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Dataset results
586 results for “March”
SHIFT: HyTES L1 Brightness Temperature, March 23 2022
This dataset holds Level 1 (L1) brightness temperature data collected by the Hyperspectral Thermal Emission Spectrometer (HyTES) instrument. This imagery was acquired as part of the Surface Biology and Geology High-Frequency Time Series (SHIFT) campaign on March 23, 2022. The SHIFT campaign generated precise, high-frequency data on plant communities for nearly 1,656 square kilometers across Santa Barbara County, California, US, and the nearby ocean. HyTES is a compact image spectrometer that acquires data in 256 spectral bands between 7.5 and 12 micrometers; it was deployed on a Twin Otter aircraft. The SHIFT campaign sought to demonstrate the joint use of both VSWIR and thermal infrared (TIR) data. TIR data are used to measure land surface temperature (LST), which informs models of water flux from land surface through processes such as evapotranspiration. LST is sensitive to solar heat gains and local cooling effects due to evaporative cooling. The HyTES instrument measures TIR radiances that can be used to derive LST, emissivity and Level 3 products such as latent heat flux and detection of air pollution sources. The HyTES data are provided in HDF5 format and include 91 flight scenes. The data are not projected, but georeferencing information for each pixel are provided in the HDF5 and a separate ENVI file for each flight scene. In addition, the flight scene boundaries and an overlay image are provided in Keyhole Markup Language (KML) along with a quicklook image and spectral response data.
SHIFT: HyTES L2 Geolocated Land Surface Temperature and Emissivity, March 23 2022
This dataset holds Level 2 (L2) data for surface emissivity and land surface temperature (LST) collected by the Hyperspectral Thermal Emission Spectrometer (HyTES) instrument. This imagery was acquired as part of the Surface Biology and Geology High-Frequency Time Series (SHIFT) campaign on March 23, 2022. The SHIFT campaign generated precise, high-frequency data on plant communities for nearly 1,656 square kilometers across Santa Barbara County, California, US, and the nearby ocean. HyTES is a compact image spectrometer that acquires data in 256 spectral bands between 7.5 and 12 micrometers; it was deployed on a Twin Otter aircraft. The SHIFT campaign sought to demonstrate the joint use of both VSWIR and thermal infrared (TIR) data. TIR data are used to measure land surface temperature (LST), which informs models of water flux from land surface through processes such as evapotranspiration. LST is sensitive to solar heat gains and local cooling effects due to evaporative cooling. The HyTES instrument measures TIR radiances that can be used to derive LST, emissivity and Level 3 products such as latent heat flux and detection of air pollution sources. The HyTES data are provided in HDF5 format and include 91 flight scenes. In addition, overlay images for emissivity and LST are provided in compressed Keyhole Markup Language (KMZ) along with a quicklook image.
MASTER: Airborne Science, California-Nevada, March, 2000
This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during five flights aboard a DOE B-200 aircraft over California and Nevada, U.S., on 2000-03-10 to 2000-03-14. This deployment was coordinated by the U.S. Department of Energy's Remote Sensing Laboratory (RSL) located at Nellis Air Force Base near Las Vegas, Nevada. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 20-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.
MASTER: Costa Rica Airborne Research and Technology Applications, March, 2003
This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during 14 flights aboard a NASA WB-57 aircraft over Texas, U.S., Gulf of Mexico, and Costa Rica on 2003-03-06 to 2003-03-29. The CARTA-2003 project was a collaborative effort between the Centro Nacional de Alta Tecnologia (CENAT) of Costa Rica and NASA. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 30-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file
Microarray result of human skin derived from normal, atopic dermatitis and atopic march patients
GEO Series GSE146352. Homo sapiens. 6 samples. Type: Expression profiling by array.
L1000 Connectivity Map perturbational profiles from Broad Institute LINCS Center for Transcriptomics LINCS Pilot PHASE I (n=1,319,138; updated March 03, 2017)
GEO Series GSE92742. Homo sapiens. 0 samples. Type: Expression profiling by array.
Active Apartments on Airbnb in Vienna March 2020
<p>Number of apartments listed on Airbnb in general and number aparments that can be considered as active (= at last one review in the last year or at least one bookable day in the upcoming year) in Vienna in March 2020. Data generated from <a href="http://insideairbnb.com">insideairbnb.com</a> using the software from:<a href="https://doi.org/10.5281/zenodo.3737914"> https://doi.org/10.5281/zenodo.3737914</a></p>
TESS-MARCH-2020
<p>Measurements taken by the European Photometer Network (Project STARS4ALL). March 2020</p>
EPA Headquarters 395ft - RGB (March 15, 2023)
<p>This orthomosaic of the Environmental Protection Agency (EPA) Headquarters in Dededo, Guam was created from 135 images taken on March 15 2023, at 395 ft AGL, with a DJI P1 Sensor mounted to a DJI Matrice 300 UAV. The mission was planned using the UgCS application and post-processed using DroneDeploy. </p> <p>This project was made possible through funding by the following grant(s): NASA Guam EPSCoR (80NSSC22M0052), NASA Guam Space Grant (80NSSC20M0039 / UH Subaward: MA1550), and PI-CASC (G19AC00087)."</p>
EPA Headquarters 200ft- RGB (March 15, 2023)
<p>This orthomosaic of the Environmental Protection Agency (EPA) Headquarters in Dededo, Guam was created from 505 images taken on March 15 2023, at 200 ft AGL, with a DJI P1 Sensor mounted to a DJI Matrice 300 UAV. The mission was planned using the UgCS application and post-processed using DroneDeploy. </p> <p>This project was made possible through funding by the following grant(s): NASA Guam EPSCoR (80NSSC22M0052), NASA Guam Space Grant (80NSSC20M0039 / UH Subaward: MA1550), and PI-CASC (G19AC00087)."</p>
Pago Bay Rhino Beetles - RGB (March 29, 2023)
<p>This orthomosaic of Pago Bay, Guam was created from 196 images taken on March 29 2023, at 400 ft AGL, with a DJI P1 Sensor mounted to a DJI Matrice 300 UAV. The mission was planned using the UgCS application and post-processed using DroneDeploy. </p> <p>This project was made possible through funding by the following grant(s): NASA Guam EPSCoR (80NSSC22M0052), NASA Guam Space Grant (80NSSC20M0039 / UH Subaward: MA1550), and PI-CASC (G19AC00087)."</p>
Ugum - RGB (March 23, 2023)
<p>This orthomosaic of Ugum Watershed in Talofofo, Guam was created from 519 images taken on March 23 2023, at 400 ft AGL, with a DJI P1 Sensor mounted to a DJI Matrice 300 UAV. The mission was planned using the UgCS application and post-processed using DroneDeploy. </p> <p>This project was made possible through funding by the following grant(s): NASA Guam EPSCoR (80NSSC22M0052), NASA Guam Space Grant (80NSSC20M0039 / UH Subaward: MA1550), and PI-CASC (G19AC00087)."</p>
Rhino Beetles 100ft - -RGB (March 29, 2023)
<p>This orthomosaic of Pago Bay, Guam was created from 1956 images taken on March 29 2023, at 100 ft AGL, with a DJI P1 Sensor mounted to a DJI Matrice 300 UAV. The mission was planned using the UgCS application and post-processed using DroneDeploy. </p> <p>This project was made possible through funding by the following grant(s): NASA Guam EPSCoR (80NSSC22M0052), NASA Guam Space Grant (80NSSC20M0039 / UH Subaward: MA1550), and PI-CASC (G19AC00087)."</p>
Crowd-sourced collected building attributes of the Colouring Dresden project (from 06 March 2023 to 01 October 2023)
<p><strong>Abstract</strong></p> <p>The building attribute data was collected by citizens as part of the citizen science project “Colouring Dresden”. Main goal was to collect information about buildings (like building age, usage, number of storeys, roof shape etc.) in an interactive online map. Different action formats (like dialogue series, presentations, mapathons, hackathons, and monthly meetings) were organised to bring citizens into action and discuss building-related topics. Focus was the sustainable construction of buildings and the question how good current buildings of the city are prepared for natural catastrophes like floods, heavy rain incidents or heat stress. The project period was from October 2022 to September 2023 and the mapping platform was launched in March 2023.</p> <p>Project page: <a href="https://colouring.dresden.ioer.info/">https://colouring.dresden.ioer.info/</a></p> <p>The project is part of the international research network “Colouring Cities Research Programme” (CCRP) and the first local project in Germany. Colouring Dresden is currently coordinating the European Hub of CCRP.</p> <p>The project was led by Leibniz Institute of Ecological Urban and Regional Development Dresden, Germany in cooperation with:</p> <p>- <strong>Sächsische Landesbibliothek - Staats- und Universitätsbibliothek Dresden (SLUB) - Regionalportal Saxorum</strong></p> <p>- <strong>Bund Deutscher Architektinnen und Architekten (BDA</strong>)</p> <p>- <strong>Zentrum für Baukultur Sachsen (ZfBK)</strong></p> <p>- <strong> Technische Sammlungen Dresden (TSD) / DLR_School_Lab TU Dresden</strong></p> <p>- <strong>Zentralbibliothek der Städtische Bibliotheken Dresden (SBD)</strong></p> <p> </p> <p><strong>Data description</strong></p> <p>The data contains several files:</p> <p>- <strong>building_atributes_geometry_20231001.gpkg</strong>: building geometries and building attributes in Geopackage file format</p> <p>- <strong>building_attributes.csv</strong>: building attributes</p> <p>- <strong>building_verification.csv</strong>: building verification data (crowd-sourced)</p> <p>- <strong>edit_history.csv</strong>: edit history of collected building_attributes</p> <p>- <strong>README.md</strong></p> <p> </p> <p><strong>Building geometries:</strong></p> <p><strong>Data source</strong>: 3D-Stadtmodell (3D city model) LoD2, Open Data Dresden</p> <p><strong>URL</strong>: <a href="https://daten.dresden.de/SONST/Datenbeschreibung_3D_Gebaeude_Dresden_OpenData.pdf">https://daten.dresden.de/SONST/Datenbeschreibung_3D_Gebaeude_Dresden_OpenData.pdf</a></p> <p><strong>Contact</strong>: opendata@dresden.de</p> <p><strong>Data license</strong>: Data license Germany – Attribution – Version 2.0 <a href="https://www.govdata.de/dl-de/by-2-0">https://www.govdata.de/dl-de/by-2-0</a>., Attribution: “Datenquelle: Landeshauptstadt Dresden, dl-de/by-2-0, opendata.dresden.de”</p> <p><strong>Spatial reference</strong>: WGS 84 / Web Mercator (EPSG: 3857)</p> <p><strong>Spatial extent</strong>: City of Dresden, Germany</p> <p><strong>Number of buildings</strong>: 135598</p> <p><strong>Completeness</strong>: Almost complete. Recently built buildings are not included.</p> <p><strong>Positional accuracy</strong>: Building footprints based on official cadastre data (ALKIS)</p> <p><strong>Up-to-dateness</strong>: Data is from 4<sup>th</sup> of May, 2023. Recently built buildings are not included.</p> <p> </p> <p> </p> <p><strong>Building attributes:</strong></p> <p><strong>(</strong>Including<strong> building verification </strong>and<strong> edit history)</strong></p> <p><strong>Data source:</strong> crowd-sourced collected building attributes from citizen science project “Colouring Dresden”, led by Leibniz Institute of Ecological Urban and Regional Development Dresden, Germany</p> <p><strong>Data collection:</strong> most attributes were collected by citizens using Citizen Science platform “Colouring Dresden”. Some attributes (address, centroid or identifier of external datasets like OpenStreetMap, Wikipedia or Wikidata) were linked automated.</p> <p><strong>URL:</strong> <a href="https://colouring.dresden.ioer.info/">https://colouring.dresden.ioer.info/</a></p> <p><strong>Contact:</strong> Dr Robert Hecht, <a href="https://www.ioer.de/institut/beschaeftigte/hecht">https://www.ioer.de/institut/beschaeftigte/hecht</a></p> <p><strong>Data license:</strong> Open Data Commons Open Database License (ODbL), Attribution: “Colouring Dresden contributors”, <a href="https://opendatacommons.org/licenses/odbl/">https://opendatacommons.org/licenses/odbl/</a></p> <p><strong>Spatial extent:</strong> City of Dresden, Germany</p> <p><strong>Number of buildings:</strong> 135598</p> <p><strong>Completeness: </strong></p> <p>Completeness of collected building attributes differs and depends on mapping activities of the Citizen Scientists from March to September in 2023. Completeness of automated linked attributes is 47.6% or more. Completeness of crowd-sourced attributes is up to 5.3%.</p> <p>100.0% building_id; ref_toid; location_latitude; location_longitude; revision_id; size_height_apex</p> <p>47.6% location_number; location_street; location_postcode; location_town</p> <p>5.3% building_attachment_form</p> <p>2.0% is_domestic</p> <p>1.1% size_storeys_core</p> <p>1.0% architectural_style; architectural_style_source; use_building_current</p> <p>0.6% size_storeys_attic; size_roof_shape</p> <p>0.3% use_building_origin</p> <p>And more attributes</p> <p><strong>Up-to-dateness:</strong> the data extract is from 1<sup>st</sup> of October, 2023 and includes the collecting period from March to September in 2023.</p>
As Gadao - RGB (March 6, 2024)
<p>This orthomosaic of AsGadao was created from 871 images taken on March 6 2024, at 400 ft AGL, with a M350. The mission was planned using the DJI Pilot application and post-processed using DroneDeploy. </p> <p>This project was made possible through funding by the following grant(s): NASA Guam EPSCoR (80NSSC22M0052), NASA Guam Space Grant (80NSSC20M0039 / UH Subaward: MA1550), and PI-CASC (G19AC00087)."</p>
As Gadao Burn Site - RGB (March 21, 2024)
<p>This orthomosaic of As Gadao was created from 816 images taken on March 21 2024, at 400 ft AGL, with a M350. The mission was planned using the DJI Pilot application and post-processed using DroneDeploy. </p> <p>This project was made possible through funding by the following grant(s): NASA Guam EPSCoR (80NSSC22M0052), NASA Guam Space Grant (80NSSC20M0039 / UH Subaward: MA1550), and PI-CASC (G19AC00087)."</p>
Calibration of Nonlinear Rheology Parameters in the Salt Lake Basin from the March 18, M5.7 Magna, Utah, Earthquake Sequence Records
<p>Simulated time series and scripts to extract intensity measures described in the U.S. Geological Survey (USGS) technical report (under USGS award number G22AP00033).</p> <p>The simulation results are located "<a href="../api/records/10892430/draft/files/time-series-all.zip/content" target="_blank" rel="noopener noreferrer">time-series-all.zip</a>" with folder names defined as in the table-of-contents shown in the additional descriptions, all waveform data are in ASCII format, where the first column is time in seconds from the initial time of the event, the second column is velocity in m/s. The python scripts used to calculate intensity measurements based on the time series are located in "<a href="../api/records/10892430/draft/files/itensity-measures-calculation.zip/content" target="_blank" rel="noopener noreferrer">itensity-measures-calculation.zip</a>", with package requirements listed within each script.</p>
Ugum - RGB (March 26 2024)
<p>This orthomosaic of Ugum Watershed in Talofofo, Guam was created from 922 images taken on March 26 2024, at 400 ft AGL, with a M350. The mission was planned using the DJI Pilot application and post-processed using DroneDeploy. </p> <p>This project was made possible through funding by the following grant(s): NASA Guam EPSCoR (80NSSC22M0052), NASA Guam Space Grant (80NSSC20M0039 / UH Subaward: MA1550), and PI-CASC (G19AC00087)."</p>
LPL5 - March 2021
<p>Measurements of LPL5 (Tejeda) in March 2021</p> <p>Tejeda, Gran Canaria</p> <p>Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL5">info</a></p>
Community Meeting of the Sensitive Data Interest Group: March 2022
<p>This is the recording from the RDA Sensitive Data Interest Group community meeting held March 30, 08:00 UTC, 2022. More information about the series can be found here: https://www.rd-alliance.org/group/sensitive-data-interest-group/post/2022-sensitive-data-community-meeting-series-register-now</p>
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.