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533
datasets available to search
ShareScore release 0.9.0
Dataset results
533 results for “Aerial”
ABoVE: Aerial Photographs of Frozen Lakes near Fairbanks, Alaska, October 2014
This dataset includes high resolution orthophotographs of 21 lakes in the region of Fairbanks, Alaska, USA. Aerial photographs were taken on October 8, 2014, three days after lake-ice formation. These photographs were used to identify open holes in lake ice that indicate the location of hotspot seeps associated with the releases of methane from thawing permafrost. Aerial photography can be used to measure changes in lake areas and to observe patterns in the formation of lake ice and other early winter lake conditions.
G-LiHT Aerial Orthomosaic V001
Goddard’s LiDAR, Hyperspectral, and Thermal Imager ([G-LiHT](https://gliht.gsfc.nasa.gov/)) mission is a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico.The purpose of G-LiHT’s Aerial Orthomosaic data product (GLORTHO) is to provide orthorectified high-resolution aerial photography. This data is provided as a supplement to other G-LiHT data products.GLORTHO data are processed as a raster data product (GeoTIFF) at 1 inch spatial resolution over locally defined areas. A low resolution browse is also provided with a color map applied in PNG format. Known Issues* Orthomosaics are automatically generated, and results may not be optimal.
SAFARI 2000 ER-2 Color-IR Aerial Photography, Dry Season 2000
Aerial photography from the NASA ER-2 high altitude aircraft was collected to provide detailed and spatially extensive documentation over parts of the SAFARI study area. The ER-2 aerial photography consists of 3,046 color-infrared (IR) transparencies collected during the SAFARI 2000 Dry Season Aircraft Campaign in August and September of 2000. ORNL DAAC has archived scanned subsets of the ER-2 aerial photography.The original color-IR aerial photography the SAFARI 2000 Dry Season Aircraft Campaign is located at NASA Ames Research Center (ARC) Aircraft Data and Sensor Facilities. Copies can be ordered from the U.S. Geological Survey's EROS Data Center (EDC) in Sioux Falls, South Dakota, USA. In addition, 515 image frames have been scanned from copies of the original level-0 ER-2 aerial photography by the University of the Witwatersrand (Wits), in Pretoria, South Africa. ORNL DAAC has archived subsets of the available imagery from ARC and Wits. Information about the imagery subsets that are available from ORNL DAAC, as well as information about the original color-IR aerial photography at ARC and scanned imagery at Wits can be found at: ftp://daac.ornl.gov/data/safari2k/atmospheric/remote_sensing/er2_aerial_photos/comp/er2_aerial_photos_readme.pdf.
Hormone and transcriptome profiling in aerial tissues derived from crown buds of glyphosate treated leafy spurge
GEO Series GSE56509. Euphorbia esula. 8 samples. Type: Expression profiling by high throughput sequencing.
Accumulation of TuMV-derived siRNAs in aerial parts of Arabidopsis thaliana plants at 7 and 10 dpi
GEO Series GSE20197. Arabidopsis thaliana; Turnip mosaic virus. 36 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Histone modifications of Arabidopsis thaliana (aerial tissue)
GEO Series GSE28398. Arabidopsis thaliana. 12 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
A rapid transcriptome response is associated with desiccation resistance in aerially-exposed killifish embryos
GEO Series GSE19424. Fundulus heteroclitus. 42 samples. Type: Expression profiling by array.
Data and R code for the preprint "Downscaling digital soil maps using electromagnetic induction and aerial imagery"
<p>Data and R code used in the preprint "Downscaling digital soil maps using electromagnetic induction and aerial imagery" (Møller, 2020). This is the data and code for the preprint before submission for peer review. The data and code for the revised manuscript are available at <a href="https://doi.org/10.5281/zenodo.3959005">https://doi.org/10.5281/zenodo.3959005</a>.</p> <p>Code originally written for R version 3.6.2.</p> <p>References<br> Møller, A.B., Koganti, T., Beucher, A., Iversen, B.V. and Greve, M.H., 2020. Downscaling digital soil maps using electromagnetic induction and aerial imagery. EarthArXiv. <a href="http://dx.doi.org/10.31223/osf.io/a7xz6">http://dx.doi.org/10.31223/osf.io/a7xz6</a>. [preprint]</p> <p> </p>
Fusion of Single and Integral Multispectral Aerial Images
<p>We present a novel hybrid (model- and learning-based) architecture for fusing the most significant features from conventional aerial images and integral aerial images that result from synthetic aperture sensing for removing occlusion caused by dense vegetation. It combines the environment's spatial references with features of unoccuded targets. Our method out-beats the state-of-the-art, does not require manually tuned parameters, can be extended to an arbitrary number and combinations of spectral channels, and is reconfigurable to address different use-cases. </p>
Replication Package: "When Uncertainty Leads to Unsafety: Empirical Insights into the Role of Uncertainty in Unmanned Aerial Vehicle Safety"
<p>Replication Package of the paper titled "When Uncertainty Leads to Unsafety: Empirical Insights into the Role of Uncertainty in Unmanned Aerial Vehicle Safety"</p>
Figure 2 from: Marinov T, Kokanova-Nedialkova Z, Nedialkov P (2024) UHPLC-HRMS-based profiling and simultaneous quantification of the hydrophilic phenolic compounds from the aerial parts of Hypericum aucheri Jaub. & Spach (Hypericaceae). Pharmacia 71: 1-11. https://doi.org/10.3897/pharmacia.71.e122436
Figure 2 Chromatogram of the EtOH extract from the aerial parts of Hypericum aucheri.
Figure 5 from: Marinov T, Kokanova-Nedialkova Z, Nedialkov P (2024) UHPLC-HRMS-based profiling and simultaneous quantification of the hydrophilic phenolic compounds from the aerial parts of Hypericum aucheri Jaub. & Spach (Hypericaceae). Pharmacia 71: 1-11. https://doi.org/10.3897/pharmacia.71.e122436
Figure 5 A postulated fragmentation pathway of flavanols.
Figure 4 from: Marinov T, Kokanova-Nedialkova Z, Nedialkov P (2024) UHPLC-HRMS-based profiling and simultaneous quantification of the hydrophilic phenolic compounds from the aerial parts of Hypericum aucheri Jaub. & Spach (Hypericaceae). Pharmacia 71: 1-11. https://doi.org/10.3897/pharmacia.71.e122436
Figure 4 The fragmentation pattern of xanthone-C-glycosides.
Figure 3 from: Marinov T, Kokanova-Nedialkova Z, Nedialkov P (2024) UHPLC-HRMS-based profiling and simultaneous quantification of the hydrophilic phenolic compounds from the aerial parts of Hypericum aucheri Jaub. & Spach (Hypericaceae). Pharmacia 71: 1-11. https://doi.org/10.3897/pharmacia.71.e122436
Figure 3 A postulated fragmentation pathway of maclurin.
A Comparison of LiDAR-based SLAM Systems for Control of Unmanned Aerial Vehicles
<p>Datasets collected from the experiments described in the paper R. Milijas, L. Markovic, A. Ivanovic, F. Petric and S. Bogdan, "A Comparison of LiDAR-based SLAM Systems for Control of Unmanned Aerial Vehicles," <em>2021 International Conference on Unmanned Aircraft Systems (ICUAS)</em>, 2021, pp. 1148-1154, doi: 10.1109/ICUAS51884.2021.9476802.</p> <p>The datasets consist of ROS bags which hold the UAV and LiDAR data, and of zip files which hold only the lidar data in binary format for non-ROS users.</p>
Prediction of Yield and Nitrogen-Use Efficiency by Using Consumer-Grade Unmanned Aerial Vehicle Multispectral Images of Winter Wheat
<p>It contains supplementary materials(revised version)and supporting data of Tables of Prediction of Yield and Nitrogen-Use Efficiency by Using Consumer-Grade Unmanned Aerial Vehicle Multispectral Images of Winter Wheat.<em> </em>However, the artical has not published. Data is available upon request.</p> <p>If you need anything, please don't hesitate to contact me(liujk@ahstu.edu.cn).</p>
Casa Malpais Aerial Survey - Decimated
A digital model of the Village of Casa Malpais. One of the most unique ancient places in the Southwestern Culture Area with strong ancestral times to the Pueblo of Zuni as well as ties to Hopi and Acoma. People probably lived in this place from about ad 1150 to 1350, when the place was left to the ancients who still reside at this sacred place to this day. Casa Malpais is open to guided tours, which start at the Casa Malpais Musuem in the Springerville Heritage Center, 418 E Main St, Springerville, AZ. Be sure to call the museum at 928-333-2123 to confirm tour availability. This model has been squeezed down to 5% of the available data in order to fit on the Skecthfab Server. Source: Objaverse 1.0 / Sketchfab
Gussage St Michael 10 Aerial 2016
Gussage St Michael 10 Neolithic long barrow, Dorset. On Environment Agency Lidar DSM. Contains public sector information licensed under the Open Government Licence v3.0 Source: Objaverse 1.0 / Sketchfab
Land Cover Aerial Imagery (LICAID) dataset for semantic segmentation
<p><strong>Dataset Highlights:</strong></p> <ul> <li><strong>Title:</strong> Land Cover Aerial Imagery Dataset (LICAID)</li> <li><strong>Focus Area:</strong> Franciacorta wine-growing region, Lombardy, Italy</li> <li><strong>Data Source:</strong> Satellite imagery from Google Earth Pro</li> <li><strong>Classes and Descriptions:</strong> <ol> <li><strong>Grasslands:</strong> Habitats dominated by grasses, with few or no trees, found in various climates from tropical to temperate regions.</li> <li><strong>Arable Land:</strong> Land predominantly used for growing crops.</li> <li><strong>Herb-dominated Habitats:</strong> Areas where non-woody plants (herbs) are the dominant vegetation, including meadows, prairies, marshes, and wetlands.</li> <li><strong>Hedgerows:</strong> Linear strips of vegetation consisting of shrubs, small trees, and grasses, often used to mark boundaries or provide wildlife habitat in agricultural landscapes.</li> <li><strong>Vineyards:</strong> Agricultural landscapes cultivated specifically for growing grapevines, typically for wine production.</li> <li><strong>Tree-dominated Man-made Habitats:</strong> Human-modified landscapes where trees are the predominant vegetation, such as urban parks, orchards, and landscaped gardens.</li> <li><strong>Olea europaea Groves:</strong> Groves or orchards of olive trees, primarily cultivated for the production of olives and olive oil, commonly found in Mediterranean regions.</li> </ol> </li> </ul> <p><strong>gy:</strong></p> <ol> <li> <p><strong>Data Acquisition:</strong></p> <ul> <li>18 orthophoto tiles manually selected from Franciacorta.</li> <li>Satellite imagery and corresponding shape files acquired from Google Earth Pro.</li> <li>Georeferencing of imagery using ArcGIS software.</li> </ul> </li> <li> <p><strong>Data Preparation:</strong></p> <ul> <li>Segmentation using multiresolution segmentation in eCognition software.</li> <li>Validation of segmented images by a plant expert using QGIS software.</li> <li>Manual annotation of seven land cover classes.</li> </ul> </li> </ol>
Figure 1 from: Kokanova-Nedialkova Z, Nedialkov P (2021) Validated UHPLC-HRMS method for simultaneous quantification of flavonoid contents in the aerial parts of Chenopodium bonus-henricus L. (wild spinach). Pharmacia 68(3): 597-601. https://doi.org/10.3897/pharmacia.68.e69781
Figure 1 Chenopodium bonus-henricus L.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.