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183 results for “Laser Scanning”
3D Laser Scanning Data: Public Square in Murcia and Engineering Laboratory at the University of Alicante
<p>This dataset includes 3D terrestrial laser scans obtained using the Leica C10 ScanStation. The data covers two distinct scenarios:</p> <ol> <li> <p><strong>Public Square in Murcia Capital</strong>: This dataset includes two scan positions within a public square located in Murcia. Three HDTarget markers were placed, and their center or vertex coordinates are provided in the accompanying _vertices.txt file. The scans were conducted with the laser scanner leveled, but they are not registered.</p> </li> <li> <p><strong>Engineering Laboratory at the University of Alicante</strong>: This dataset consists of two scans of the Ground Engineering Laboratory at the University of Alicante. The scans were conducted with the same leveled laser scanner, and no targets were used. Between the two scans, some elements in the laboratory were slightly moved, which can be identified by comparing the point clouds.</p> </li> </ol>
Point clouds from terrestrial laser scanning of 97 trees in St Pancras Old Church, London
<p>Point clouds of 97 trees scanned in the grounds of St Pancras Old Church, Camden, London</p> <p>Tree species is predominantly London Plane (<em>Platanus × hispanica</em>) but also includes the <a href="https://www.atlasobscura.com/places/the-hardy-tree-london-england">Hardy ash tree</a>.</p> <p>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.</p> <p>Data is a binary PLY format with <em>xyz</em> 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.</p> <p>Raw data can be accessed from here.</p> <p>Please acknowledge the data set authors if using this data.</p>
Point clouds from terrestrial laser scanning of 30 trees along Malet Street, London
<p>Point clouds of 30 street trees scanned along <a href="https://goo.gl/maps/7x3dutn6vHcxVPdC6">Malet Street, London, UK</a>. </p> <p>Tree species is predominantly London Plane (<em>Platanus × hispanica</em>).</p> <p>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.</p> <p>Data is a binary PLY format with <em>xyz</em> 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.</p> <p>Raw data can be accessed from here.</p> <p>Please acknowledge the data set authors if using this data.</p>
Point clouds from terrestrial laser scanning of 74 trees in Russell Square, London
<p>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></p> <p>Tree species is predominantly London Plane (<em>Platanus × hispanica</em>).</p> <p>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.</p> <p>Data is a binary PLY format with <em>xyz</em> 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.</p> <p>Raw data can be downloaded from <a href="https://doi.org/10.5281/zenodo.5070681">10.5281/zenodo.5070681</a></p> <p>Please acknowledge the data set authors if using this data.</p>
FIG. 4 in New insights on the morphology of a digenean parasite Digenea: Brachylaimidae, Brachylaima mazzantii (Travassos, 1927)) using confocal laser scanning microscopy
FIG. 4. — Confocal tomographies of the reproductive system of Brachylaima mazzantii (Travassos, 1927): A, Mehlis' gland (mg), vitelline reservoir (vr), ovary (ov) and testes (t); B, ovary (ov), seminal reservoir (sr), testes (t) and intestinal caeca (ic); C, ovary (ov) and ootype (oo); D, vitelline glands (vg) forming lobed acini; E, vitelline duct (vd) showing vitelline cells inside forming a single row; F, uterus full of eggs; G, egg, revealing the embryo (emb), eggshell (sh), operculum (op) and discontinuity area (da) in the eggshell. Scale bars: A, B, D, F, 50 μm; C, E, 10 μm; G, 5 μm.
FIG. 8 in New insights on the morphology of a digenean parasite Digenea: Brachylaimidae, Brachylaima mazzantii (Travassos, 1927)) using confocal laser scanning microscopy
FIG. 8. — Reproductive system of Brachylaima mazzantii (Travassos, 1927) as first described by Travassos in 1927 (adapted from Lent & Freitas 1937). Scale bar: 1 mm.
FIG. 1 in New insights on the morphology of a digenean parasite Digenea: Brachylaimidae, Brachylaima mazzantii (Travassos, 1927)) using confocal laser scanning microscopy
FIG. 1. — Confocal tomographies of the reproductive system of Brachylaima mazzantii (Travassos, 1927): A, gland cells (gc) surrounding the genital pore (gp); B, commissure (co) and gland cells (gc); C, region of the genital opening showing differentiated musculature (dfm); D, female genital opening (fgo), male genital opening (mgo) and unarmed cirrus (ci); E, cirrus pouch (cip), metraterm (m), testes (t), bursa (b) and seminal vesicle (sv); F, vitelline duct (vd), vitelline reservoir (vr), uterus (u), ovary (ov) and testes (t). Scale bars: 50 μm.
FIG. 6 in New insights on the morphology of a digenean parasite Digenea: Brachylaimidae, Brachylaima mazzantii (Travassos, 1927)) using confocal laser scanning microscopy
FIG. 6. — Confocal tomographies of tegument, musculature of the body and acetabulum of Brachylaima mazzantii (Travassos, 1927): A, tegument covered by many scales; B, scales; C, circular musculature (cm); D, longitudinal (lm) and diagonal musculature (dm); E, two differentiated muscle bundles (dfm); F, surface of acetabulum featuring many papillae (p); G, papillae (p), radial musculature (rm) and differentiated musculature (dfm) supporting the acetabulum; H, papillae. Scale bars: A-G, 50 μm; H, 10 μm.
FIG. 3 in New insights on the morphology of a digenean parasite Digenea: Brachylaimidae, Brachylaima mazzantii (Travassos, 1927)) using confocal laser scanning microscopy
FIG. 3. — Schematic drawings of the reproductive system of Brachylaima mazzantii (Travassos, 1927): A, reconstruction of the reproductive system from the confocal tomographies, showing seminal vesicle (sv), metraterm (m), cirrus (c), cirrus pouch (cp), genital atrium (ga), testes (t), ovary (o), ootype (oo), vitelline duct (vd), vitelline glands (vg) vitelline reservoir (vr), and Mehlis' gland (mg); B, cirrus pouch as first described by Travassos in 1927 (adapted from Lent & Freitas 1937). Scale bars: A, 0.06 mm; B, 0.25 cm.
FIG. 5 in New insights on the morphology of a digenean parasite Digenea: Brachylaimidae, Brachylaima mazzantii (Travassos, 1927)) using confocal laser scanning microscopy
FIG. 5. — Confocal tomographies showing the anterior region of Brachylaima mazzantii (Travassos, 1927): A, image showing the meridional musculature (mm); B, equatorial musculature (eqm); C, radial musculature (rm), papillae (p) on the surface of the oral sucker and differentiated musculature (dfm) making the transition between mouth and pharynx (pre-pharynx); D, pharynx (ph), radial musculature (rm), esophagus (e), and intestinal caeca (ic); E, detail of the intestinal caeca, revealing numerous microvilli (mi), and the epithelium (ep); F, esophageal glands (eg) circling the esophagus. Scale bars: A-D, 50 μm; E, 10 μm.
FIG. 2 in New insights on the morphology of a digenean parasite Digenea: Brachylaimidae, Brachylaima mazzantii (Travassos, 1927)) using confocal laser scanning microscopy
FIG. 2. — Schematic drawings of the genital atrium of Brachylaima mazzantii (Travassos, 1927): A-D, sequential tomographic images starting from the body surface. Scale bar: 5 µm.
FIG. 7 in New insights on the morphology of a digenean parasite Digenea: Brachylaimidae, Brachylaima mazzantii (Travassos, 1927)) using confocal laser scanning microscopy
FIG. 7. — Confocal tomographies of the excretory and nervous system of Brachylaima mazzantii (Travassos, 1927): A, excretory ducts (exd), testes (t); B, excretory bladder (exb), excretory pore (exp), and testes (t); C, longitudinal nervous cord (nc); D, commissures (co) originated from the nervous cord (nc). Scale bars: A-C, 50 μm; D, 10 μm.
Terrestrial laser scanning data Wytham Woods: individual trees and quantitative structure models (QSMs)
<p>This dataset was used for the analysis of the following publication:<br> <em>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)</em></p> <p><strong>Any use of this dataset should cite the paper above </strong>(Creative Commons Attribution 4.0 International Public License).</p> <p>Contact: kim.calders@ugent.be</p> <p> </p> <p>================================================<br> Dataset<br> ================================================</p> <p><strong>General</strong>: <br> 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</p> <p>[ 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]</p> <p>Full details of the methods to segment individual trees and generate the QSMs can be found in the paper <em>Calders et al. Ecological Solutions and Evidence.</em></p> <p><strong>Tree ID:</strong><br> 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.</p> <p><strong>Datasets:</strong><br> 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</p> <p>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 </p> <p>3) Raw scan data can be found here: http://dx.doi.org/10.5285/ed9156e1697343e4ad82e83ed550e345</p> <p> </p> <p>================================================<br> Paper analysis<br> ================================================</p> <p>We have provided all scripts (analysis_and_figures) that were used to:</p> <p>1 ) analyse the data (TLS_Inventory.ipynb):<br> ----- Analysis of point clouds and QSMs using TLS_Inventory.py.ipynb > tls_summary.csv (#876 trees)<br> ----- Link with census &1.4ha > trees_summary.csv (#835 trees)</p> <p>2) generate the paper figures:<br> ----- various *.R and *.ipynb scripts in the main folder and /allometriesTLS/</p> <p> </p> <p>================================================<br> Funding<br> ================================================</p> <p>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).</p>
Data from: Leveraging a new branch-based taper curve and form factor from terrestrial laser scanning proxies
<p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p>
Fig. 11. Confocal laser scanning 3D reconstructions. A in Living on the edge - first survey of loriciferans along the Atacama Trench
Fig. 11. Confocal laser scanning 3D reconstructions. A. Pliciloricus leocaudatus, ventral view, paratype (NHMD 100760). B. Pliciloricus aff. ukupachaensis collected off Oregon, US west coast, lateral view (NHMD 225904).
FOR-instance: a UAV laser scanning benchmark dataset for semantic and instance segmentation of individual trees
<p>The challenge of accurately segmenting individual trees from laser scanning data hinders the assessment of crucial tree parameters necessary for effective forest management, impacting many downstream applications. While dense laser scanning offers detailed 3D representations, automating the segmentation of trees and their structures from point clouds remains difficult. The lack of suitable benchmark datasets and reliance on small datasets have limited method development. The emergence of deep learning models exacerbates the need for standardized benchmarks. Addressing these gaps, the FOR-instance data represent a novel benchmarking dataset to enhance forest measurement using dense airborne laser scanning data, aiding researchers in advancing segmentation methods for forested 3D scenes.</p> <p>In this repository, users will find forest laser scanning point clouds from unamnned aerial vehicle (using Riegl sensors) that are manually segmented according to the individual trees (1130 trees) and semantic classes. The point clouds are subdivided into five data collections representing different forests in Norway, the Czech Republic, Austria, New Zealand, and Australia. </p> <p>These data are meant to be used either for developement of new methods (using the dev data) or for testing of exisitng methods (test data). The data splits are provided in the data_split_metadata.csv file.</p> <p>A full description of the FOR-instance data can be found at <a href="http://arxiv.org/abs/2309.01279">http://arxiv.org/abs/2309.01279</a> </p>
UVA laser scanning labelled las data over tropical moist forest classified as leaf or wood points
<p>UAV Laser Scanning data collected over neotropical forest (Paracou French Guiana). Four flights conducted over one ha plot in 2021 and 2022.</p> <p>Leaf wood labels were transferred from contemporaneous (2021) TLS acquisition, for which segmentation was done using LeWoS and onscreen post correction.</p> <p>Predicted values using SOUL model (see ref below) for a single UAV-LS acquisition are provided as separate file.</p> <p> </p>
Terrestrial laser scanning data of urban trees in Milton Keynes, UK: individual trees and Treegraph model outputs
<p><strong>TLS_point_clouds:</strong></p> <p>- Data collection: Terrestrial laser scanning data acquired in leaf-off condition in April 2021.</p> <p>- Scanning instrument: We used a RIEGL VZ-400 with a wavelength of 1550 nm, 0.35 mrad beam divergence and 0.04˚ angular resolution.</p> <p>- Locations: The data were collected from three urban sites in Milton Keynes, UK: Avebury Blvd (Ave), Dansteed Way (Dan), and Overgate (Ove).</p> <p>- File information: Each file is an individual tree point cloud in Polygon File Format (.ply), which can be viewed in software such as CloudCompare.</p> <p> </p> <p><strong>Treegraph_outputs:</strong></p> <p>- Description: Model outputs from <em>Treegraph</em> for individual trees.</p> <p>- File naming convention: [TreeID]-[downsample_voxel_length]-[tip_diameter_if_known].*</p> <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>
Detection of standing retention trees in boreal forests with airborne laser scanning point clouds and multispectral imagery
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Data from: Leveraging a new branch-based taper curve and form factor from terrestrial laser scanning proxies
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