102","DOI":"10.1016\/j.rse.2020.112102","article-title":"Terrestrial laser scanning in forest ecology: Expanding the horizon","volume":"251","author":"Calders","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1111\/2041-210X.12301","article-title":"Nondestructive estimates of above-ground biomass using terrestrial laser scanning","volume":"6","author":"Calders","year":"2015","journal-title":"Methods Ecol. Evol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.14214\/sf.10550","article-title":"Volumetric overestimation of small branches in 3D reconstructions of Fraxinus excelsior","volume":"56","author":"Demol","year":"2022","journal-title":"Silva Fenn."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1111\/2041-210X.12904","article-title":"Estimation of above-ground biomass of large tropical trees with terrestrial LiDAR","volume":"9","author":"Lau","year":"2018","journal-title":"Methods Ecol. Evol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1111\/2041-210X.12933","article-title":"Using terrestrial laser scanning data to estimate large tropical trees biomass and calibrate allometric models: A comparison with traditional destructive approach","volume":"9","author":"Ploton","year":"2018","journal-title":"Methods Ecol. Evol."},{"key":"ref_9","unstructured":"Duncanson, L., Armston, J., Disney, M., Avitabile, V., Barbier, N., Calders, K., Carter, S., Chave, J., Herold, M., and MacBean, N. (2024, December 02). Aboveground Woody Biomass Product Validation Good Practices Protocol, Version 1.0, Available online: https:\/\/lpvs.gsfc.nasa.gov\/PDF\/CEOS_WGCV_LPV_Biomass_Protocol_2021_V1.0.pdf."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.rse.2017.04.030","article-title":"Data acquisition considerations for Terrestrial Laser Scanning of forest plots","volume":"196","author":"Wilkes","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_11","unstructured":"RIEGL Laser Measurement Systems GmbH (2024, December 02). 3D Terrestrial Laser Scanning System RIEGL VZ-i Series. Data Sheet, RIEGL VZ-400i, 2024\/09\/02. Available online: http:\/\/www.riegl.com\/uploads\/tx_pxpriegldownloads\/RIEGL_VZ-400i_Datasheet_2024-09-02.pdf."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.agrformet.2014.03.022","article-title":"Implications of sensor configuration and topography on vertical plant profiles derived from terrestrial LiDAR","volume":"194","author":"Calders","year":"2014","journal-title":"Agric. For. Meteorol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2716","DOI":"10.1109\/TGRS.2017.2652721","article-title":"Evaluation of the Range Accuracy and the Radiometric Calibration of Multiple Terrestrial Laser Scanning Instruments for Data Interoperability","volume":"55","author":"Calders","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","unstructured":"Team, R.C. (2013). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. Available online: http:\/\/www.R-project.org\/."},{"key":"ref_15","unstructured":"Dowle, M., and Srinivasan, A. (2024, December 02). data.table: Extension of \u2018data.frame\u2019; 2023. Available online: https:\/\/rdrr.io\/cran\/data.table\/."},{"key":"ref_16","unstructured":"CloudCompare (2024, December 02). CloudCompare. Available online: https:\/\/www.cloudcompare.org\/."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1111\/2041-210X.13121","article-title":"Extracting individual trees from lidar point clouds using treeseg","volume":"10","author":"Burt","year":"2019","journal-title":"Methods Ecol. Evol."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Calders, K., Origo, N., Burt, A., Disney, M., Nightingale, J., Raumonen, P., \u00c5kerblom, M., Malhi, Y., and Lewis, P. (2018). Realistic Forest Stand Reconstruction from Terrestrial LiDAR for Radiative Transfer Modelling. Remote Sens., 10.","DOI":"10.3390\/rs10060933"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Lowe, T., and Pinskier, J. (2023). Tree Reconstruction Using Topology Optimisation. Remote Sens., 15.","DOI":"10.3390\/rs15010172"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3083","DOI":"10.1111\/2041-210X.14233","article-title":"TLS2trees: A scalable tree segmentation pipeline for TLS data","volume":"14","author":"Wilkes","year":"2023","journal-title":"Methods Ecol. Evol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"112061","DOI":"10.1016\/j.rse.2020.112061","article-title":"lidR: An R package for analysis of Airborne Laser Scanning (ALS) data","volume":"251","author":"Roussel","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_22","unstructured":"Roussel, J.R., and Auty, D. (2024, December 02). Airborne LiDAR Data Manipulation and Visualization for Forestry Applications, R Package Version 3.1.2. Available online: https:\/\/github.com\/r-lidar\/lidR."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1111\/2041-210X.14026","article-title":"Analysing individual 3D tree structure using the R package ITSMe","volume":"14","author":"Terryn","year":"2023","journal-title":"Methods Ecol. Evol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"255","DOI":"10.2307\/2532051","article-title":"A Concordance Correlation Coefficient to Evaluate Reproducibility","volume":"45","author":"Lin","year":"1989","journal-title":"Biometrics"},{"key":"ref_25","unstructured":"Signorell, A. (2024, December 02). DescTools: Tools for Descriptive Statistics. Available online: https:\/\/cran.r-project.org\/web\/packages\/DescTools\/index.html."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"201458","DOI":"10.1098\/rsos.201458","article-title":"New insights into large tropical tree mass and structure from direct harvest and terrestrial lidar","volume":"8","author":"Burt","year":"2021","journal-title":"R. Soc. Open Sci."},{"key":"ref_27","first-page":"1","article-title":"Graph-Based Leaf\u2013Wood Separation Method for Individual Trees Using Terrestrial Lidar Point Clouds","volume":"60","author":"Tian","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"491","DOI":"10.3390\/rs5020491","article-title":"Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data","volume":"5","author":"Raumonen","year":"2013","journal-title":"Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"8153","DOI":"10.1109\/TGRS.2020.3037763","article-title":"Impact of Beam Diameter and Scanning Approach on Point Cloud Quality of Terrestrial Laser Scanning in Forests","volume":"59","author":"Abegg","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"109564","DOI":"10.1016\/j.agrformet.2023.109564","article-title":"Quantifying stand-level clumping of boreal, hemiboreal and temperate European forest stands using terrestrial laser scanning","volume":"339","author":"Schraik","year":"2023","journal-title":"Agric. For. Meteorol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"e2021JD036175","DOI":"10.1029\/2021JD036175","article-title":"Implications of 3D Forest Stand Reconstruction Methods for Radiative Transfer Modeling: A Case Study in the Temperate Deciduous Forest","volume":"127","author":"Liu","year":"2022","journal-title":"J. Geophys. Res. Atmos."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/23\/4560\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:47:29Z","timestamp":1760114849000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/23\/4560"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,5]]},"references-count":31,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["rs16234560"],"URL":"https:\/\/doi.org\/10.3390\/rs16234560","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,5]]}}}