No Cover Image

Journal article 127 views 18 downloads

Structure from Motion Photogrammetry in Forestry: a Review / Jakob Iglhaut; Carlos Cabo; Stefano Puliti; Livia Piermattei; James O’Connor; Jacqueline Rosette

Current Forestry Reports, Volume: 5, Issue: 3, Pages: 155 - 168

Swansea University Authors: Jakob, Iglhaut, Jacqueline, Rosette

  • 51276.pdf

    PDF | Version of Record

    Released under the terms of a Creative Commons Attribution 4.0 International License (CC-BY).

    Download (2.77MB)

Abstract

AbstractPurpose of ReviewThe adoption of Structure from Motion photogrammetry (SfM) is transforming the acquisition of three-dimensional (3D) remote sensing (RS) data in forestry. SfM photogrammetry enables surveys with little cost and technical expertise. We present the theoretical principles and p...

Full description

Published in: Current Forestry Reports
ISSN: 2198-6436
Published: 2019
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa51276
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2019-07-31T16:34:04Z
last_indexed 2019-08-09T16:31:51Z
id cronfa51276
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2019-08-07T15:07:01.4170617</datestamp><bib-version>v2</bib-version><id>51276</id><entry>2019-07-31</entry><title>Structure from Motion Photogrammetry in Forestry: a Review</title><swanseaauthors><author><sid>79de14ee696e248dfb744d5b82e38535</sid><firstname>Jakob</firstname><surname>Iglhaut</surname><name>Jakob Iglhaut</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>0307f116e8f87a83cf4080c493fb7590</sid><ORCID>0000-0002-2589-0244</ORCID><firstname>Jacqueline</firstname><surname>Rosette</surname><name>Jacqueline Rosette</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2019-07-31</date><deptcode>SGE</deptcode><abstract>AbstractPurpose of ReviewThe adoption of Structure from Motion photogrammetry (SfM) is transforming the acquisition of three-dimensional (3D) remote sensing (RS) data in forestry. SfM photogrammetry enables surveys with little cost and technical expertise. We present the theoretical principles and practical considerations of this technology and show opportunities that SfM photogrammetry offers for forest practitioners and researchers.Recent FindingsOur examples of key research indicate the successful application of SfM photogrammetry in forestry, in an operational context and in research, delivering results that are comparable to LiDAR surveys. Reviewed studies have identified possibilities for the extraction of biophysical forest parameters from airborne and terrestrial SfM point clouds and derived 2D data in area-based approaches (ABA) and individual tree approaches. Additionally, increases in the spatial and spectral resolution of sensors available for SfM photogrammetry enable forest health assessment and monitoring. The presented research reveals that coherent 3D data and spectral information, as provided by the SfM workflow, promote opportunities to derive both structural and physiological attributes at the individual tree crown (ITC) as well as stand levels.SummaryWe highlight the potential of using unmanned aerial vehicles (UAVs) and consumer-grade cameras for terrestrial SfM-based surveys in forestry. Offering several spatial products from a single sensor, the SfM workflow enables foresters to collect their own fit-for-purpose RS data. With the broad availability of non-expert SfM software, we provide important practical considerations for the collection of quality input image data to enable successful photogrammetric surveys.</abstract><type>Journal Article</type><journal>Current Forestry Reports</journal><volume>5</volume><journalNumber>3</journalNumber><paginationStart>155</paginationStart><paginationEnd>168</paginationEnd><publisher/><issnElectronic>2198-6436</issnElectronic><keywords>SfM Point cloud UAV Close-range photogrammetry (CRP) Forest inventory Forest health</keywords><publishedDay>16</publishedDay><publishedMonth>7</publishedMonth><publishedYear>2019</publishedYear><publishedDate>2019-07-16</publishedDate><doi>10.1007/s40725-019-00094-3</doi><url>https://link.springer.com/article/10.1007/s40725-019-00094-3?wt_mc=alerts.TOCjournals&amp;amp;utm_source=toc&amp;amp;utm_medium=email&amp;amp;utm_campaign=toc_40725_5_3</url><notes/><college>COLLEGE NANME</college><department>Geography</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>SGE</DepartmentCode><institution>Swansea University</institution><lastEdited>2019-08-07T15:07:01.4170617</lastEdited><Created>2019-07-31T10:04:47.8230000</Created><authors><author><firstname>Jakob</firstname><surname>Iglhaut</surname><order>1</order></author><author><firstname>Carlos</firstname><surname>Cabo</surname><order>2</order></author><author><firstname>Stefano</firstname><surname>Puliti</surname><order>3</order></author><author><firstname>Livia</firstname><surname>Piermattei</surname><order>4</order></author><author><firstname>James</firstname><surname>O&#x2019;Connor</surname><order>5</order></author><author><firstname>Jacqueline</firstname><surname>Rosette</surname><orcid>0000-0002-2589-0244</orcid><order>6</order></author></authors><documents><document><filename>0051276-31072019100626.pdf</filename><originalFilename>51276.pdf</originalFilename><uploaded>2019-07-31T10:06:26.4930000</uploaded><type>Output</type><contentLength>3011358</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><action/><embargoDate>2019-07-30T00:00:00.0000000</embargoDate><documentNotes>Released under the terms of a Creative Commons Attribution 4.0 International License (CC-BY).</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language></document></documents><OutputDurs/></rfc1807>
spelling 2019-08-07T15:07:01.4170617 v2 51276 2019-07-31 Structure from Motion Photogrammetry in Forestry: a Review 79de14ee696e248dfb744d5b82e38535 Jakob Iglhaut Jakob Iglhaut true false 0307f116e8f87a83cf4080c493fb7590 0000-0002-2589-0244 Jacqueline Rosette Jacqueline Rosette true false 2019-07-31 SGE AbstractPurpose of ReviewThe adoption of Structure from Motion photogrammetry (SfM) is transforming the acquisition of three-dimensional (3D) remote sensing (RS) data in forestry. SfM photogrammetry enables surveys with little cost and technical expertise. We present the theoretical principles and practical considerations of this technology and show opportunities that SfM photogrammetry offers for forest practitioners and researchers.Recent FindingsOur examples of key research indicate the successful application of SfM photogrammetry in forestry, in an operational context and in research, delivering results that are comparable to LiDAR surveys. Reviewed studies have identified possibilities for the extraction of biophysical forest parameters from airborne and terrestrial SfM point clouds and derived 2D data in area-based approaches (ABA) and individual tree approaches. Additionally, increases in the spatial and spectral resolution of sensors available for SfM photogrammetry enable forest health assessment and monitoring. The presented research reveals that coherent 3D data and spectral information, as provided by the SfM workflow, promote opportunities to derive both structural and physiological attributes at the individual tree crown (ITC) as well as stand levels.SummaryWe highlight the potential of using unmanned aerial vehicles (UAVs) and consumer-grade cameras for terrestrial SfM-based surveys in forestry. Offering several spatial products from a single sensor, the SfM workflow enables foresters to collect their own fit-for-purpose RS data. With the broad availability of non-expert SfM software, we provide important practical considerations for the collection of quality input image data to enable successful photogrammetric surveys. Journal Article Current Forestry Reports 5 3 155 168 2198-6436 SfM Point cloud UAV Close-range photogrammetry (CRP) Forest inventory Forest health 16 7 2019 2019-07-16 10.1007/s40725-019-00094-3 https://link.springer.com/article/10.1007/s40725-019-00094-3?wt_mc=alerts.TOCjournals&amp;utm_source=toc&amp;utm_medium=email&amp;utm_campaign=toc_40725_5_3 COLLEGE NANME Geography COLLEGE CODE SGE Swansea University 2019-08-07T15:07:01.4170617 2019-07-31T10:04:47.8230000 Jakob Iglhaut 1 Carlos Cabo 2 Stefano Puliti 3 Livia Piermattei 4 James O’Connor 5 Jacqueline Rosette 0000-0002-2589-0244 6 0051276-31072019100626.pdf 51276.pdf 2019-07-31T10:06:26.4930000 Output 3011358 application/pdf Version of Record true 2019-07-30T00:00:00.0000000 Released under the terms of a Creative Commons Attribution 4.0 International License (CC-BY). true eng
title Structure from Motion Photogrammetry in Forestry: a Review
spellingShingle Structure from Motion Photogrammetry in Forestry: a Review
Jakob, Iglhaut
Jacqueline, Rosette
title_short Structure from Motion Photogrammetry in Forestry: a Review
title_full Structure from Motion Photogrammetry in Forestry: a Review
title_fullStr Structure from Motion Photogrammetry in Forestry: a Review
title_full_unstemmed Structure from Motion Photogrammetry in Forestry: a Review
title_sort Structure from Motion Photogrammetry in Forestry: a Review
author_id_str_mv 79de14ee696e248dfb744d5b82e38535
0307f116e8f87a83cf4080c493fb7590
author_id_fullname_str_mv 79de14ee696e248dfb744d5b82e38535_***_Jakob, Iglhaut
0307f116e8f87a83cf4080c493fb7590_***_Jacqueline, Rosette
author Jakob, Iglhaut
Jacqueline, Rosette
author2 Jakob Iglhaut
Carlos Cabo
Stefano Puliti
Livia Piermattei
James O’Connor
Jacqueline Rosette
format Journal article
container_title Current Forestry Reports
container_volume 5
container_issue 3
container_start_page 155
publishDate 2019
institution Swansea University
issn 2198-6436
doi_str_mv 10.1007/s40725-019-00094-3
url https://link.springer.com/article/10.1007/s40725-019-00094-3?wt_mc=alerts.TOCjournals&amp;utm_source=toc&amp;utm_medium=email&amp;utm_campaign=toc_40725_5_3
document_store_str 1
active_str 0
description AbstractPurpose of ReviewThe adoption of Structure from Motion photogrammetry (SfM) is transforming the acquisition of three-dimensional (3D) remote sensing (RS) data in forestry. SfM photogrammetry enables surveys with little cost and technical expertise. We present the theoretical principles and practical considerations of this technology and show opportunities that SfM photogrammetry offers for forest practitioners and researchers.Recent FindingsOur examples of key research indicate the successful application of SfM photogrammetry in forestry, in an operational context and in research, delivering results that are comparable to LiDAR surveys. Reviewed studies have identified possibilities for the extraction of biophysical forest parameters from airborne and terrestrial SfM point clouds and derived 2D data in area-based approaches (ABA) and individual tree approaches. Additionally, increases in the spatial and spectral resolution of sensors available for SfM photogrammetry enable forest health assessment and monitoring. The presented research reveals that coherent 3D data and spectral information, as provided by the SfM workflow, promote opportunities to derive both structural and physiological attributes at the individual tree crown (ITC) as well as stand levels.SummaryWe highlight the potential of using unmanned aerial vehicles (UAVs) and consumer-grade cameras for terrestrial SfM-based surveys in forestry. Offering several spatial products from a single sensor, the SfM workflow enables foresters to collect their own fit-for-purpose RS data. With the broad availability of non-expert SfM software, we provide important practical considerations for the collection of quality input image data to enable successful photogrammetric surveys.
published_date 2019-07-16T04:11:57Z
_version_ 1678139685769052160
score 10.751122