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Dataset results
18 results for “digital photography”
Historical digital elevation models (DEMs) and orthoimage mosaics for North American Glacier Aerial Photography (NAGAP) program, version 1.0
<p>This data archive contains digital elevation models (DEMs) and orthoimages generated from scanned historical aerial photographs from the North American Glacier Aerial Photography program available from the NSF Arctic Data Center (ADC, arcticdata.io). </p> <p>The scanned images were preprocessed using the <a href="https://github.com/friedrichknuth/hipp">Historical Image Pre-Processing</a> v0.1 software. Photogrammetric processing was performed with the <a href="https://github.com/friedrichknuth/hsfm">Historical Structure from Motion</a> v0.1 software. </p> <p>All DEM and orthoimage products are provided in the UTM Zone 10N (EPSG:32610) projected coordinate system. Elevation values are in meters above the WGS84 ellipsoid. </p> <p>See <a href="https://www.sciencedirect.com/science/article/pii/S0034425722004850">manuscript</a> and <a href="https://ars.els-cdn.com/content/image/1-s2.0-S0034425722004850-mmc1.pdf">supplement</a> for processing details and further dataset description.</p> <p>This release contains data products for two study sites in Washington state, USA:</p> <p><strong>Mount Baker</strong><br> 1970-09-09<br> 1970-09-29<br> 1974-08-10<br> 1977-09-27<br> 1979-10-06<br> 1987-08-21<br> 1990-09-05<br> 1991-09-09<br> 1992-09-15<br> 1992-09-18</p> <p><strong>South Cascade</strong><br> 1967-09-21<br> 1970-09-29<br> 1974-08-10<br> 1977-10-03<br> 1979-08-20<br> 1979-10-06<br> 1984-08-14<br> 1986-09-05<br> 1987-08-21<br> 1990-09-05<br> 1991-09-09<br> 1992-07-28<br> 1992-09-15<br> 1992-09-18<br> 1992-10-06<br> 1994-09-06<br> 1996-09-10<br> 1997-09-23</p> <p>The 00_thumbnails.jpg provides a quicklook overview at both sites.</p> <p><strong>The DEM and ortho file names are structured as follows:</strong><br> hsfm_NAGAP_[site-name]_[date]_[type].tif</p> <p><strong>For example:</strong><br> hsfm_NAGAP_south-cascade_19670921_ortho.tif</p> <p><strong>Where:</strong><br> [site-name] = Either mount-baker or south-cascade<br> [date] = Image acquisition date in YYYYMMDD format<br> [type] = File type</p> <p><strong>For each DEM and ortho pair, we provide the following:</strong><br> _1m_dem.tif = Digital elevation model posted at 1 m resolution <br> _ortho.tif = Orthoimage mosaic posted at the median image ground sample distance, rounded up to the nearest second decimal place.<br> _metadata.tar.gz = Metadata tarball containing:<br> _ortho_footprints.geojson = Orthoimage mosaic footprint polygons provided in GeoJSON format (EPSG:4326)<br> _dem_footprints.geojson = DEM footprint polygons provided in GeoJSON format (EPSG:4326)<br> _cameras.csv = Image file names, positions, and orientations</p>
Linked collectors and determiners for: Taxonomy and Biogeography without frontiers – WhatsApp, Facebook and smartphone digital photography let citizen scientists in more remote localities step out of the dark.
Natural history specimen data linked to collectors and determiners held within, "Taxonomy and Biogeography without frontiers – WhatsApp, Facebook and smartphone digital photography let citizen scientists in more remote localities step out of the dark". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/d9953b25-4b14-437c-aecf-1ccb60e8d698">https://bionomia.net/dataset/d9953b25-4b14-437c-aecf-1ccb60e8d698</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/d9953b25-4b14-437c-aecf-1ccb60e8d698">https://gbif.org/dataset/d9953b25-4b14-437c-aecf-1ccb60e8d698</a>. Formatted as a Frictionless Data package.
Data from: Two new species of Limbodessus diving beetles from New Guinea - short verbal descriptions flanked by online content (digital photography, μCT scans, drawings and DNA sequence data)
Background: To date only one species of Limbodessus diving beetles has been reported from the Island of New Guinea, L. compactus (Clark, 1862), which is widerspread in the Australian region. New information: We describe two new species of microendemic New Guinea Limbodessus and use a compact descriptive format flanked by enriched online content in wiki powered species pages. Limbodessus baliem sp.n. is described from ca. 1,600 m altitude in the Baliem Valley of Papua and Limbodessus alexanderi sp.n. from >3,000 m altitude north of Sugapa, Papua. Based on our analysis, we also transfer three species from other genera to Limbodessus Guignot, 1939, with the following changes: Limbodessus deflectus (Ordish, 1966), new combination; Limbodessus leveri (J. Balfour-Browne, 1944), new combination; and Limbodessus plicatus (Sharp, 1882), new combination.
Digital Ocular Fundus Photography in the Emergency Department: A New Application for Telemedicine?
ClinicalTrials.gov study NCT00873613. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Data from: Dietary studies in birds: testing a non-invasive method using digital photography in seabirds
Open the record for dataset details and reuse information.
Data from: Two new species of Limbodessus diving beetles from New Guinea - short verbal descriptions flanked by online content (digital photography, μCT scans, drawings and DNA sequence data)
Open the record for dataset details and reuse information.
Figure 1 in Moth floral visitors of the three rewarding Platanthera orchids revealed by interval photography with a digital camera
Figure 1. Floral visitors of Platanthera species. (A) Mabra charonialis visiting Platanthera ussuriensis; (B) Polychrysia splendida with Platanthera sachalinensis pollinia attached on the proboscis; (C) Paratalanta sp. visiting P. sachalinensis; (D) Lampropteryx sp. with Platanthera florentii pollinia attached on the eyes; (E) Scopariinae sp. visiting P. florentii and (F) Paratalanta sp. visiting P. florentii.
Data from: Digital photography provides a fast, reliable and non-invasive method to estimate anthocyanin pigment concentration in reproductive and vegetative plant tissues
1. Anthocyanin pigments have become a model trait for evolutionary ecology since they often provide adaptive benefits for plants. Anthocyanins have been traditionally quantified biochemically, or more recently using spectral reflectance. However, both methods require destructive sampling and can be labour intensive and challenging with small samples. Recent advances in digital photography and image processing make it the method of choice for measuring colour in the wild. Here, we use digital images as a quick, non-invasive method to estimate relative anthocyanin concentration among plants exhibiting colour variation. 2. By using a consumer-level digital camera and a free image processing toolbox, we extracted RGB values from digital images to generate colour indices. We tested petals, stems, pedicels and calyces of six species, which contain different types of anthocyanin pigments and exhibit different pigmentation patterns. Colour indices were assessed by their correlation to biochemically determined anthocyanin concentration. For comparison, we also calculated colour indices from spectral reflectance and tested the correlation with anthocyanin concentration. 3. Indices perform differently depending on the nature of the colour variation. For both digital images and spectral reflectance, the most accurate estimates of anthocyanin concentration emerge from anthocyanin content-chroma ratio (ACCR), anthocyanin-chroma basic (ACCB) and strength of green (S green) indices. Some colour indices derived from digital images and spectral reflectance strongly correlate with biochemically determined anthocyanin concentration, but the estimates from digital images performed better than spectral reflectance in terms of 2 and normalized root-mean-square error. This was particularly noticeable in a species with striped petals, but in the case of striped calyces both methods showed a comparable relationship with anthocyanin concentration. 4. Using digital images brings new opportunities to accurately quantify the anthocyanin concentration in both floral and vegetative tissues. This method is efficient, completely non-invasive, applicable to both uniform and patterned colour, and works with samples of any size.
Microhabitat selection of meadow and steppe vipers enlightened by digital photography and image processing to describe grassland vegetation structure
<p>Dataset</p> <ol> <li> <p>Understanding animals’ selection of microhabitats is important in both ecology and biodiversity conservation. However, there is no generally accepted methodology for the characterisation of microhabitats, especially for vegetation structure.</p> </li> <li> <p>We studied microhabitat selection of <em>Vipera</em> snakes by comparing grassland vegetation structure between viper occurrence points and random points in three grassland ecosystems: <em>V. graeca</em> in mountain meadows of Albania, <em>V. renardi</em> in loess steppes of Ukraine, and <em>V. ursinii</em> in sand grasslands in Hungary. We quantified vegetation structure in an objective manner by automated processing of images taken of the vegetation against a vegetation profile board under standardised conditions. We developed an R script for automatic calculation of four vegetation structure variables derived from raster data obtained in the images: leaf area (LA), height of closed vegetation (HCV), maximum height of vegetation (MHC), and foliage height diversity (FHD).</p> </li> <li> <p>Generalized linear mixed models revealed that snake occurrence was positively related to HCV in <em>V. graeca</em>, to LA in <em>V. renardi</em> and to LA and MHC in <em>V. ursinii</em>, and negatively to to HCV in <em>V. ursinii</em>.</p> </li> <li> <p>Our results demonstrate that vegetation structure variables derived from automated image processing significantly influence viper microhabitat selection. Our method minimises the risk of subjectivity in measuring vegetation structure, allows upscaling if neighbouring pixels are combined, and is suitable for comparison of or extrapolation across different grasslands, vegetation types or ecosystems.</p> </li> </ol>
Identification of Hypospadias Parameters Using Digital Photography and Artificial Intelligence
ClinicalTrials.gov study NCT05569863. IPD Sharing: NO. Countries: 0. Publications: 3.
Digital Photography to Evaluate Dry Eye
ClinicalTrials.gov study NCT00073099. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Digital photography provides a fast, reliable and non-invasive method to estimate anthocyanin pigment concentration in reproductive and vegetative plant tissues
Open the record for dataset details and reuse information.
Self Digital Photography for Assessing Elbow Range of Motion
ClinicalTrials.gov study NCT02985788. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Digital Photography to Estimate Anthropometric Measurements in Children
ClinicalTrials.gov study NCT05034913. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Impact Of Digital Photography & Conventional Method On The Accuracy Of Dental Shade Matching In The Esthetic Zone
ClinicalTrials.gov study NCT03229707. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Feasibility Study of Digital Photography and Group Discussion for People With Diabetes
ClinicalTrials.gov study NCT00225888. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Efficacy and Safety of Pulmonary Function Analysis With Dynamic Digital Radiography Total Respiratory Cycle Photography
ClinicalTrials.gov study NCT05565027. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Tooth Color Differences Between Digital Photography and Spectrophotometer in both Genders An In Vivo Study
<p>This is an SPSS file that was used in the study title: Tooth Color Differences Between Digital Photography and Spectrophotometer in both Genders An In Vivo Study</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.