Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
405
datasets available to search
ShareScore release 0.9.0
Dataset results
405 results for “flight data”
Data from: Nocturnal flight-calling behaviour predicts vulnerability to artificial light in migratory birds
Understanding interactions between biota and the built environment is increasingly important as human modification of the landscape expands in extent and intensity. For migratory birds, collisions with lighted structures are a major cause of mortality, but the mechanisms behind these collisions are poorly understood. Using 40 years of collision records of passerine birds, we investigated the importance of species' behavioral ecologies in predicting rates of building collisions during nocturnal migration through Chicago, IL and Cleveland, OH, USA. We found that use of nocturnal flight calls is an important predictor of collision risk in nocturnally migrating passerine birds. Species that produce flight calls during nocturnal migration collided with buildings more than expected given their local abundance, whereas those that do not use such communication collided much less frequently. Our results suggest that a stronger attraction response to artificial light at night in species that produce flight calls may mediate these differences in collision rates. Nocturnal flight calls likely evolved to facilitate collective decision-making during navigation, but this same social behavior may now exacerbate vulnerability to a widespread anthropogenic disturbance. Our results also suggest that social behavior during migration may reflect poorly-understood differences in navigational mechanisms across lineages of birds.
Data from:Inferring flight parameters of Mesozoic avians through multivariate analyses of forelimb elements in their living relatives
Our knowledge of the diversity, ecology, and phylogeny of Mesozoic birds has increased significantly during recent decades, yet our understanding of their flight competence remains poor. Wing loading (WL) and aspect ratio (AR) are two aerodynamically relevant parameters, as they relate to energy costs of aerial locomotion and flight maneuverability. They can be calculated in living birds (i.e., Neornithes) from body mass (BM), wingspan (B) and lift surface (SL). However, the estimates for extinct birds can be subject to biases from statistical issues, phylogeny, locomotor adaptations, and diagenetic compaction. Here we develop a sequential approach for generating reliable multivariate models that allow estimating measurements necessary to determine WL and AR in the main clades of non-neornithine Mesozoic birds. The strength of our predictions is supported by the use of those variables that show similar scaling patterns in modern and stem taxa (i.e., non-neornithine birds), and the similarity of our predictions with measurements obtained from fossils preserving wing outlines. In addition, although our WL and AR values are based on estimates (BM, B, and SL) that have an associated error, there is no cumulative error in their calculation, and both parameters show low prediction errors. Therefore we present the first taxonomically broad, error-calibrated estimation of these two important aerodynamic parameters in non-neornithine birds. Such estimates show that the WL and AR of the non-neornithine birds here analyzed fall within the range of variation of modern birds (i.e., Neornithes). Our results indicate that most modern flight modes (e.g., continuous flapping, flap and gliding, flap and bounding, thermal soaring) were possible for the wide range of non-neornithine avian taxa; we found no evidence for the presence of dynamic soaring among these early birds.
Flight data for Severe Typhoon Koinu
<p>Probe data and dropsonde data collected for tropical cyclone Koinu</p>
Popular flight costs and emissions data
Open the record for dataset details and reuse information.
Data from: Flight is the key to postprandial blood glucose balance in the fruit bats Eonycteris spelaea and Cynopterus sphinx
Open the record for dataset details and reuse information.
Data from: Preparation for flight: pre-fledging exercise time is correlated with growth and fledging age in burrow-nesting seabirds
Open the record for dataset details and reuse information.
Data from:Inferring flight parameters of Mesozoic avians through multivariate analyses of forelimb elements in their living relatives
Open the record for dataset details and reuse information.
Data from: Nocturnal flight-calling behaviour predicts vulnerability to artificial light in migratory birds
Open the record for dataset details and reuse information.
IceBridge Sigma Space Lidar L0 Raw Time-of-Flight Data, Version 1
This data set contains raw time-of-flight measurements for Antarctica and Greenland acquired by the Sigma Space Lidar. The data were collected by scientists working on the Investigating the Cryospheric Evolution of the Central Antarctic Plate (ICECAP) project, which is funded by the National Science Foundation (NSF) and the Natural Environment Research Council (NERC), with additional support from NASA Operation IceBridge.
IceBridge Sigma Space Prototype L0 Raw Time-of-Flight Data, Version 1
This data set contains time-of-flight data captured over Antarctica using the Sigma Space Photon Counting Lidar Prototype instrument. The data were collected by scientists working on the Investigating the Cryospheric Evolution of the Central Antarctic Plate (ICECAP) project, which is funded by the National Science Foundation (NSF) and the Natural Environment Research Council (NERC), with additional support from NASA Operation IceBridge.
Flight Crew Physiological Data for Crew State Monitoring
This physiological data was collected from pilot/copilot pairs in and out of a flight simulator. It was collected to train machine-learning models to aid in the detection of pilot attentive states. The benchmark training set is comprised of a set of controlled experiments collected in a non-flight environment, outside of a flight simulator. The test set (abbreviated LOFT = Line Oriented Flight Training) consists of a full flight (take off, flight, and landing) in a flight simulator. The pilots experienced distractions intended to induce one of the following three cognitive states: Channelized Attention (CA) is the state of being focused on one task to the exclusion of all others. This is induced in benchmarking by having the subjects play an engaging puzzle-based video game. Diverted Attention (DA) is the state of having one’s attention diverted by actions or thought processes associated with a decision. This is induced by having the subjects perform a display monitoring task. Periodically, a math problem showed up which had to be solved before returning to the monitoring task. Startle/Surprise (SS) is induced by having the subjects watch movie clips with jump scares. For each experiment, a pair of pilots (each with its own crew ID) was recorded over time and subjected to the CA, DA, or SS cognitive states. The training set contains three experiments (one for each state) in which the pilots experienced just one of the states. For example, in the experiment labelled CA, the pilots were either in a baseline state (no event) or the CA state. The test set contains a full flight simulation during which the pilots could experience any of the states (but never more than one at a time). Each sensor operated at a sample rate of 256 Hz. Please note that since this is physiological data from real people, there will be noise and artifacts in the data.
Data from NASA Langley Airborne Lidar flights.
Data from the 1982 NASA Langley Airborne Lidar flights following the eruption of El Chichon beginning in July 1982 and continuing to January 1984. Data in ASCII format.
CALIPSO Night Validation Flights High Spectral Resolution Lidar (HSRL-2) Data
The CALIPSO Night Validation Flights (CALIPSO-NVF) airborne deployment was conducted in August 2022 out of Bermuda. The goal was to conduct a series of nighttime underflights of the CALIPSO satellite with the NASA Langley High Spectral Resolution Lidar (HSRL-2). Airborne measurements from the NASA Langley HSRL-2 instrument are essential for verifying the calibration accuracy of the CALIPSO lidar and for acquiring information on aerosol optical properties used for its aerosol profile retrievals. By flying under the CALIPSO ground track, HSRL-2 provides an independent measurement of lidar attenuated backscatter with a higher signal-to-noise ratio. To obtain this important validation dataset, the HSRL-2 was flown on board the LaRC B-200 King Air as CALIPSO passed within range of the aircraft. The western Atlantic Ocean was selected for CALIPSO-NVF to allow unobstructed, 45-minute flights along the satellite ground track. Five nighttime underflights were executed in total – four in cloud-free skies on August 7, 10, 12, and 17th, yielding ideal data from both instruments for calibration validation. The fifth flight on August 18th targeted measurements beneath cirrus to assess the accuracy of CALIPSO aerosol retrievals through high clouds at night, an important but previously unexplored validation target. Total research flight time was 17.7 hours, sampling 2,200 km along the CALIPSO ground track.
CAMEX-4 NOAA WP-3D FLIGHT LEVEL DATA V1
The CAMEX-4 NOAA WP-3D Flight Level Data dataset used the NOAA WP-3D Orion aircraft, which collects numerous in-situ meteorological measurements along with navigation and aircraft state parameters during each flight. CAMEX-4 focused on the study of tropical cyclone (hurricane) development, tracking, intensification, and landfalling impacts using NASA-funded aircraft and surface remote sensing instrumentation. The WP-3D data are encoded on 8mm tapes in what is called the 'AOC Standard Tape Format'. Examples of meteorological data include total temperature, dew point, liquid water content and dynamic pressure (from several sensors). Aircraft parameters include angle of attack, airspeed, and slip angle. For further information and to obtain this data, please contact GHRC at support-ghrc@earthdata.nasa.gov
First ISCCP Regional Experiment (FIRE) Atlantic Stratocumulus Transition Experiment (ASTEX) SOFIA ARAT Fokker F27 Aircraft Flight Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to improve the basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution cloud data. To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.SOFIA (Surface of the Ocean, Fluxes and Interaction with the Atmosphere) is a research program carried out by French groups from the Centre de Recherches en Physique de l'Environnement (CRPE), Laboratoire l'Aerologie (LA)-Toulouse, Centre de Meteorologie Marine (CMM)-Brest, Institut Francais de Rechercher sur la Mer (IFREMER)-Brest, Service d'Aeronomie-Paris, and Laboratoire de Meteorologie Dynamique (LMD)-Palaiseau with cooperation from Centre National de Recherche Meteorologique (CNRM)-Toulouse. The scientific objective of SOFIA during ASTEX was the study of energy transfer (heat, humidity and momentum fluxes) between the sea surface and the atmospheric boundary layer at scales ranging from the local scale to the mesoscale (50 km). The general concept of the program was to develop a measurement strategy based on nested boxes in which instrumentation would be used to estimate and quantify fluxes. These instruments, from which flux estimates at different scales would be measured, were used in connection with satellite measurements to understand and, hence, to validate the satellite integration of fluxes, particularly in the presence of mesoscale oceanic and atmospheric structures responsible for spatial inhomogeneity of fluxes. The FOKKER F27 aircraft with flux measurement package and the airborne Lidar Leandre was used during ASTEX. The FOKKER 27 ARAT capabilities were as follows: * Turbulence measurements of wind, temperature and moisture. Fast response sensors located on a nose boom 5m long, which measured - attack and sideslip angles by mobile vanes and by a five hole probe (Rosemound 858). - true airspeed by a Pitot probe - temperature by a fast response INSU probe - humidity by a Lyman-alpha humidity meter * Mean state sensors - Rosemount temperature probe - Reverse-flow temperature probe - General Eastern dew point sensor * Aerosols and cloud microphysics - 1-D drop size measurements from 0-6000 microns by four Knollenberg sensors - 2-D sensor OAP 2DC for drop sizes between 25 and 800 microns * Liquid water content - Johnson-Williams sensors * Radiative measurements, up- and downward - Longwave (14-40 microns) Eppley radiometers - Shortwave (0.2-2.8 microns) Eppley radiometers - Radiances (7.8-14 microns) Barnes PRT5 radiometers * Chemical measurements(isokinetic veins) * Pointint backscatter lidar (Leandre) * Directional reflectances meausrements (POLDER- Polarized Direct Reflectance)
TOLNet NASA Goddard Space Flight Center Data
TOLNet_GSFC_Data is the lidar data collected by the Tropospheric Ozone (TROPOZ) lidar at the Goddard Space Flight Center (GSFC) as part of the Tropospheric Ozone Lidar Network (TOLNet). Data collection for this product is ongoing.In the troposphere, ozone is considered a pollutant and is important to understand due to its harmful effects on human health and vegetation. Tropospheric ozone is also significant for its impact on climate as a greenhouse gas. Operating since 2011, TOLNet is an interagency collaboration between NASA, NOAA, and the EPA designed to perform studies of air quality and atmospheric modeling as well as validation and interpretation of satellite observations. TOLNet is currently comprised of seven Differential Absorption Lidars (DIAL). Each of the lidars are unique, and some have had a long history of ozone observations prior to joining the network. Five lidars are mobile systems that can be deployed at remote locations to support field campaigns. This includes the Langley Mobile Ozone Lidar (LMOL) at NASA Langley Research Center (LaRC), the Tropospheric Ozone (TROPOZ) lidar at the Goddard Space Flight Center (GSFC), the Tunable Optical Profile for Aerosol and oZone (TOPAZ) lidar at the NOAA Chemical Sciences Laboratory (CSL) in Boulder, Colorado, the Autonomous Mobile Ozone LIDAR instrument for Tropospheric Experiments (AMOLITE) lidar at Environment and Climate Change Canada (ECCC) in Toronto, Canada, and the Rocket-city O3 Quality Evaluation in the Troposphere (RO3QET) lidar at the University of Alabama in Huntsville, Alabama. The remaining lidars, the Table Mountain Facility (TMF) tropospheric ozone lidar system located at the NASA Jet Propulsion Laboratory (JPL), and City College of New York (CCNY) New York Tropospheric Ozone Lidar System (NYTOLS) are fixed systems.TOLNet seeks to address three science objectives. The primary objective of the network is to provide high spatio-temporal measurements of ozone from near the surface to the top of the troposphere. Detailed observations of ozone structure allow science teams and the modeling community to better understand ozone in the lower-atmosphere and to assess the accuracy and vertical resolution with which geosynchronous instruments could retrieve the observed laminar ozone structures. Another objective of TOLNet is to identify an ozone lidar instrument design that would be suitable to address the needs of NASA, NOAA, and EPA air quality scientists who express a desire for these ozone profiles. The third objective of TOLNET is to perform basic scientific research into the processes create and destroy the ubiquitously observed ozone laminae and other ozone features in the troposphere. To help fulfill these objectives, lidars that are a part of TOLNet have been deployed to support nearly ten campaigns thus far. This includes campaigns such as the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission, the Korea United States Air Quality Study (KORUS-AQ), the Tracking Aerosol Convection ExpeRiment – Air Quality (TRACER-AQ) campaign, the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ), the Long Island Sound Tropospheric Ozone Study (LISTOS), and the Ozone Water–Land Environmental Transition Study (OWLETS).
GOES-R PLT ER-2 Flight Navigation Data
The GOES-R PLT ER-2 Flight Navigation Data dataset consists of multiple altitude, pressure, temperature parameters, airspeed, and ground speed measurements collected by the NASA ER-2 high-altitude aircraft for flights that occurred during the GOES-R Post Launch Test (PLT) field campaign. The GOES-R PLT airborne science field campaign took place between March 21 and May 17, 2017 in support of the post-launch product validation of the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM). ER-2 navigation data files in ASCII-IWG1 format are available for March 21, 2017 through May 17, 2017.
Zenodo flights data upload
This is my first upload from the REST API of the flights data csv dataset
MMS 1 Energetic Particle Detector, Energetic Ion Spectrometer (EPD-EIS) Pulse Height by Time of Flight, Level 2 (L2), Burst Mode, 0.605 s Data
Energetic Particle Detector (EPD), Energetic Ion Spectrometer (EIS) Pulse Height by Time of Flight, Level 2, Burst Survey, 0.605 s Data. The EIS provides ion composition measurements (protons versus oxygen ions) and angular distributions over the energy range from approximately 45 to 500 keV.
MMS 1 Hot Plasma Composition Analyzer (HPCA) Time of Flight, TOF, Counts, Level 2 (L2), Survey Mode, 0.625 s Data
Hot Plasma Composition Analyzer (HPCA) Time of Flight, TOF, Counts, Level 2, Survey 10 s Data. The MMS HPCA instruments measure the energy and composition of magnetospheric plasmas in the energy range from 1 eV to 40 keV. An electrostatic energy analyzer (ESA) that is optically coupled to a carbon-foil based Time-of-Flight (TOF) section comprises each HPCA. The basic HPCA data product is an array of counts for 5 ion species, at 63 energies, for each of 16 elevation anodes. Sixteen basic products, also called azimuths, are acquired every 10 s; half a spacecraft spin period nominally has 16 azimuths. The five ion species are protons (H+), alpha particles (He++), helium ions (He+), singly charged Oxygen (O+), and background counts.
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.