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183 results for “Laser Scanning”
FIGURE 3 in Confocal laser scanning microscopy technique for the study of internal genitalia and external morphology of eriophyoid mites (Acari: Eriophyoidea)
FIGURE 3. Images obtained via LSCM of specimens on older microscope slides. A. Boczekella reticulata (slide-mounted on 11 May 2010); B. Sierraphytoptus ambulans (21 Sept. 2008), C. Phytoptus atherodes (5 Aug. 2003), D. Novophytoptus?stipae (9–14 Sept. 1976, uncoloured and black-white inverted). Note: empodia and proximal part of setae are not visible with blue laser (see 2B & 2D).
FIGURE 5 in Confocal laser scanning microscopy technique for the study of internal genitalia and external morphology of eriophyoid mites (Acari: Eriophyoidea)
FIGURE 5. CLSM images (blue laser) of female internal genitalia (A) and spermatophore inside male (B). A. Phytoptus chamaebatiae. B. Setoptus pini. Note: original pseudocolour obtained from CLS microscope using Leica software was saved on both images.
FIGURE 2 in Confocal laser scanning microscopy technique for the study of internal genitalia and external morphology of eriophyoid mites (Acari: Eriophyoidea)
FIGURE 2. Larvae of Phytoptus hirtae inside egg (fresh microscope slides). Note: the colour was changed from original (pseudo colour) red to light blue-green for enhancing contrast.
FIGURE 1 in Confocal laser scanning microscopy technique for the study of internal genitalia and external morphology of eriophyoid mites (Acari: Eriophyoidea)
FIGURE 1. Images obtained via CLSM of fresh microscope slides (specimens mounted between April and September 2011). A. Phytoptus rigidus; B. Trisetacus?kirghisorum; C. Setoptus pini. Original colour (pseudo-colour) kept. Note: blue is the colour of the exciting laser.
FIGURE 7 in Confocal laser scanning microscopy technique for the study of internal genitalia and external morphology of eriophyoid mites (Acari: Eriophyoidea)
FIGURE 7. CLSM images of empodia of Setoptus pini (reflected laser light): A. red laser, B. blue laser, C. green laser. Note: the original pseudo-colour was changed to red (A), blue (B) and green (C).
Data for article: Robust characterization of forest structure from airborne laser scanning – a systematic assessment and sample workflow for ecologists
<p><strong>### Update 03/02/2025: the most up to date version of the processing pipeline presented here, also working on Linux, is available on github: https://github.com/fischer-fjd/GCA/tree/main, and a worked example with open data from the Dutch AHN surveys is available on Zenodo: https://zenodo.org/records/14722001 ###<br></strong></p> <p>This is a collection of scripts and research data to assess the robustness of forest structure characterization from airborne laser scanning (ALS). It accompanies the article "Robust characterization of forest structure from airborne laser scanning – a systematic assessment and sample workflow for ecologists" (accepted in Methods in Ecology and Evolution on 25/08/2024). </p> <p>In the article, we assess the derivation of canopy height models (CHMs) from point cloud data, how sensitive CHM algorithms are to point cloud degradation (pulse density thinning, large scan angles, loss of higher-order returns) and how uncertainties and biases propagate to commonly used forest structure metrics. In addition, we provide a standardized processing pipeline in R to convert point clouds into CHMs. </p> <p>The main data source for this study are ALS point clouds from nine Australian research sites belonging to the Terrestrial Ecosystem Research Network (TERN, 5 km x 5 km extent each). The underlying data can be found here: https://portal.tern.org.au/metadata/TERN/4ff0b4c9-cfa0-4d09-9520-b5402adc583f. For one site (Robson Creek), we also used field data to assess the sensitivity of aboveground biomass estimates to ALS point cloud characteristics. Data are available here: https://portal.tern.org.au/metadata/supersite.174. </p> <p>To characterize climatic/environmental differences between sites, we used climatic data from the CHELSA/BIOCLIM+ climatology 1981-2010 (Brun et al. 2022: Global climate-related predictors at kilometer resolution for the past and future. Earth System Science Data, 14(12), 5573–5603. https://doi.org/10.5194/essd-14-5573-2022; Karger et al. 2017: Climatologies at high resolution for the earth's land surface areas. Scientific Data, 4(1), 170122. https://doi.org/10.1038/sdata.2017.122). </p> <p>We note that the enormous size of the full set of manipulated point clouds (original + thinned + individual flightlines: ~400 GB) and the derived raster products (~200 GB) by far exceeds limits on data storage in Zenodo. However, all analyses can be recreated from scratch from the openly available data and the R code in this repository. In addition, we include derived products for the nine study sites that allow to replicate results in the main text without any point cloud processing (CHMs and other rasters across thinned point clouds + summary statistics). </p> <p>The different data layers are:</p> <p><strong>01_rscripts.zip:</strong></p> <ul> <li>contains a sample script to test the processing pipeline (<em>test.processing.R</em>) as well as a collection of helper functions (<em>ALS_processing_helperfunctions_v40.R</em>); the script can be run directly after unzipping the folder, but an installation of LAStools (https://rapidlasso.de) is necessary (path_lastools = "PATH/TO/LASTOOLS/BIN"); we note that the script was developed on Windows PCs, its application with the recent Linux distribution of LAStools has not yet been tested</li> <li>contains the full set of scripts necessary to reproduce the analyses, including point cloud manipulations and derivation of CHMs from the raw data (<em>create.CHMs.R)</em> as well as the overall robustness analysis (<em>analyze.CHMs.R</em>); to replicate the processing of the raw point clouds step by step, .laz files should be downloaded from the TERN repository (cf. citation above) and placed in a "data" folder, with subfolders for each site and with the same naming conventions as in this repository (e.g., "/data/Alice Mulga")</li> </ul> <p><strong>02_reference.zip</strong></p> <ul> <li>contains reference digital surface models (DSMs), canopy height models (CHMs) and digital terrain models (DTMs) for all nine TERN sites, based on the original ALS point clouds</li> <li>note that these reference layers are produced with the "CHMhighest" algorithm, which provides an easily interpretable canopy description as long as pulse densities are high (>= 20 shots per squaremetre)</li> </ul> <p><strong>03_climate.zip</strong></p> <ul> <li>contains site coordinates</li> <li>contains the climate layers from the CHELSA climatology (cf. citation above, only used to evaluate climatic ranges of sites)</li> </ul> <p><strong>04_robson_additional.zip</strong></p> <ul> <li>contains biomass estimates for Robson Creek</li> <li>contains shapefiles for large trees at Robson Creek (only used for visualization purposes)</li> </ul> <p><strong>05_downsampling_pulse_[Site name].zip</strong></p> <ul> <li>[Site name] is a stand-in for the nine TERN sites (e.g., "Alice Mulga.zip", "Credo.zip", etc.)</li> <li>contains the data necessary to reproduce results in the main text of the study, i.e. DSMs, CHMs, and DTMs for all nine TERN sites, and at different pulse density levels (from 16 down to 0.5 laser shots per squaremetre)</li> <li>also contains calculated summary statistics for each site</li> </ul> <p>All zip files should be extracted into the same folder, except for 05_downsampling_pulse_[Site name].zip which should all be moved to a subfolder called "downsampling_pulse".</p>
Supplementary Data for Manuscript 'Observing impacts on luminescence depth profile evolutions from surface altered quartzite using OSL laser scanning and controlled light exposed rock sampling techniques'
<p>This file contains the supplementary data for the manuscript 'Observing impacts on luminescence depth profile evolutions from surface altered quartzite using OSL laser scanning and controlled light exposed rock sampling techniques'</p>
Point clouds and QSM for 598 individually scanned tree branches to support "Terrestrial laser scanning to reconstruct branch architecture from harvested branches"
<p>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.</p> <p>Branch nomenclature is <em>PLOT</em>-<em>TREE</em>-B<em>N</em><S or SH> where <em>PLOT </em>codes can be found in the manuscript, <em>N</em> refers to the sample number of branch harvested from a tree, and S and SH refer to sun or shade branch respectivetly.</p> <p>For each branch there are 3 files: </p> <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 <em>treegraph </em>(<a href="https://doi.org/10.5281/zenodo.5226212">https://doi.org/10.5281/zenodo.5226212</a>)</li> </ul> <p>Polygon File Format (.ply) files can be viewed in software such as CloudCompare.</p> <p>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. <em>Methods in Ecology and Evolution</em>, 12, 2487–2500. <a href="https://doi.org/10.1111/2041-210X.13709">https://doi.org/10.1111/2041-210X.13709</a></p>
FIGURE 1 in Micromorphology of seeds of three Mexican species of Pinguicula (Lentibulariaceae) show autofluorescence using confocal laser scanning microscopy
FIGURE 1. Confocal laser scanning microscopy images showing the micromorphological features of Pinguicula seeds. A–D. Pinguicula casperi; E–H. P. parvifolia; I–L. P. oblongiloba. A, E and I are a general view of the entire seeds (20×, scale bar 100 μm); B, F and J show the micropylar end (60×, scale bar 20 μm); D, H, and L show the chalazal end of the seed (60×, scale bar 20 μm); C, G and K show the surface details of the seeds (100×, scale bar 10 μm).
Comparability of skeletal fibulae surfaces generated by different source scanning (dual-energy CT scan vs. high resolution laser scanning) and 3D geometric morphometric validation
<p><strong>SI_Appendix 1.</strong> Matrix of Cartesian coordinates of analyzed specimens.</p> <p><strong>SI_Appendix 2</strong>. Sample list and acquisition methods. </p>
Dynamic deformation calculation of articular cartilage and cells using resonance-driven laser scanning microscopy - Osmotic Challenge and Validation Testing Dataset
<p>This archive contains 3-D image stacks obtained over time of articular cartilage undergoing osmotic swelling. These were acquired with a resonance scanning protocol, which allows for fast scanning but with decreased image quality. The Python package, resonant_lsm, was developed to segment and analyze the deformation of cells in such images. The archive also contains validation testing data of this software. Included README files document the archive contents and how to reproduce the analyses. </p>
basketry- child's shoe (laser scanned)
Made with the Next Engine Laser Scanner Source: Objaverse 1.0 / Sketchfab
cedar cylinder basket (laser scanned)
Made with the Next Engine laser scanner Source: Objaverse 1.0 / Sketchfab
Fig. 2 Confocal laser scanning microscopy images showing the hard tick morphology. a in parasitised feathered dinosaurs as Cretaceous amber assemblages revealed
Fig. 2 Confocal laser scanning microscopy images showing the hard tick morphology. a Habitus in ventral view of the Cornupalpatum burmanicum nymph associated with feathers. Scale bar, 0.2 mm. b Detail of the gnathosoma and coxal area in ventral view revealing the absence of genital pore. Scale bar, 0.1 mm. c Dorsal view detail of the gnathosoma and anterior part of the scutum (arrow indicates the lateral margin of the scutum). Scale bar, 0.1 mm
Point cloud from terrestrial laser scanning of a coppiced beech tree (Fagus sylvatica) in Wytham Woods, UK
<p>Point cloud of an old beech coppice stool located in Wytham Woods, UK. </p> <p>A 3D model of the tree can be found <a href="https://skfb.ly/6WLqp">here</a> on SketchFab.</p> <p>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.</p> <p>Please acknowledge the data set authors if using this data.</p>
Figure 3 in Confocal laser scanning microscopy analysis of the phalloidin-labelled musculature in nemerteans
Figure 3. Confocal projections of the longitudinal sections of the body wall musculature showing diagonal muscles (A–E) and fascias of the extracellular matrix (F, arrows), dorsal view. (A) Carinina sp., precerebral region; (B) Hubrechtella juliae, just behind mouth; (C) Cephalothrix cf. simula, just behind mouth; (D) Tetrastemma sp., middle body region; (E) Quasitetrastemma stimpsoni, middle body region; (F) Collarenemertes bimaculata, middle body region. Abbreviation: gp, gonopore. Scales: 50 µm.
Figure 5 in Confocal laser scanning microscopy analysis of the phalloidin-labelled musculature in nemerteans
Figure 5. Confocal projections of the transversal (A, B) and longitudinal (C–I) sections of the proboscis. Anterior (A–D, F, G) and middle (E, H, I) proboscis portions. (A, B), everted proboscis of Cerebratulus marginatus; (C) third proboscis region of Callinera sp.; (D) longitudinal and diagonal musculature in region of muscle cross (arrows) of Nipponomicrura uchidai; (E) bulb region of Emplectonema gracile; (F, G) anterior proboscis region of Ototyphlonemertes martynovi (F) and Ototyphlonemertes valentinae (G); (H, I) middle proboscis region of Ototyphlonemertes martynovi (H) and Ototyphlonemertes valentinae (I). Abbreviations: as, anterior sphincter; cm, circular musculature; dm, diagonal musculature; ge, glandular epithelium; icm, inner circular musculature; lm, longitudinal musculature; ls, longitudinal muscle strand; mc, muscle cross; pms, posterior muscle sheath. Scale: (A), 200 µm; (B–E, G), 50 µm; (F, H, I), 20 µm.
Figure 7 in Confocal laser scanning microscopy analysis of the phalloidin-labelled musculature in nemerteans
Figure 7. Confocal projections of the longitudinal sections of gonadal sac musculature. (A, B, E, F) mature ovaries of Emplectonema gracile (A), Antarctonemertes varvarae (B), Tetrastemma sp. (E), and Malacobdella grossa (F), ventral view; (C) immature testis of Antarctonemertes varvarae, ventral view; (D) gonopore of Tetrastemma sp., dorsal view. Abbreviation: gp, gonopore; lm, longitudinal body musculature. Scale: (A–E), 50 µm; (F), 100 µm.
Figure 2 in Confocal laser scanning microscopy analysis of the phalloidin-labelled musculature in nemerteans
Figure 2. Confocal projections of the longitudinal (A–D) and transversal (E) sections showing dermal musculature. (A, B) Cerebratulus marginatus, just behind mouth, dorsal view (A), precerebral region, dorsal view (B); (C) Lineus alborostratus, just behind mouth, dorsal view; (D, E) Hubrechtella juliae, brain region, dorsal view (D), transversal section through the brain region showing connection of the dermal and outer circular muscles (arrows) (E). Abbreviations: br, brain; cdm, circular dermal muscles; em, epidermal muscle processes; lm, longitudinal musculature; pr, proboscis. Scales: 50 µm.
Figure 6 in Confocal laser scanning microscopy analysis of the phalloidin-labelled musculature in nemerteans
Figure 6. Schematic diagrams of the body wall musculature (A–C) and proboscis musculature (D–F). (A) Tubulanid palaeonemerteans; (B) heteronemerteans; (C) hoplonemerteans; (D, D̓) palaeonemerteans (D, Cephalothrix; D̓, Carinoma); (E) Ototyphlonemertes valentinae; (F) lineid nemerteans (only outer circular and diagonal musculature). Abbreviations: ddm, diagonal dermal muscles; dm, diagonal muscles; icm, inner circular musculature; ilm, inner longitudinal musculature; ldm, longitudinal dermal muscles; lm, longitudinal musculature; ls, longitudinal muscle strand; mc, muscle cross; mcm, middle circular musculature; ocm, outer circular musculature; olm, outer longitudinal musculature; rem, radial epidermal muscles.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.