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4,404 results for “digits”
Data from: Digit ratio predicts the number of lifetime recruits in female collared flycatchers
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Data from: A survey of digitized data from U.S. fish collections in the iDigBio data aggregator
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Data from: Digit ratio (2D:4D) and prosocial behavior in economic games: no direct correlation with generosity, bargaining, or trust-related behaviors
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Data from: Examining community stability in the face of mass extinction in communities of digital organisms
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Digital Particle Image Velocimetry (DPIV) data on a hovering hawkmoth to determine the strength of the vortex loop
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Digital image correlation (DIC) measurement of contact stiffness
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Digital research data from: Biochar stability in a highly weathered sandy soil under four years of continuous corn production
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Anaheim, CA Digital Elevation Models
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Digital Elevation Model (AZ 7.5 - Minute)
7.5 Minute Digital Elevation Model for the state of Arizona. Digital Elevation Model (DEM) is the terminology adopted by the USGS to describe terrain elevation data sets in a digital raster form. The standard DEM consists of a regular array of elevations cast on a designated coordinate projection system. The DEM data are stored as a series of profiles in which the spacing of the elevations along and between each profile is in regular whole number intervals. The normal orientation of data is by columns and rows. Each column contains a series of elevations ordered from south to north with the order of the columns from west to east. The DEM is formatted as one ASCII header record (A-record), followed by a series of profile records (B-records) each of which include a short B-record header followed by a series of ASCII integer elevations per each profile. The last physical record of the DEM is an accuracy record (C-record). The DEM for 7.5-minute units correspond to the USGS 1:24000 scale topographic quadrangle map series for all of the United States and its territories. Each 7.5 minute DEM is based on 30- by 30-meter data spacing with Universal Transverse Mercator(UTM) projection. Each 7.5- by 7.5-minute block provides the same coverage as the standard USGS 7.5-minute map series.
Snow-Off Digital Terrain Model (DTM) from 2010 LiDAR for the Boulder Creek Critical Zone Observatory (CZO), Colorado
This 1m Digital Terrain Model (DTM) is a snow-off DTM derived from bare-ground Light Detection and Ranging (LiDAR) point cloud data from August 2010 for the Boulder Creek Critical Zone Observatory (CZO), near Boulder Colorado. This dataset is better suited for derived layers such as slope angle, aspect, and contours. The DTM was created from 1,375 LiDAR point cloud tiles subsampled from 10 points/m2 to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the Boulder Creek CZO and NCALM, both funded by the National Science Foundation (NSF). The DTM has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 598.92 km^2. The LiDAR point cloud data was acquired with an Optech Gemini Airborne Laser Terrain Mapper (ALTM) and mounted in a Piper Twin PA-31 Chieftain with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from four GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DTM surface was created by mosaicing and then kriging 0.5 x 1 km LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy is at least, but usually better than, 11 cm RMSE at 1 sigma and vertical accuracy is 5-30 cm RMSE at 1 sigma. The layer is available in IMAGINE format approx. 4 GB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum, with FGDC-compliant metadata. A shaded relief model was also generated. A similar layer, the Digital Surface Model (DSM), is a first-stop elevation layer. Accessory layers consist of index map layers for point cloud tiles and flight lines, each with detailed attribute information such as acquisition date and tile file name. The DTM is available through an unrestricted public license. Other LiDAR DSMs, DTMs, and point cloud data ava
BOREAS Daedalus TMS Level-0 Imagery: Digital Counts in BIL Format
The level-0 Daedalus TMS imagery, along with the other remotely sensed images, was collected to provide spatially extensive information about radiant energy over the primary BOREAS study areas. This information includes detailed land cover and biophysical parameter maps such as FPAR and LAI. Two flights of the Daedalus TMS instrument were made onboard the ER-2 aircraft on September 16 and 17, 1994. Companion files include (1) an image inventory listing to inform users of the images that are available and (2) example thumbnail images that may be viewed and the image data files downloaded using a convenient viewer utility.
Radarsat Antarctic Mapping Project Digital Elevation Model, Version 2
The high-resolution Radarsat Antarctic Mapping Project (RAMP) Digital Elevation Model (DEM) combines topographic data from a variety of sources to provide consistent coverage of all of Antarctica.
LBA-ECO LC-15 SRTM30 Digital Elevation Model Data, Amazon Basin: 2000
This dataset provides a subset of the SRTM30 Digital Elevation Model (DEM) elevation and standard deviation data for the Amazon Basin. SRTM30 is a near-global digital elevation model (DEM) comprising a combination of data from the Shuttle Radar Topography Mission (SRTM), flown in February, 2000, and the earlier U.S. Geological Survey's GTOPO30 data set. The SRTM30 resolution is 30 arc-sec or about 1 km. In processing the SRTM data, to combine with GTOPO30, the data were resampled from 3 arc-sec to 30 arc-sec. Provided here are the mean elevation and the standard deviation (STD) of the data points used in the averaging. The STD is thus an indication of topographic roughness useful in some applications.
PhenoCam Dataset v2.0: Vegetation Phenology from Digital Camera Imagery, 2000-2018
This data set provides a time series of vegetation phenological observations for 393 sites across diverse ecosystems of the world (mostly North America) from 2000-2018. The phenology data were derived from conventional visible-wavelength automated digital camera imagery collected through the PhenoCam Network at each site. From each acquired image, RGB (red, green, blue) color channel information was extracted and means and other statistics calculated for a region-of-interest (ROI) that delineates an area of specific vegetation type. From the high-frequency (typically, 30 minute) imagery collected over several years, time series characterizing vegetation color, including canopy greenness, plus greenness rising and greenness falling transition dates, were summarized over 1- and 3-day intervals.
BOREAS Level-0 AOCI Imagery: Digital Counts in BIL Format
The level-0 AOCI imagery, along with the other remotely sensed images, was collected to provide spatially extensive information about radiant energy over the primary BOREAS study areas. The AOCI was the only remote sensing instrument flown with wavelength bands specific to the investigation of various aquatic parameters such as chlorophyll content and turbidity. Only one flight of the AOCI instrument was made onboard the ER-2 aircraft on 21-Jul-1994 over the SSA. Companion files include (1) an image inventory listing to inform users of the images that are available and (2) example thumbnail images that may be viewed and the image data files downloaded using a convenient viewer utility.
G-LiHT Digital Terrain Model V001
Goddard’s LiDAR, Hyperspectral, and Thermal Imager ([G-LiHT](https://gliht.gsfc.nasa.gov/)) mission utilizes 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 Digital Terrain Model data product (GLDTMT) is to provide LiDAR-derived bare earth elevation, aspect and slope on the EGM96 Geopotential Model. Scientists at NASA’s Goddard Space Flight Center began collecting data over locally-defined areas in 2011 and that the collection will continue to grow as aerial campaigns are flown and processed.GLDTMT data are processed as a raster data product (GeoTIFF) at a nominal 1 meter spatial resolution over locally-defined areas. A low resolution browse is also provided showing the digital terrain with a color map applied in JPEG format.
G-LiHT Digital Surface Model V001
Goddard’s LiDAR, Hyperspectral, and Thermal Imagery ([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 Digital Surface Model data product (GLDSMT) is to provide LiDAR-derived visualizations of elevation above bare earth. GLDSMT data is offered in multiple formats, including Digital Surface Model, Mean, Aspect, Rugosity, and Slope.GLDSMT data are processed as multiple raster data products (GeoTIFFs) at a nominal 1 meter spatial resolution over locally defined areas. A low resolution browse is also provided showing the digital surface model with a color map applied in PNG format.
ASTER Global Digital Elevation Model V003
The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) Version 3 (ASTGTM) provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator).The development of the ASTER GDEM data products is a collaborative effort between National Aeronautics and Space Administration (NASA) and Japan's Ministry of Economy, Trade, and Industry (METI). The ASTER GDEM data products are created by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was created from the automated processing of the entire [ASTER Level 1A](https://doi.org/10.5067/ASTER/AST_L1A.003) archive of scenes acquired between March 1, 2000, and November 30, 2013. Stereo correlation was used to produce over one million individual scene based ASTER DEMs, to which cloud masking was applied. All cloud screened DEMs and non-cloud screened DEMs were stacked. Residual bad values and outliers were removed. In areas with limited data stacking, several existing reference DEMs were used to supplement ASTER data to correct for residual anomalies. Selected data were averaged to create final pixel values before partitioning the data into 1 degree latitude by 1 degree longitude tiles with a one pixel overlap. To correct elevation values of water body surfaces, the ASTER Global Water Bodies Database ([ASTWBD](https://doi.org/10.5067/ASTER/ASTWBD.001)) Version 1 data product was also generated. The geographic coverage of the ASTER GDEM extends from 83° North to 83° South. Each tile is distributed in both a Cloud Optimized GeoTIFF (COG) and NetCDF4 format through NASA Earthdata Search and in standard GeoTIFF format through the LP DAAC Data Pool. Data are projected on the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each of the 22,912 tiles in the collection contain at least 0.01% land area. Provided in the ASTER GDEM product are layers for DEM and number of scenes (NUM). The NUM layer indicates the number of scenes that were processed for each pixel and the source of the data.While the ASTER GDEM Version 3 data products offer substantial improvements over Version 2, users are advised that the products still may contain anomalies and artifacts that will reduce its usability for certain applications. Known Issues* ASTER GDEM Version 3 tiles overlap by one pixel to the north, south, east, and west of the tile perimeter. In most cases the overlapping edge pixels have identical pixel values, but it is possible that in some instances values will differ. * ASTER GDEM Version 3 is considered to be void free except for Greenland and Antarctica.* Users are reminded that because there are known inaccuracies and artifacts in the dataset, to use the product with awareness of these limitations. The data are provided "as is" and neither NASA nor METI/Earth Resources Satellite Data Analysis Center (ERSDAC) will be responsible for any damages resulting from use of the data.Improvements/Changes from Previous Version* Expansion of acquisition coverage to increase the amount of cloud free input scenes from about 1.5 million in Version 2 to about 1.88 million scenes in Version 3.* Separation of rivers from lakes in the water body processing.* Minimum water body detection size decreased from 1 square kilometer (km²) to 0.2 km².
LBA-ECO LC-01 SRTM 90-Meter Digital Elevation Model, Northern Ecuadorian Amazon
This data set provides 90-meter resolution Digital Elevation Model data used in the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects. The topographic data were derived from Shuttle Radar Topography Mission (SRTM) C-band and X-band interferometric synthetic aperture radars (IFSARs) data that were acquired over 80% of Earth's land mass in February 2000. This data set includes one image in GeoTiff format that is a subset for the Northern Ecuadorian Amazon region.
ASTER Digital Elevation Model V004
The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (AST14DEM) product is generated using bands 3N (nadir-viewing) and 3B (backward-viewing) of an ASTER [Level 1A](https://doi.org/10.5067/ASTER/AST_L1A.004) image acquired by the Visible and Near Infrared (VNIR) sensor. The VNIR subsystem includes two independent telescope assemblies that facilitate the generation of stereoscopic data. The band 3 stereo pair is acquired in the spectral range of 0.78 and 0.86 microns with a base-to-height ratio of 0.6 and an intersection angle of 27.7 degrees. There is a time lag of approximately one minute between the acquisition of the nadir and backward images. For a better understanding, refer to the [diagram](https://lpdaac.usgs.gov/documents/301/ASTER_Along_Track_Imaging_Geometry.png) depicting the along-track imaging geometry diagram of the ASTER VNIR nadir and backward-viewing sensors. Improvements/Changes from Previous Versions* Radiometric Calibration Update: Version 4 applies Radiometric Calibration Coefficient Version 5 (RCC V5) to improve the radiometric accuracy of the raw DNs, based on research by [Tsuchida and others (2020)](https://doi.org/10.3390/rs12030427), published in Remote Sensing.
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.