<div class="csl-bib-body">
<div class="csl-entry">Eysn, L., Hollaus, M., Lindberg, E., Berger, F., Monnet, J.-M., Dalponte, M., Kobal, M., Pellegrini, M., Lingua, E., Mongus, D., & Pfeifer, N. (2015). A Benchmark of Lidar-Based Single Tree Detection Methods Using Heterogeneous Forest Data from the Alpine Space. <i>Forests</i>. https://doi.org/10.3390/f6051721</div>
</div>
In this study, eight airborne laser scanning (ALS)-based single tree detection methods are benchmarked and investigated. The methods were applied to a unique dataset originating from different regions of the Alpine Space covering different study areas, forest types, and structures. This is the first benchmark ever performed for different forests within the Alps. The evaluation of the detection results was carried out in a reproducible way by automatically matching them to precise in situ forest inventory data using a restricted nearest neighbor detection approach. Quantitative statistical parameters such as percentages of correctly matched trees and omission and commission errors are presented. The proposed automated matching procedure presented herein shows an overall accuracy of 97%. Method based analysis, investigations per forest type, and an overall benchmark performance are presented. The best matching rate was obtained for single-layered coniferous forests. Dominated trees were challenging for all methods. The overall performance shows a matching rate of 47%, which is comparable to results of other benchmarks performed in the past. The study provides new insight regarding the potential and limits of tree detection with ALS and underlines some key aspects regarding the choice of method when performing single tree detection for the various forest types encountered in alpine regions.
en
dc.description.sponsorship
The European Commission
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dc.language
English
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dc.language.iso
en
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dc.publisher
MDPI
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dc.relation.ispartof
Forests
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
single tree extraction
en
dc.subject
airborne laser scanning
en
dc.subject
forest inventory
en
dc.subject
comparative testing
en
dc.subject
co-registration
en
dc.subject
mountain forests
en
dc.subject
Alpine Space
en
dc.subject
matching
en
dc.title
A Benchmark of Lidar-Based Single Tree Detection Methods Using Heterogeneous Forest Data from the Alpine Space
en
dc.type
Article
en
dc.type
Artikel
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dc.contributor.affiliation
SLU: Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden
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dc.contributor.affiliation
Irstea, UR EMGR Écosystèmes Montagnards, centre de Grenoble, Saint-Martin-d’Hères, France
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dc.contributor.affiliation
Irstea, UR EMGR Écosystèmes Montagnards, centre de Grenoble, Saint-Martin-d’Hères, France
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dc.contributor.affiliation
FEM: Department of Sustainable Agro-Ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele all’Adige, Italy
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dc.contributor.affiliation
SFI: Department of Forestry and Renewable Forest Resources, Biotechnical Faculty, University of Ljubljana
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dc.contributor.affiliation
TESAF: Department of Land, Environment, Agriculture and Forestry, University of Padova, Legnaro, Italy
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dc.contributor.affiliation
TESAF: Department of Land, Environment, Agriculture and Forestry, University of Padova, Legnaro, Italy
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dc.contributor.affiliation
UM-FERI: Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia
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dc.relation.grantno
Alpine Space 2-3-2-FR NEWFOR
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dc.rights.holder
The Author(s) 2015
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dc.type.category
Original Research Article
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tuw.journal.peerreviewed
true
-
tuw.peerreviewed
true
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tuw.version
vor
-
wb.publication.intCoWork
International Co-publication
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dcterms.isPartOf.title
Forests
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tuw.publication.orgunit
E120 - Department für Geodäsie und Geoinformation
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tuw.publisher.doi
10.3390/f6051721
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dc.date.onlinefirst
2015-05-15
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dc.identifier.eissn
1999-4907
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dc.identifier.libraryid
AC11360268
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dc.identifier.urn
urn:nbn:at:at-ubtuw:3-2109
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tuw.author.orcid
0000-0001-6063-7239
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tuw.author.orcid
0000-0001-9515-7657
-
tuw.author.orcid
0000-0002-2160-0529
-
tuw.author.orcid
0000-0002-2348-7929
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dc.rights.identifier
CC BY 4.0
de
dc.rights.identifier
CC BY 4.0
en
wb.sci
true
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item.fulltext
with Fulltext
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item.cerifentitytype
Publications
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item.openairecristype
http://purl.org/coar/resource_type/c_2df8fbb1
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item.languageiso639-1
en
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item.openaccessfulltext
Open Access
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item.openairetype
research article
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item.grantfulltext
open
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crisitem.author.dept
E120 - Department für Geodäsie und Geoinformation
-
crisitem.author.dept
E120-07 - Forschungsbereich Photogrammetrie
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crisitem.author.dept
SLU: Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden
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crisitem.author.dept
FEM: Department of Sustainable Agro-Ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, San Michele all’Adige, Italy
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crisitem.author.dept
TESAF: Department of Land, Environment, Agriculture and Forestry, University of Padova, Legnaro, Italy
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crisitem.author.dept
UM-FERI: Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia