Field
Value
Language
dc.contributor.author
Xi, Zhouxin
datacite.creator.affiliationIdentifier
https://ror.org/044j76961;https://ror.org/0430zw506
en_US
datacite.creator.affiliation
University of Lethbridge;Canadian Forest Service
en_US
datacite.creator.nameIdentifier
https://orcid.org/0000-0002-0458-6323
en_US
dc.contributor.author
Hopkinson, Chris
datacite.creator.affiliationIdentifier
datacite.creator.affiliation
University of Lethbridge
datacite.creator.nameIdentifier
https://orcid.org/0000-0002-3998-4778
dc.contributor.author
Chasmer, Laura
datacite.creator.affiliationIdentifier
datacite.creator.affiliation
University of Lethbridge
datacite.creator.nameIdentifier
https://orcid.org/0000-0002-8062-1530
dc.coverage.temporal
2021-07-18/2021-07-24
dc.date.accessioned
2023-09-29T12:51:40Z
dc.date.available
2023-09-29T12:51:40Z
dc.date.issued
2023-09-29
dc.identifier.uri
https://www.frdr-dfdr.ca/repo/dataset/54c17384-8680-4bba-ae98-08777754b53f
dc.identifier.uri
https://doi.org/10.20383/103.0814
dc.description
The 3D detail of forest plots under mountain pine beetle (MPB) attack can be characterized with the high-resolution terrestrial laser scanning (TLS) dataset that represents heterogeneous fuel components and individual-tree conditions. The dataset is generated by multiple processing steps of scan collection, point cloud georeferencing, noise cleaning, tree extraction, individual-tree isolation, plot component delineation, individual-tree wood reconstruction, and MPB phase classification.
The entire methodology is described in Xi. et al (2023).
The dataset is suitable for diverse research purposes, e.g. point cloud processing, classifier and segmenter training and testing, inventory attribute extraction, and branch-level tree attribute analysis.
en_US
dc.publisher
Federated Research Data Repository / dépôt fédéré de données de recherche
dc.rights
Creative Commons Attribution 4.0 International (CC BY 4.0)
en_US
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
en_US
dc.subject
terrestrial laser scanning
en_US
dc.subject
lidar
en_US
dc.subject
forest fuel
en_US
dc.subject
mountain pine beetle
en_US
dc.subject
quantitative structrual modeling
en_US
dc.subject
3D deep learning classification
en_US
dc.title
Delineation and reconstruction of 3D components and volumes from mountain pine beetle-infected forest plots using terrestrial laser scanning (TLS)
en_US
globus.shared_endpoint.name
f163c1b3-9c88-42f6-a7bb-5839ed6c4063
globus.shared_endpoint.path
/1/published/publication_809/
datacite.publicationyear
2023
datacite.contributor.DataCollector
Zhouxin Xi
datacite.contributor.DataCollector
Chris Hopkinson
datacite.contributor.DataCollector
Laura Chasmer
datacite.contributor.DataManager
Chris Hopkinson
datacite.date.Collected
2021-07-18/2021-07-24
datacite.resourcetype
Dataset
en_US
datacite.geolocation.geolocationPoint
52.7467 117.9762
datacite.geolocation.geolocationBox
52.66875 117.8883 52.86956 118.2533
datacite.geolocation.geolocationPlace
Jasper National Park;Jasper;Alberta;Canada
datacite.fundingReference.funderIdentifier
en_US
datacite.fundingReference.funderName
Mitacs Accelerate
en_US
datacite.fundingReference.awardNumber
IT27605
en_US
datacite.fundingReference.awardTitle
en_US
datacite.fundingReference.funderIdentifier
en_US
datacite.fundingReference.funderName
Foothills Research Institute (fRI)— Federal-Provincial MPB Research Partnership
en_US
datacite.fundingReference.awardNumber
247.15
en_US
datacite.fundingReference.awardTitle
NSERC Canada Wildfire
en_US
datacite.fundingReference.funderIdentifier
en_US
datacite.fundingReference.funderName
SPG-N—NETGP 548629-19
en_US
datacite.fundingReference.awardNumber
en_US
datacite.fundingReference.awardTitle
en_US
datacite.fundingReference.funderIdentifier
https://ror.org/000az4664
en_US
datacite.fundingReference.funderName
Canada Foundation for Innovation
en_US
datacite.fundingReference.awardNumber
32436
en_US
datacite.fundingReference.awardTitle
en_US
datacite.fundingReference.funderIdentifier
https://ror.org/002sgqx17
en_US
datacite.fundingReference.funderName
Western Economic Diversification Canada
en_US
datacite.fundingReference.awardNumber
000015316
en_US
datacite.fundingReference.awardTitle
en_US
frdr.crdc.code
RDF4010414
en_US
frdr.crdc.group_en
Agriculture, forestry, and fisheries
en_US
frdr.crdc.class_en
Forestry sciences
en_US
frdr.crdc.field_en
Quantitative methods in forestry
en_US
frdr.crdc.group_fr
Agriculture, foresterie et pêches
fr_CA
frdr.crdc.class_fr
Sciences de la foresterie
fr_CA
frdr.crdc.field_fr
Méthodes quantitatives en foresterie
fr_CA
datacite.description.other
Item exited embargo and became publicly available on 2023-09-29
