No Cover Image

Journal article 63 views 1 download

3DFin: a software for automated 3D forest inventories from terrestrial point clouds

Diego Laino Rebollido, Carlos Cabo Gomez, Covadonga Prendes, Romain Janvier, Celestino Ordonez, Tadas Nikonovas, Stefan Doerr Orcid Logo, Cristina Santin Nuno

Forestry: An International Journal of Forest Research, Issue: cpae020

Swansea University Authors: Diego Laino Rebollido, Carlos Cabo Gomez, Tadas Nikonovas, Stefan Doerr Orcid Logo, Cristina Santin Nuno

  • 66704.VoR.pdf

    PDF | Version of Record

    © The Author(s) 2024. This is an Open Access article distributed under the terms of the Creative Commons Attribution License.

    Download (4.77MB)

Check full text

DOI (Published version): 10.1093/forestry/cpae020

Abstract

Accurate and efficient forest inventories are essential for effective forest management and conservation. The advent of ground-based remote sensing has revolutionized the data acquisition process, enabling detailed and precise 3D measurements of forested areas. Several algorithms and methods have be...

Full description

Published in: Forestry: An International Journal of Forest Research
ISSN: 0015-752X 1464-3626
Published: Oxford University Press (OUP) 2024
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa66704
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2024-06-11T15:38:05Z
last_indexed 2024-06-11T15:38:05Z
id cronfa66704
recordtype SURis
fullrecord <?xml version="1.0" encoding="utf-8"?><rfc1807 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"><bib-version>v2</bib-version><id>66704</id><entry>2024-06-11</entry><title>3DFin: a software for automated 3D forest inventories from terrestrial point clouds</title><swanseaauthors><author><sid>4f9aa56b174c9abf66b578389fcee260</sid><firstname>Diego</firstname><surname>Laino Rebollido</surname><name>Diego Laino Rebollido</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>660108e8078886c3e750d803be23276b</sid><firstname>Carlos</firstname><surname>Cabo Gomez</surname><name>Carlos Cabo Gomez</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>940b37dbdcb6896884af0887808b089c</sid><firstname>Tadas</firstname><surname>Nikonovas</surname><name>Tadas Nikonovas</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>575eb5094f2328249328b3e43deb5088</sid><ORCID>0000-0002-8700-9002</ORCID><firstname>Stefan</firstname><surname>Doerr</surname><name>Stefan Doerr</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>993c82cbaf875c1268156360e83c4dfd</sid><firstname>Cristina</firstname><surname>Santin Nuno</surname><name>Cristina Santin Nuno</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2024-06-11</date><deptcode>BGPS</deptcode><abstract>Accurate and efficient forest inventories are essential for effective forest management and conservation. The advent of ground-based remote sensing has revolutionized the data acquisition process, enabling detailed and precise 3D measurements of forested areas. Several algorithms and methods have been developed in the last years to automatically derive tree metrics from such terrestrial/ground-based point clouds. However, few attempts have been made to make these automatic tree metrics algorithms accessible to wider audiences by producing software solutions that implement these methods. To fill this major gap, we have developed 3DFin, a novel free software program designed for user-friendly, automatic forest inventories using ground-based point clouds. 3DFin empowers users to automatically compute key forest inventory parameters, including tree Total Height, Diameter at Breast Height (DBH), and tree location. To enhance its user-friendliness, the program is open-access, cross-platform, and available as a plugin in CloudCompare and QGIS as well as a standalone in Windows. 3DFin capabilities have been tested with Terrestrial Laser Scanning, Mobile Laser Scanning, and terrestrial photogrammetric point clouds from public repositories across different forest conditions, achieving nearly full completeness and correctness in tree mapping and highly accurate DBH estimations (root mean squared error &lt;2 cm, bias &lt;1 cm) in most scenarios. In these tests, 3DFin demonstrated remarkable efficiency, with processing times ranging from 2 to 7 min per plot. The software is freely available at: https://github.com/3DFin/3DFin.</abstract><type>Journal Article</type><journal>Forestry: An International Journal of Forest Research</journal><volume>0</volume><journalNumber>cpae020</journalNumber><paginationStart/><paginationEnd/><publisher>Oxford University Press (OUP)</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0015-752X</issnPrint><issnElectronic>1464-3626</issnElectronic><keywords/><publishedDay>23</publishedDay><publishedMonth>5</publishedMonth><publishedYear>2024</publishedYear><publishedDate>2024-05-23</publishedDate><doi>10.1093/forestry/cpae020</doi><url/><notes/><college>COLLEGE NANME</college><department>Biosciences Geography and Physics School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>BGPS</DepartmentCode><institution>Swansea University</institution><apcterm>SU Library paid the OA fee (TA Institutional Deal)</apcterm><funders>NERC (NE/T001194/1). This work was supported by the UK NERC project [NE/T001194/1]: ‘Advancing 3D Fuel Mapping for Wildfire Behaviour and Risk Mitigation Modelling’, the Spanish Knowledge Generation project [PID2021-126790NB-I00]: ‘Advancing carbon emission estimations from wildfires applying artificial intelligence to 3D terrestrial point clouds’, and the Spanish ‘Ramón y Cajal’ programme [RYC2018-025797-I]</funders><projectreference/><lastEdited>2024-07-04T12:06:31.9282585</lastEdited><Created>2024-06-11T16:34:20.9341663</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Biosciences, Geography and Physics - Geography</level></path><authors><author><firstname>Diego</firstname><surname>Laino Rebollido</surname><order>1</order></author><author><firstname>Carlos</firstname><surname>Cabo Gomez</surname><order>2</order></author><author><firstname>Covadonga</firstname><surname>Prendes</surname><order>3</order></author><author><firstname>Romain</firstname><surname>Janvier</surname><order>4</order></author><author><firstname>Celestino</firstname><surname>Ordonez</surname><order>5</order></author><author><firstname>Tadas</firstname><surname>Nikonovas</surname><order>6</order></author><author><firstname>Stefan</firstname><surname>Doerr</surname><orcid>0000-0002-8700-9002</orcid><order>7</order></author><author><firstname>Cristina</firstname><surname>Santin Nuno</surname><order>8</order></author></authors><documents><document><filename>66704__30818__c68e53b8196f488b8adffbdc972dd702.pdf</filename><originalFilename>66704.VoR.pdf</originalFilename><uploaded>2024-07-04T12:04:05.1189709</uploaded><type>Output</type><contentLength>5002800</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>© The Author(s) 2024. This is an Open Access article distributed under the terms of the Creative Commons Attribution License.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs><OutputDur><Id>255</Id><IsDataAvailableOnline>true</IsDataAvailableOnline><DataNotAvailableOnlineReasonId xsi:nil="true"/><DurUrl>https://doi.org/10.48436/afdjq-ce434</DurUrl><IsDurRestrictions xsi:nil="true"/><DurRestrictionReasonId xsi:nil="true"/><DurEmbargoDate xsi:nil="true"/></OutputDur></OutputDurs></rfc1807>
spelling v2 66704 2024-06-11 3DFin: a software for automated 3D forest inventories from terrestrial point clouds 4f9aa56b174c9abf66b578389fcee260 Diego Laino Rebollido Diego Laino Rebollido true false 660108e8078886c3e750d803be23276b Carlos Cabo Gomez Carlos Cabo Gomez true false 940b37dbdcb6896884af0887808b089c Tadas Nikonovas Tadas Nikonovas true false 575eb5094f2328249328b3e43deb5088 0000-0002-8700-9002 Stefan Doerr Stefan Doerr true false 993c82cbaf875c1268156360e83c4dfd Cristina Santin Nuno Cristina Santin Nuno true false 2024-06-11 BGPS Accurate and efficient forest inventories are essential for effective forest management and conservation. The advent of ground-based remote sensing has revolutionized the data acquisition process, enabling detailed and precise 3D measurements of forested areas. Several algorithms and methods have been developed in the last years to automatically derive tree metrics from such terrestrial/ground-based point clouds. However, few attempts have been made to make these automatic tree metrics algorithms accessible to wider audiences by producing software solutions that implement these methods. To fill this major gap, we have developed 3DFin, a novel free software program designed for user-friendly, automatic forest inventories using ground-based point clouds. 3DFin empowers users to automatically compute key forest inventory parameters, including tree Total Height, Diameter at Breast Height (DBH), and tree location. To enhance its user-friendliness, the program is open-access, cross-platform, and available as a plugin in CloudCompare and QGIS as well as a standalone in Windows. 3DFin capabilities have been tested with Terrestrial Laser Scanning, Mobile Laser Scanning, and terrestrial photogrammetric point clouds from public repositories across different forest conditions, achieving nearly full completeness and correctness in tree mapping and highly accurate DBH estimations (root mean squared error <2 cm, bias <1 cm) in most scenarios. In these tests, 3DFin demonstrated remarkable efficiency, with processing times ranging from 2 to 7 min per plot. The software is freely available at: https://github.com/3DFin/3DFin. Journal Article Forestry: An International Journal of Forest Research 0 cpae020 Oxford University Press (OUP) 0015-752X 1464-3626 23 5 2024 2024-05-23 10.1093/forestry/cpae020 COLLEGE NANME Biosciences Geography and Physics School COLLEGE CODE BGPS Swansea University SU Library paid the OA fee (TA Institutional Deal) NERC (NE/T001194/1). This work was supported by the UK NERC project [NE/T001194/1]: ‘Advancing 3D Fuel Mapping for Wildfire Behaviour and Risk Mitigation Modelling’, the Spanish Knowledge Generation project [PID2021-126790NB-I00]: ‘Advancing carbon emission estimations from wildfires applying artificial intelligence to 3D terrestrial point clouds’, and the Spanish ‘Ramón y Cajal’ programme [RYC2018-025797-I] 2024-07-04T12:06:31.9282585 2024-06-11T16:34:20.9341663 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Geography Diego Laino Rebollido 1 Carlos Cabo Gomez 2 Covadonga Prendes 3 Romain Janvier 4 Celestino Ordonez 5 Tadas Nikonovas 6 Stefan Doerr 0000-0002-8700-9002 7 Cristina Santin Nuno 8 66704__30818__c68e53b8196f488b8adffbdc972dd702.pdf 66704.VoR.pdf 2024-07-04T12:04:05.1189709 Output 5002800 application/pdf Version of Record true © The Author(s) 2024. This is an Open Access article distributed under the terms of the Creative Commons Attribution License. true eng https://creativecommons.org/licenses/by/4.0/ 255 true https://doi.org/10.48436/afdjq-ce434
title 3DFin: a software for automated 3D forest inventories from terrestrial point clouds
spellingShingle 3DFin: a software for automated 3D forest inventories from terrestrial point clouds
Diego Laino Rebollido
Carlos Cabo Gomez
Tadas Nikonovas
Stefan Doerr
Cristina Santin Nuno
title_short 3DFin: a software for automated 3D forest inventories from terrestrial point clouds
title_full 3DFin: a software for automated 3D forest inventories from terrestrial point clouds
title_fullStr 3DFin: a software for automated 3D forest inventories from terrestrial point clouds
title_full_unstemmed 3DFin: a software for automated 3D forest inventories from terrestrial point clouds
title_sort 3DFin: a software for automated 3D forest inventories from terrestrial point clouds
author_id_str_mv 4f9aa56b174c9abf66b578389fcee260
660108e8078886c3e750d803be23276b
940b37dbdcb6896884af0887808b089c
575eb5094f2328249328b3e43deb5088
993c82cbaf875c1268156360e83c4dfd
author_id_fullname_str_mv 4f9aa56b174c9abf66b578389fcee260_***_Diego Laino Rebollido
660108e8078886c3e750d803be23276b_***_Carlos Cabo Gomez
940b37dbdcb6896884af0887808b089c_***_Tadas Nikonovas
575eb5094f2328249328b3e43deb5088_***_Stefan Doerr
993c82cbaf875c1268156360e83c4dfd_***_Cristina Santin Nuno
author Diego Laino Rebollido
Carlos Cabo Gomez
Tadas Nikonovas
Stefan Doerr
Cristina Santin Nuno
author2 Diego Laino Rebollido
Carlos Cabo Gomez
Covadonga Prendes
Romain Janvier
Celestino Ordonez
Tadas Nikonovas
Stefan Doerr
Cristina Santin Nuno
format Journal article
container_title Forestry: An International Journal of Forest Research
container_volume 0
container_issue cpae020
publishDate 2024
institution Swansea University
issn 0015-752X
1464-3626
doi_str_mv 10.1093/forestry/cpae020
publisher Oxford University Press (OUP)
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Geography{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Geography
document_store_str 1
active_str 0
description Accurate and efficient forest inventories are essential for effective forest management and conservation. The advent of ground-based remote sensing has revolutionized the data acquisition process, enabling detailed and precise 3D measurements of forested areas. Several algorithms and methods have been developed in the last years to automatically derive tree metrics from such terrestrial/ground-based point clouds. However, few attempts have been made to make these automatic tree metrics algorithms accessible to wider audiences by producing software solutions that implement these methods. To fill this major gap, we have developed 3DFin, a novel free software program designed for user-friendly, automatic forest inventories using ground-based point clouds. 3DFin empowers users to automatically compute key forest inventory parameters, including tree Total Height, Diameter at Breast Height (DBH), and tree location. To enhance its user-friendliness, the program is open-access, cross-platform, and available as a plugin in CloudCompare and QGIS as well as a standalone in Windows. 3DFin capabilities have been tested with Terrestrial Laser Scanning, Mobile Laser Scanning, and terrestrial photogrammetric point clouds from public repositories across different forest conditions, achieving nearly full completeness and correctness in tree mapping and highly accurate DBH estimations (root mean squared error <2 cm, bias <1 cm) in most scenarios. In these tests, 3DFin demonstrated remarkable efficiency, with processing times ranging from 2 to 7 min per plot. The software is freely available at: https://github.com/3DFin/3DFin.
published_date 2024-05-23T12:06:31Z
_version_ 1803646340898488320
score 10.608602

Similar Items