<div class="csl-bib-body">
<div class="csl-entry">Eysn, L., Hollaus, M., Schadauer, K., & Pfeifer, N. (2012). Forest delineation based on airborne LIDAR data. <i>Remote Sensing</i>. https://doi.org/10.3390/rs4030762</div>
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The delineation of forested areas is a critical task, because the resulting maps are a fundamental input for a broad field of applications and users. Different national and international forest definitions are available for manual or automatic delineation, but unfortunately most definitions lack precise geometrical descriptions for the different criteria. A mandatory criterion in forest definitions is the criterion of crown coverage (CC), which defines the proportion of the forest floor covered by the vertical projection of the tree crowns. For loosely stocked areas, this criterion is especially critical, because the size and shape of the reference area for calculating CC is not clearly defined in most definitions. Thus current forest delineations differ and tend to be non-comparable because of different settings for checking the criterion of CC in the delineation process. This paper evaluates a new approach for the automatic delineation of forested areas, based on airborne laser scanning (ALS) data with a clearly defined method for calculating CC. The new approach, the ‘tree triples’ method, is based on defining CC as a relation between the sum of the crown areas of three neighboring trees and the area of their convex hull. The approach is applied and analyzed for two study areas in Tyrol, Austria. The selected areas show a loosely stocked forest at the upper timberline and a fragmented forest on the hillside. The fully automatic method presented for delineating forested areas from ALS data shows promising results with an overall accuracy of 96%, and provides a beneficial tool for operational applications.
en
dc.description.sponsorship
The European Territorial Cooperation Alpine Space
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dc.description.sponsorship
The Klima- und Energiefonds in the framework of the program NEUE ENERGIEN 2020
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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
Remote Sensing
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
forest definition
en
dc.subject
canopy cover
en
dc.subject
crown coverage
en
dc.subject
vegetation mapping
en
dc.subject
airborne laser scanning
en
dc.subject
forest classification
en
dc.subject
land cover
en
dc.subject
canopy height model
en
dc.title
Forest delineation based on airborne LIDAR data
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
Federal Research and Training Centre for Forests, Natural Hazards and Landscape (BFW), Austria
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dc.relation.grantno
NEWFOR
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dc.relation.grantno
LASER-WOOD 822030
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dc.rights.holder
The Author(s) 2012
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dc.type.category
Original Research Article
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tuw.journal.peerreviewed
true
-
tuw.peerreviewed
true
-
tuw.version
vor
-
dcterms.isPartOf.title
Remote Sensing
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tuw.publication.orgunit
E120 - Department für Geodäsie und Geoinformation
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tuw.publisher.doi
10.3390/rs4030762
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dc.identifier.eissn
2072-4292
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dc.identifier.libraryid
AC11360731
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dc.identifier.urn
urn:nbn:at:at-ubtuw:3-2509
-
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
-
item.languageiso639-1
en
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item.cerifentitytype
Publications
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item.cerifentitytype
Publications
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http://purl.org/coar/resource_type/c_18cf
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item.openairecristype
http://purl.org/coar/resource_type/c_18cf
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item.fulltext
with Fulltext
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item.openaccessfulltext
Open Access
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item.grantfulltext
open
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item.openairetype
Article
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item.openairetype
Artikel
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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
Federal Research and Training Centre for Forests, Natural Hazards and Landscape (BFW), Austria