<div class="csl-bib-body">
<div class="csl-entry">Hollaus, M., Schimpl, L., Posch, L., & Kirchmeir, H. (2023, September 7). <i>Deadwood detection – in-situ versus UAV-LiDAR based approaches</i> [Conference Presentation]. SilviLaser 2023, London, United Kingdom of Great Britain and Northern Ireland (the). http://hdl.handle.net/20.500.12708/188708</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/188708
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dc.description.abstract
Deadwood is an important component of the forest ecosystem and represents a central input for carbon storage studies. In addition to information on the presence of deadwood, the volume or biomass as well as the degree of decay are of interest. Usually, deadwood is surveyed in the context of forest inventories at plot level, whereby the lying as well as the standing deadwood is recorded by means of diameter at breast height, and tree height and stem length respectively. Another method is the line-intersect sampling (LIS), where all lying trunks intersecting with a line are recorded. Finally, statistical methods can be used to estimate the total amount of deadwood in a defined area.
Due to the rapid developments in the field of UAV-LiDAR, it is now possible to acquire 3D point clouds with a very high point density even for larger survey areas at favourable prices. This makes it possible to determine the deadwood for large areas.
The lying deadwood is detected and its volume is estimated from UAV-LiDAR and image data (RIEGL-VUX-120, PhaseOne-iXM100) data with a point density of >4000 pts/m² for the Rohrach natural forest reserve with an area of 48 ha. From the aerial images a true-orthopoto is calculated with a pixel size of 5 cm. Voxel-based approaches are used which take into account not only the geometrical properties but also the radiometric properties of the backscattering objects. The results are compared with reference surveys of 48 plots (437 trees) and with LIS (174 trees).
The results show a very high completeness of the detected deadwood. The validation with the plot-based deadwood volumes shows high accuracies. The total deadwood volume for the entire area show some deviations which have to be analysed in more detail in the next months. This study is funded via the Austrian Waldfonds.
en
dc.language.iso
en
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dc.subject
laserscanning
en
dc.subject
drones
en
dc.subject
deadwood detection
en
dc.title
Deadwood detection – in-situ versus UAV-LiDAR based approaches
en
dc.type
Presentation
en
dc.type
Vortrag
de
dc.contributor.affiliation
TU Wien, Austria
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dc.contributor.affiliation
E.C.O. Institut für Ökologie GmbH (Austria), Austria
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dc.contributor.affiliation
E.C.O. Institut für Ökologie GmbH (Austria), Austria
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dc.type.category
Conference Presentation
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tuw.researchTopic.id
E4
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tuw.researchTopic.name
Environmental Monitoring and Climate Adaptation
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E120-07 - Forschungsbereich Photogrammetrie
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tuw.author.orcid
0000-0003-1000-370X
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tuw.event.name
SilviLaser 2023
en
tuw.event.startdate
06-09-2023
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tuw.event.enddate
08-09-2023
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
London
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tuw.event.country
GB
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tuw.event.institution
UCL University College London
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tuw.event.presenter
Hollaus, Markus
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wb.sciencebranch
Geodäsie, Vermessungswesen
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wb.sciencebranch
Informatik
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wb.sciencebranch
Physische Geographie
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wb.sciencebranch.oefos
2074
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
1054
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wb.sciencebranch.value
70
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wb.sciencebranch.value
15
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wb.sciencebranch.value
15
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item.grantfulltext
none
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item.cerifentitytype
Publications
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item.fulltext
no Fulltext
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item.openairecristype
http://purl.org/coar/resource_type/c_18cp
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item.openairetype
conference paper not in proceedings
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item.languageiso639-1
en
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crisitem.author.dept
E120-07 - Forschungsbereich Photogrammetrie
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crisitem.author.dept
E120-07 - Forschungsbereich Photogrammetrie
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crisitem.author.dept
E.C.O. Institut für Ökologie GmbH (Austria), Austria
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crisitem.author.dept
E.C.O. Institut für Ökologie GmbH (Austria), Austria
