Data

Great Western Woodlands Terrestrial LiDAR, 2021

Terrestrial Ecosystem Research Network
Terrestrial Ecosystem Research Network ; CSIRO Environment ; University of Queensland ; Levick, Shaun ; Devereux, Timothy ; Johnson, Stephanie ; Woodgate, William
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25901/rdpv-bm71&rft.title=Great Western Woodlands Terrestrial LiDAR, 2021&rft.identifier=10.25901/rdpv-bm71&rft.publisher=Terrestrial Ecosystem Research Network&rft.description=This terrestrial LiDAR dataset captures detailed vegetation structural information at the Great Western Woodlands SuperSite on Credo Station, Western Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.The 1-hectare plot underwent sampling utilizing a 20 m grid configuration employing a Riegl VZ-2000i Terrestrial Laser Scanner (TLS) operating at 600 kHz. This dataset comprises 36 scans captured within the 1-hectare grid. Raw processing of the TLS data and co-registration of scans was conducted in Riegl’s RiSCAN PRO software suite. The internal inclination and orientation sensors of the Riegl VZ-2000i enabled scans to be placed in geographic coordinates with rough alignment. Riegl’s Multi-Station Adjustment tool (MSA) was used to refine the alignment until an overall RMSE of 0.02 m was attained. The dataset is available as a compressed RiSCAN PRO project and single scans as LAZ 1.4. Single scans are given in the scanner coordinate system. Transformations matrices for each position are made available for both global (WGS 84 / UTM zone 51S) and local coordinate systems.Progress Code: completedMaintenance and Update Frequency: notPlanned&rft.creator=Terrestrial Ecosystem Research Network &rft.creator=CSIRO Environment &rft.creator=University of Queensland &rft.creator=Levick, Shaun &rft.creator=Devereux, Timothy &rft.creator=Johnson, Stephanie &rft.creator=Woodgate, William &rft.date=2024&rft.edition=1.0&rft.coverage=Great Western Woodlands SuperSite on Credo Station, Western Australia.&rft.coverage=northlimit=-30.191006436; southlimit=-30.191989322; westlimit=120.655090964; eastLimit=120.656294895; projection=EPSG:4326&rft_rights=Creative Commons Attribution 4.0 International Licence http://creativecommons.org/licenses/by/4.0&rft_rights=TERN services are provided on an as-is and as available basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure. <br />Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN. <br /><br />Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting&rft_rights=Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.&rft_subject=environment&rft_subject=FOREST COMPOSITION/VEGETATION STRUCTURE&rft_subject=EARTH SCIENCE&rft_subject=BIOSPHERE&rft_subject=VEGETATION&rft_subject=Landscape Ecology&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=ECOLOGICAL APPLICATIONS&rft_subject=Great Western Woodlands&rft_subject=Riegl VZ-2000i laser scanner&rft_subject=vegetation structure (Unitless)&rft_subject=Unitless&rft_subject=lidar point cloud (Meter)&rft_subject=Meter&rft_subject=Point Resolution&rft_subject=one off&rft_subject=TLS&rft_subject=LiDAR&rft.type=dataset&rft.language=English Access the data
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Creative Commons Attribution 4.0 International Licence
http://creativecommons.org/licenses/by/4.0

TERN services are provided on an "as-is" and "as available" basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure.
Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN.

Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting

Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.

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Building 1019, 80 Meiers Rd
QLD 4068
Australia
Ph: +61 7 3365 9097

esupport@tern.org.au

Brief description

This terrestrial LiDAR dataset captures detailed vegetation structural information at the Great Western Woodlands SuperSite on Credo Station, Western Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.

Lineage

The 1-hectare plot underwent sampling utilizing a 20 m grid configuration employing a Riegl VZ-2000i Terrestrial Laser Scanner (TLS) operating at 600 kHz. This dataset comprises 36 scans captured within the 1-hectare grid. Raw processing of the TLS data and co-registration of scans was conducted in Riegl’s RiSCAN PRO software suite. The internal inclination and orientation sensors of the Riegl VZ-2000i enabled scans to be placed in geographic coordinates with rough alignment. Riegl’s Multi-Station Adjustment tool (MSA) was used to refine the alignment until an overall RMSE of 0.02 m was attained. The dataset is available as a compressed RiSCAN PRO project and single scans as LAZ 1.4. Single scans are given in the scanner coordinate system. Transformations matrices for each position are made available for both global (WGS 84 / UTM zone 51S) and local coordinate systems.

Progress Code: completed
Maintenance and Update Frequency: notPlanned

Notes

Credit
We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.

This work was jointly funded by the Terrestrial Ecosystem Research Network (TERN), an Australian Government National Collaborative Research Infrastructure Strategy (NCRIS) project, CSIRO and the University of Queensland. This work was also supported by an Australian Research Council DECRA Fellowship (DE190101182).
The Great Western Woodlands SuperSite is managed by CSIRO Land and Water.
Purpose
Terrestrial LiDAR measurements can be used to assess vegetation structure, create 3D reconstructions, and perform terrain surface analysis.

Created: 2021-09-07

Issued: 2024-07-04

Modified: 2024-07-04

Data time period: 2021-09-07 to 2021-09-07

This dataset is part of a larger collection

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120.65629,-30.19101 120.65629,-30.19199 120.65509,-30.19199 120.65509,-30.19101 120.65629,-30.19101

120.6556929295,-30.191497879

text: Great Western Woodlands SuperSite on Credo Station, Western Australia.

Subjects
BIOSPHERE | EARTH SCIENCE | Ecological Applications | Environmental Sciences | FOREST COMPOSITION/VEGETATION STRUCTURE | Great Western Woodlands | Landscape Ecology | LiDAR | Meter | Point Resolution | Riegl VZ-2000i laser scanner | TLS | Unitless | VEGETATION | environment | lidar point cloud (Meter) | one off | vegetation structure (Unitless) |

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Point-of-truth metadata URL

uri : https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/0d1225be-ceab-44d6-98f6-aa08523cfa02

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