Find research datasets worth reusing

opencc-by-4.0Jan 2021View details →

Terrestrial laser scanning - RIEGL VZ-1000, individual tree point clouds and cylinder models, Belgian hedgerows and tree rows

Terrestrial laser scans were acquired for 69 trees (Quercus robur: 39 trees; Alnus glutinosa: 19 trees; Betula pendula: 11 trees) in hedgerows and tree rows in agricultural lands in Flanders, Belgium. We used a RIEGL VZ-1000 terrestrial laser scanner (RIEGL Laser Measurement Systems GmbH, Austria) with a beam divergence of 0.35 mrad operating in the infrared (wavelength 1550 nm) with a range up to 1000 m. We scanned leaf-off and all recorded variables are valid for overbark measurements. Individual trees were manually extracted from the co-registered point cloud in RiSCAN PRO software (provided by RIEGL). To the extracted trees, quantitative structure models (QSM) were fitted. We used the QSMs to derive branch length (m), total wood volume (m³) and merchantable wood volume (m³, using only cylinders with diameter > 7 cm). From the point clouds, we extracted the tree structural features such as crown projection (m²), maximum crown diameter (m) and tree height (m). Biomass expansion factors (BEF) were calculated by dividing total tree volume to merchantable tree volume. We expressed the age dependency of the BEF values via non-linear regression models. See Van Den Berge et al. (2021) for further information (DOI: 10.1007/s12155-021-10250-y).

opencc-by-4.0Oct 2023View details →

High-resolution, Decadal to Weekly Geomorphic Change Analysis of the Elbow River in Calgary, using Multi-temporal Lidar and Repeat Terrestrial Laser Scanning

This directory contains files related to the scientific research project of Luc van Dijk at the Department of Earth, Energy, and Environment, University of Calgary. The project title is "High-resolution, Decadal to Weekly Geomorphic Change Analysis of the Elbow River in Calgary, using Multi-temporal Lidar and Repeat Terrestrial Laser Scanning". This project in the field of geomorphology was a collaboration between the University of Calgary and Utrecht University in the Netherlands. The project was completed on October 27, 2023. Below is a description of the files in this directory. DisplacementVolumeDistributions_TLS.xlsxExcel file containing tabular data of the normalized sediment displacement volumes that were obtained using TLS. Each tab in the Excel file represents a period of interest in 2023. The data in this file were used to generate the 'histogram-like' figures in the report. DoD_rasters.zipFolder containing the aerial lidar DEMs of Difference (DoDs) for each period of interest. The DoDs are 'waterless', i.e. the water surface is masked. The suffix of the file name before the file extension (e.g., ..._10cm.tif) indicates the maximum REM value that was used for the automated masking of the water surface extent (see report section 3.1.2). If the file name contains "large", it refers to the upstream greater area (see report section 3.1.3).Within this folder is another folder called 'Clipped2AOIs'. This folder contains the same DoDs, but covering only the extents of the sites of interest ('AOIs' = Areas Of Interest). FilteredPointClouds_TLS.zipFolder containing the processed and filtered point clouds that were acquired throughout the summer of 2023 using TLS. These point clouds have been pre-processed and filtered to remove vegetation (see report section 3.2). They are grouped in sub-folders per acquisition date. The filenames are numbered to location, i.e. 'elbow1', 'elbow2', 'elbow3' and 'elbow4'. These correspond to the sites of interest: Glenmore Dam, golf club, Sandy Beach and Riverdale, respectively. PythonScripts_Discharge_Rainfall.zipFolder containing the Python scripts that were made to process the discharge and rainfall data that were sourced from Environment Canada and The City of Calgary (see report section 3.3). The scripts themselves contain descriptions of their purpose. PythonScripts_DisplacementVolumeAnalysis.zipFolder containing the Python scripts that were made to process and analyze the aerial lidar DoDs and the TLS rasterized difference point clouds (M3C2 output). The 'convert2pickle' scripts converted the sizable rasters to smaller pickle files, which were easier and faster to work with. The 'chart' scripts load the data from the pickle files, analyze them and produce the 'histogram-like' figures in the report. The scripts themselves contain descriptions of their purpose. RainfallDischargeData.xlsxExcel file containing the discharge and rainfall data from Environment Canada and The City of Calgary. The data came from different sources in different formats and were combined into this single table. RasterizedDifferencedPointClouds_M3C2.zipFolder containing the rasterized results of the differenced TLS point clouds (M3C2 output) (see report section 3.2.4). The filenames are numbered to location, i.e. 'Elbow1', 'Elbow2', 'Elbow3' and 'Elbow4'. These correspond to the sites of interest: Glenmore Dam, golf club, Sandy Beach and Riverdale, respectively. The numeric sequence in the file name indicates the start and end date of the change analysis in a 'mm-dd' format. The suffixes '_dist', '_unc' and '_sig' refer to the three output layers of the M3C2 algorithm: distance, uncertainty and significance of change. The main files of interest are the '.tif' files. Files sharing the same name, but with different extensions (.tfw, .tif.aux.xml, .tif.xml) are supplementary/auxiliary files for the '.tif' file, generated by ArcGIS Pro. ScarpsOfInterest_shapefile.zipFolder containing a polygon shapefile describing the extents and locations of the sites of interest. The main file of interest is the '.shp' file. The other files with the same name, but different extensions (.cpg, .dbf, .prj, .sbn, .sbx, .shp.xml, .shx) are supplementary/auxiliary files for the '.shp' file, generated by ArcGIS Pro.

opencc-by-4.0Nov 2024View details →

Mangrove terrestrial laser scanning (TLS) point clouds and quantitative structural models (QSMs)

Datasets for a publication entitled, "Terrestrial laser scanning for the estimation of above ground biomass of mangrove roots by modelling them as inverted trees." See the file "Data dictionary for Mangrove terrestrial laser scanning.pdf" for a description of the datasets included in the zipped folder.

opencc-by-4.0Dec 2021View details →

Point clouds from terrestrial laser scanning from crowns of individual Scots pine trees

Trees adapt to their growing conditions by regulating the sizes of their parts and their relationships. For example, removal or death of adjacent trees increases the growing space and the amount of light received by the remaining trees enabling their crowns to expand. Knowledge about the effects of silvicultural practices on crown size and shape as well as about the quality of branches affecting the shape of a crown is, however, still limited. Laser scanning (or Light detecting and ranging LiDAR) has provided new opportunities for characterizing trees in more detail in three-dimensional space. Especially terrestrial laser scanning (TLS) has increasingly been used in producing a variety of tree attributes. This data set includes 3D reconstruction of crowns of Scots pine (Pinus sylvestris L.) trees from sample plots with different thinning treatments. The thinning treatments include two intensities of thinning, three thinning types as well as control (i.e. no thinning treatment since the establishment). This data set can be used in developing point cloud processing algorithms for single tree crown characterization and for investigating variation in crown size and shape as well as the effects of various thinning treatments on crown size and shape of Scots pine trees grown in boreal forests.

opencc-by-4.0Jan 2024View details →

Terrestrial laser scan data of a experimental plot in Forstamt Billenhagen, 340 a31 (Mecklenburg-Vorpommern, Germany 2023) v2

The area was surveyed using terrestrial laser scanning, and the subsequent derivation of individual tree yield data (BHD, tree height, volume, etc.) was carried out as part of a study to assess the ecosystem services of different forest stands (recorded in March 2023). In this version of the data, transmission errors and unit errors were corrected.

Point clouds from terrestrial laser scanning of 97 trees in St Pancras Old Church, London

Point clouds of 97 trees scanned in the grounds of St Pancras Old Church, Camden, London Tree species is predominantly London Plane (Platanus × hispanica) but also includes the <a href="https://www.atlasobscura.com/places/the-hardy-tree-london-england">Hardy ash tree</a>. Data was captured on 18/7/2017 (leaf-on) with a RIEGL VZ-400 terrestrial laser scanner. 38 scans were conducted from 19 positions. The weather was good, with little to no noticeable wind. Data is a binary PLY format with xyz fields in an arbitrary coordinate system. Trees have been extracted from the global point cloud and have been "cleaned" to remove the ground and neighbouring trees (however there may be some errors). Data has been downsampled to a voxel size of 0.04 m. Raw data can be accessed from here. Please acknowledge the data set authors if using this data.

Point clouds from terrestrial laser scanning of 30 trees along Malet Street, London

Point clouds of 30 street trees scanned along <a href="https://goo.gl/maps/7x3dutn6vHcxVPdC6">Malet Street, London, UK</a>.  Tree species is predominantly London Plane (Platanus × hispanica). Data was captured on 8/2/2017 (leaf-off) with a RIEGL VZ-400 terrestrial laser scanner. 24 scans were conducted from 12 positions along the street. The weather was good, with little to no noticeable wind. Data is a binary PLY format with xyz fields in an arbitrary coordinate system. Trees have been extracted from the global point cloud and have been "cleaned" to remove the ground and neighbouring trees (however there may be some errors). Data has been downsampled to a voxel size of 0.04 m. Raw data can be accessed from here. Please acknowledge the data set authors if using this data.

Point clouds from terrestrial laser scanning of 74 trees in Russell Square, London

Point clouds of 74 trees scanned in <a href="https://www.google.co.uk/maps/place/Russell+Square/@51.5217533,-0.1280787,17z/data=!3m1!4b1!4m5!3m4!1s0x48761b310bb300bf:0xd1190a08b331324a!8m2!3d51.52175!4d-0.12589">Russell Square, London</a> Tree species is predominantly London Plane (Platanus × hispanica). Data was captured on 8/2/2017 (leaf-off) with a RIEGL VZ-400 terrestrial laser scanner. 22 scans were conducted from 11 positions. The weather was good, with little to no noticeable wind. Data is a binary PLY format with xyz fields in an arbitrary coordinate system. Trees have been extracted from the global point cloud and have been "cleaned" to remove the ground and neighbouring trees (however there may be some errors). Data has been downsampled to a voxel size of 0.04 m. Raw data can be downloaded from <a href="https://doi.org/10.5281/zenodo.5070681">10.5281/zenodo.5070681</a> Please acknowledge the data set authors if using this data.

opencc-by-4.0Nov 2022View details →

Terrestrial laser scanning data Wytham Woods: individual trees and quantitative structure models (QSMs)

This dataset was used for the analysis of the following publication: Laser scanning reveals potential underestimation of biomass carbon in temperate forest. Calders, K, Verbeeck, V, Burt, A, Origo, N, Nightingale, J, Malhi, Y, Wilkes, P, Raumonen, P, Bunce, R G H and Disney, M. Ecological Solutions and Evidence (accepted) Any use of this dataset should cite the paper above (Creative Commons Attribution 4.0 International Public License). Contact: kim.calders@ugent.be   ================================================                     Dataset ================================================ General:  TLS data were collected in leaf-off conditions during late November 2015 - January 2016. Windy days were avoided to ensure data quality. We used a RIEGL VZ-400 terrestrial laser scanner (RIEGL Laser Measurement Systems GmbH). The instrument has a beam divergence of 0.35 mrad and operates in the infrared (wavelength 1550 nm) with a range up to 350 m. The pulse repetition rate for each scan was 300 kHz, the minimum range was 0.5 m and the angular sampling resolution was 0.04°. This resulted in 22,500,000 outgoing pulses for a single scan, resulting in a beam diameter of 2.45 cm and beam spacing of 3.5 cm at 50 m (for example). The azimuth angle range was 0-360° and the zenith angle range was 30-130°. Therefore an additional scan was acquired at each scan location with the scanner tilted at 90° from the vertical to complete sampling of the full hemisphere at each location. Scans were done in a larger 6 ha area using an approximate 20 m × 20 m grid, to ensure the best possible data quality within our 1.4 ha study area. Trees which had at least more than half of their stem at tree diameter 1.3 m inside the boundaries of the study area were included [ Note that this dataset contains 876 individual trees, but after applying the boundary conditions, 835 trees within the study area were used in the analysis of the paper >> see TLS_Inventory.ipynb] Full details of the methods to segment individual trees and generate the QSMs can be found in the paper Calders et al. Ecological Solutions and Evidence. Tree ID: Tree IDs can have numbers only or numbers + letters. A number only means this was a base with one stem. A number + letter means individual trees (split below 1.3m), that share a common tree base. Datasets: 1) DATA_clouds_txt & DATA_clouds_ply: Individually segmented trees in *txt and *ply format. File naming is [tree_id].*txt or [tree_ply].*tx 2) DATA_QSM_opt: optimised QSMs using TreeQSM v2.0 (https://github.com/InverseTampere/TreeQSM). File naming is [tree_id]-[dmin0]-[rcov0]-[nmin0]-[dmin]-[rcov]-[nmin]-[lcyl]-[NoGround]-[iteration].mat  3) Raw scan data can be found here: http://dx.doi.org/10.5285/ed9156e1697343e4ad82e83ed550e345   ================================================                     Paper analysis ================================================ We have provided all scripts (analysis_and_figures) that were used to: 1 ) analyse the data (TLS_Inventory.ipynb): ----- Analysis of point clouds and QSMs using TLS_Inventory.py.ipynb > tls_summary.csv (#876 trees) ----- Link with census &1.4ha > trees_summary.csv (#835 trees) 2) generate the paper figures: ----- various *.R and *.ipynb scripts in the main folder and /allometriesTLS/   ================================================                     Funding ================================================ The TLS fieldwork was funded through the Metrology for Earth Observation and Climate project (MetEOC-2), grant number ENV55 within the European Metrology Research Programme (EMRP). The EMRP is jointly funded by the EMRP participating countries within EURAMET and the European Union. Funds for purchase of the UCL RIEGL VZ-400 instrument was provided by the UK NERC National Centre for Earth Observation (NCEO) and UCL Geography. The census of the forest plot was supported by an ERC Advanced Investigator Grant to Yadvinder Malhi (GEM-TRAIT, grant number 321131).

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Data from: Leveraging a new branch-based taper curve and form factor from terrestrial laser scanning proxies

Modeling branch taper curve and form factor contributes to increasing the efficiency of tree crown reconstruction: the branch taper, defined as the sequential measure of diameters along the course of the branch, is pivotal to accurately estimate key branch variables such as biomass and volume. Branch diameters or volumes have commonly been estimated from terrestrial laser scanning (TLS) based on automatized voxelization or cylinder-fitting approaches, given the whole branch length is sufficiently covered by laser reflections. The results are, however, often affected by ample variations in point cloud characteristics caused by varying point density, occlusions, and noise. As these characteristics of TLS have been difficult to be sufficiently controlled or eliminated in automatized-techniques, we proposed a new branch-based taper curve model and form factor (BFF), which can be employed directly from the laser reflections and under variable point cloud characteristics. In this paper, the approach is demonstrated on primary branches using a set of TLS-derived diameter datasets from a sample of 20 trees of 6 species. The result shows an improvement in the accuracy of the diameter estimates and, at best, enabled for predicting encompassing finer branch scales (<10 cm), with R2 of 0.86 and a mean relative absolute error of 1.03 cm (29%) when validated with field-measured diameters. This approach was also capable of retrieving branch diameters for a large percentage of explicitly identified primary branches (>85%) directly from the filtered points when validated with panoramic images acquired concurrently with laser scanning. Frequently used automatized crown reconstructions from the quantitative structural model (QSM), on the other hand, was largely obscured by discrepancies in the point clouds, with the crown-tops and finer branches being the most critical. Furthermore, our approach provides mean BFF of 0.35 and 0.49 with the diameters determined from 5% and 10% of the total branch length, respectively, which may have the potential to produce branch volume information with reasonable accuracy from only knowing the length and respective diameter. Although our model can be regarded as a first approximation to the taper curve and form factor for the primary branches on a relatively small set of samples, the approach can further our understanding of alternative ways to improve the accuracy of the assessment of branch diameter and volume. The approach may also be extended to other branch orders. This could expand the horizon for volumetric calculations and biomass estimates from non-destructive TLS proxies in tree crowns.

opencc-zeroJul 2023View details →

opencc-by-4.0Oct 2023View details →

Terrestrial laser scanning data of urban trees in Milton Keynes, UK: individual trees and Treegraph model outputs

TLS_point_clouds: - Data collection: Terrestrial laser scanning data acquired in leaf-off condition in April 2021. - Scanning instrument: We used a RIEGL VZ-400 with a wavelength of 1550 nm, 0.35 mrad beam divergence and 0.04˚ angular resolution. - Locations: The data were collected from three urban sites in Milton Keynes, UK: Avebury Blvd (Ave), Dansteed Way (Dan), and Overgate (Ove). - File information: Each file is an individual tree point cloud in Polygon File Format (.ply), which can be viewed in software such as CloudCompare.   Treegraph_outputs: - Description: Model outputs from Treegraph for individual trees. - File naming convention: [TreeID]-[downsample_voxel_length]-[tip_diameter_if_known].* <ul> <li>*.centres.ply: Skeleton nodes of individual trees.</li> <li>*.mesh.ply: Cylinder model of individual trees.</li> <li>*.json: Geometrical and topological attributes at varying scales, from internode and branch to the whole tree.</li> <li>*.txt: Summary of input parameters, logs of intermediate steps, and a statistical overview of whole-tree structural attributes.</li> </ul>

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Data from: Leveraging a new branch-based taper curve and form factor from terrestrial laser scanning proxies

Open the record for dataset details and reuse information.

publicDec 2023View details →

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Terrestrial laser scanning data of urban trees in Milton Keynes, UK: individual trees and Treegraph outputs

This dataset was used for the analysis of the following publication: Yang, W., Wilkes, P., Vicari, M.B., Hand, K., Calders, K. and Disney, M., 2024. Treegraph: tree architecture from terrestrial laser scanning point clouds. Remote Sensing in Ecology and Conservation. Any use of this dataset should cite the paper above (Creative Commons Attribution NonCommercial License).   ================================================                     Dataset ================================================ TLS_point_clouds: - Data collection: Terrestrial laser scanning data acquired in leaf-off condition in April 2021. - Scanning instrument: We used a RIEGL VZ-400 with a wavelength of 1550 nm, 0.35 mrad beam divergence and 0.04˚ angular resolution. - Locations: The data were collected from three sites in Milton Keynes, UK: Avebury Blvd (Ave), Dansteed Way (Dan), and Overgate (Ove). - File information: Each file is an individual leaf-off tree point cloud in Polygon File Format (.ply), which can be viewed in software such as CloudCompare.   Treegraph_outputs: - Description: Model outputs from Treegraph for individual trees. - File naming convention: [TreeID]-[downsample_voxel_length]-[tip_diameter_if_known].* <ul> <li>*.centres.ply: Skeleton nodes of individual trees.</li> <li>*.mesh.ply: Cylinder model of individual trees.</li> <li>*.json: Geometrical and topological attributes at varying scales, from internode and branch to the whole tree.</li> <li>*.txt: Summary of input parameters, logs of intermediate steps, and a statistical overview of whole-tree structural attributes.</li> </ul>

opencc-by-4.0Oct 2023View details →

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Terrestrial Laser Scanning data of two intertidal oyster reefs in the Wadden Sea, Germany (2020-2022)

Open the record for dataset details and reuse information.

publicOct 2024View details →

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Point clouds and QSM for 598 individually scanned tree branches to support "Terrestrial laser scanning to reconstruct branch architecture from harvested branches"

A collection of 598 harvested branches scanned in high resolution using terrestrial LiDAR. Branches were collected from GEM forest plots in Malaysia, Australia and Brazil. Branch nomenclature is PLOT-TREE-BN<S or SH> where PLOT codes can be found in the manuscript, N refers to the sample number of branch harvested from a tree, and S and SH refer to sun or shade branch respectivetly. For each branch there are 3 files:   <ul> <li>Unfiltered point clouds (raw_pc) are clipped from the original data only and have had no post processing applied</li> <li>Filtered point clouds (filtered_pc) have been filtered according to the steps in the manuscript</li> <li>QSMs were produced using treegraph (<a href="https://doi.org/10.5281/zenodo.5226212">https://doi.org/10.5281/zenodo.5226212</a>)</li> </ul> Polygon File Format (.ply) files can be viewed in software such as CloudCompare. Full details of methods can be found in: Wilkes, P., Shenkin, A., Disney, M., Malhi, Y., Bentley, L. P., & Vicari, M. B. (2021). Terrestrial laser scanning to reconstruct branch architecture from harvested branches. Methods in Ecology and Evolution, 12, 2487–2500. <a href="https://doi.org/10.1111/2041-210X.13709">https://doi.org/10.1111/2041-210X.13709</a>

opencc-by-4.0Apr 2024View details →

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Point cloud from terrestrial laser scanning of a coppiced beech tree (Fagus sylvatica) in Wytham Woods, UK

Point cloud of an old beech coppice stool located in Wytham Woods, UK.  A 3D model of the tree can be found <a href="https://skfb.ly/6WLqp">here</a> on SketchFab. Data was captured on 20/4/2021 with a RIEGL VZ-400 terrestrial laser scanner from 6 scan locations around the tree. The weather was good, with little to no noticeable wind. Data is a binary PLY format with reflectance, deviation and PCV fields as well as RGB. Note this data set still includes some ground returns. Please acknowledge the data set authors if using this data.