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162 results for “interpolation”
Classification Data set: End-to-end Learning for Land Cover Classification using Irregular and Unaligned SITS by Combining Attention-Based Interpolation with Sparse Variational Gaussian Processes
<p>Classification data set (train, validation, test) from the study area based on 27 tiles on the south of the France. This dataset contains irregular and unaligned SITS with their corresponding masks. 9 different random sampling are provided. This data set was used to train mTAN-GP, mTAN-MLP, mTAN-LTAE and raw-LTAE.</p> <p>For further details see the pre-print article "End-to-end Learning for Land Cover Classification using Irregular and Unaligned SITS by Combining Attention-Based Interpolation with Sparse Variational Gaussian Processes ". This article is available : <a href="https://hal.science/hal-04112115">here</a>.</p> <p>The implementation of the models is available in the <a href="https://gitlab.cesbio.omp.eu/belletv/land_cover_southfrance_mtan_gp_irregular_sits">open source repository</a>.</p>
Popsyn Models for StarTrack Inference Interpolation
<p>The StarTrack simulation results and population synthesis results associated with our paper, Iteratively Comparing Gravitational-Wave Observations to the Evolution of Massive Stellar Binaries.</p> <p>We were recently accepted by PRD, and you can find an earlier manuscript on the arxiv: https://arxiv.org/abs/2303.05436</p> <p>The StarTrack version used to create these simulations is from October 5th, 2022.</p> <p>The summary is in the K_series.hdf5 file. This contains properties of each simulation, but not of individual binaries.</p> <p>There is a README.txt file included which describes the data.</p> <p>The StarTrack outputs are in the K0XXX.tar.gz format. Since Zenodo frowns on uploading hundreds of files, these are organized by which iteration they were generated in:<br> -it_0[a-o].tar.gz contain K0100-399 (in batches of roughly 20)<br> -it_1[a-e].tar.gz contain K0400-499 (in batches of roughly 20)<br> -it_2.tar.gz contains K0500-519<br> -it_3.tar.gz contains K0520-559<br> -it_4.tar.gz contains K0560-562<br> -it_5.tar.gz contains K0563-598<br> See Table 1 in the paper for more details about how these models were generated.</p> <p>The popsynth outputs are in the K0XXX_sfrX.hdf5 format.<br> All of the popsynth outputs used in the paper are in the sfr2_[a-e].tar.gz files (in batches of roughly 100).<br> sfr3 files were not used in the paper, but some of them are available.<br> <br> I provide the full set of binary properties for K0559 and K0565, for both sfr2 and sfr3 (K0XXX_sfrX_full.hdf5).</p> <p>Due to size limitations, we were unable to provide all of the K0XXX_sfr3.hdf5 or K0XXX_sfrX_full.hdf5 files, however the authors can make them available upon request (xevra86@gmail.com).</p>
Data from: A generalized distribution interpolated between the exponential and power law distributions and applied to pill bug (Armadillidium vulgare) walking data
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Synthetic model parameters for the comparison between an equivalent source and a minimum curvature interpolator of aeromagnetic data
<p>Parameters of the synthetic case used in Gavazzi et al. (submitted)[1]</p> <p>FILES (ASCII FORMAT)</p> <p>param.txt<br> General parameters of the geomagnetic field<br> Incl. inclination of the geomagnetic field<br> decl. declination of the geomagnetic field</p> <p>sources.txt<br> Localization and magnetization of the simulated sources<br> xs x-position of the sources (in m)<br> ys y-position of the sources (in m)<br> zs z-position of the sources (in m)<br> Ms magnetization of the sources (in A/m)</p> <p>profiles.txt<br> Localization of the simulated acquisition profiles<br> xx x-position of the data<br> yy y-position of the data<br> zz z-position of the data</p> <p>eqsources.txt<br> Localization and magnetization of the equivalent sources<br> xdeq x-position of the sources (in m)<br> ydeq y-position of the sources (in m)<br> zdeq z-position of the sources (in m)<br> JJ magnetization of the sources (in A/m)</p> <p>[1] Gavazzi, B., Bertrand, L., Munschy, M., Mercier de Lépinay, J., Diraison, M. & Géraud, Y. (submitted). On the use of aeromagnetism for geological interpretation part I: comparison of scalar and vector magnetometers for aeromagnetic surveys and an equivalent source interpolator for combining, gridding and transform fixed altitude and draping datasets, Journal of Geophysical Research: Solid Earth.</p>
Data from: Accelerating adaptive inverse distance weighting interpolation algorithm on a graphics processing unit
This paper focuses on designing and implementing parallel adaptive inverse distance weighting (AIDW) interpolation algorithms by using the graphics processing unit (GPU). The AIDW is an improved version of the standard IDW, which can adaptively determine the power parameter according to the data points' spatial distribution pattern and achieve more accurate predictions than those predicted by IDW. In this paper, we first present two versions of the GPU-accelerated AIDW, i.e. the naive version without profiting from the shared memory and the tiled version taking advantage of the shared memory. We also implement the naive version and the tiled version using two data layouts, structure of arrays and array of aligned structures, on both single and double precision. We then evaluate the performance of parallel AIDW by comparing it with its corresponding serial algorithm on three different machines equipped with the GPUs GT730M, M5000 and K40c. The experimental results indicate that: (i) there is no significant difference in the computational efficiency when different data layouts are employed; (ii) the tiled version is always slightly faster than the naive version; and (iii) on single precision the achieved speed-up can be up to 763 (on the GPU M5000), while on double precision the obtained highest speed-up is 197 (on the GPU K40c). To benefit the community, all source code and testing data related to the presented parallel AIDW algorithm are publicly available.
Conservative Interpolation Between Control-Volume Meshes: Application to Advection & Multiphase Flow
<p>Numerical Raw Data pertaining to the Publication linked to the DOI above. Uploaded as per Open Access requirements.</p> <p>The paper itself presents a general, higher order conservative and bounded interpolation for the dynamic and adaptive meshing of continuous and discontinuous control-volume fields. The method is discussed in detail and its robustness and applicability demonstrated through several examples, including advection dominated inertial flow as well multiphase porous media flow.</p> <p> </p>
Evaluating the Accuracy of Different Number of GEDI Footprints for Interpolation and Aboveground Biomass Estimation: A Case Study from Shangri-La
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Numerical data for Figures in Radio Science paper entitled "Flatness Error Compensation of Large Near-Field Scanning Frame Based on Cubic Spline Interpolation"
<p>Data format is EXCEL</p>
Interpolated PPNN data
<p>Data for <a href="https://github.com/slerch/ppnn">https://github.com/slerch/ppnn</a></p>
Probabilistic Hierarchical Interpolation and Interpretable Configuration for Flood Prediction
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Data supporting: Multiple input tangential interpolation-driven damage detection of a jet trainer aircraft
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Data from: Accelerating adaptive inverse distance weighting interpolation algorithm on a graphics processing unit
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IPRC/SOEST Aquarius V5.0 Optimally Interpolated Sea Surface Salinity 7-Day global Dataset
The IPRC/SOEST Aquarius OI-SSS v5 product is a level 4, near-global, 0.5 degree spatial resolution, 7-day, optimally interpolated salinity dataset based on version 5.0 of the AQUARIUS/SAC-D level 2 mission data. This is a PI led dataset produced at the International Pacific Research Center (IPRC) at the University of Hawaii (Manoa) School of Ocean and Earth Science and Technology. The optimal interpolation (OI) mapping procedure used to create this product corrects for systematic spatial biases in Aquarius SSS data with respect to near-surface in situ salinity observations and takes into account available statistical information about the signal and noise, specific to the Aquarius instrument. Bias fields are constructed by differencing in situ from Aquarius derived SSS fields obtained separately using ascending and descending satellite observations for each of the three Aquarius beams, and by removal of small-scale noise and low-pass filtering along-track using a two-dimensional Hanning window procedures prior to application of the OI algorithm. Additional enhancements for this new version of the product include: 1) The V5.0 (end-of mission) version of Aquarius Level-2 (swath) SSS data are used as input data for the OI SSS analysis. 2) The source of the first guess fields has changed from the APDRC Argo-derived SSS product to the average of four different in-situ based SSS products. 3) The bias correction algorithm has changed to adjust SSS retrievals for large-scale systematic biases on a repeat-track basis. 4) New, less restrictive thresholds are implemented to filter observations for land and ice contamination, thus improving coverage in the coastal areas and semi-enclosed seas. 5) Level-2 RFI masks for descending and ascending satellite passes are used to discard observations in specific geographic zones where excessive ascending-descending differences are observed due to contamination from undetected RFI. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath. The Aquarius polar orbit is sun synchronous at 657 km with a 6 pm, ascending node, and has a 7-Day repeat cycle.
OCO-3 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V11r (OCO3_L2_Met) at GES DISC
Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations.The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.
OCO-3 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V10r (OCO3_L2_Met) at GES DISC
Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations.The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.
Multi-Mission Optimally Interpolated Sea Surface Salinity Global Monthly Dataset V1
This is a level 4 product on a 0.25-degree spatial and monthly temporal grid. The product is the monthly mean of the level 4 OISSS dataset using three satellite missions: the Aquarius/SAC-D, Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) using Optimal Interpolation (OI) with a 7-day decorrelation time scale. This dataset is produced by the International Pacific Research Center (IPRC) of the University of Hawaii at Manoa in collaboration with the Remote Sensing Systems (RSS), Santa Rosa, California. More details can be found in the users guide and Addendum I to the product Technical Notes.
CERES Time-Interpolated TOA Fluxes, Clouds and Aerosols Monthly NOAA-20 Edition1B
The Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint One Degree (SSF1deg) Month provides monthly averages of regional constant meteorology temporally interpolated CERES Top of Atmosphere (TOA) fluxes, clouds derived from a co-located imager and aerosols on a 1-degree latitude and longitude grid. One-degree zonally and global averaged values for the parameters are also provided. This single satellite product uses the primary CERES instrument in cross-track mode. TOA fluxes are provided for clear-sky and all-sky conditions for longwave (LW), shortwave (SW), and window wavelength bands. The incoming daily solar irradiance is from the Solar Radiation and Climate Experiment (SORCE) and Total Solar Irradiance (TSI). The cloud properties are averaged for day and night (24-hour) and day-only periods. Cloud properties are stratified into four atmospheric layers (surface-700 hPa, 700 hPa - 500 hPa, 500 hPa - 300 hPa, 300 hPa - 100 hPa) and a total of all layers. The aerosols are averaged instantaneous values from the co-located imager.CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument (PFM) was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the EOS flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board EOS Aqua on May 4, 2002. The CERES instrument (FM5) was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The newest CERES instrument (FM6) was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite on November 18, 2017.
CERES SSF 1 degree Time-Interpolated TOA Fluxes, Clouds and Aerosols Monthly NPP Edition2A
CER_SSF1deg-Month_NPP-VIIRS_Edition2A is the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint One Degree (SSF1deg) Time-Interpolated Top-of-Atmosphere (TOA) Fluxes, Clouds and Aerosols Monthly Edition 2A data product, which was collected using the CERES-Flight Model 5 (FM5) and Visible-Infrared Imager-Radiometer Suite (VIIRS) instruments on the Suomi National Polar-orbiting Partnership (NPP) platform. Data collection for this product is in progress.CERES SSF1deg Month provides monthly averages of regional constant meteorology temporally interpolated CERES TOA fluxes, clouds derived from a co-located imager, and aerosols on a 1-degree latitude and longitude grid. One-degree zonally and global averaged values for the parameters are also provided. This single satellite product uses the primary CERES instrument in cross-track mode. TOA fluxes are provided for clear-sky and all-sky conditions for longwave (LW), shortwave (SW), and window (WN) wavelength bands. The incoming solar daily irradiance is from the Solar Radiation and Climate Experiment (SORCE) Total Solar Irradiance (TSI). The cloud properties are averaged for day and night (24-hour) and day-only periods. Cloud properties are stratified into four atmospheric layers (surface-700 hPa, 700 hPa, - 500 hPa, 500 hPa, - 300 hPa, 300 hPa, - 100 hPa) and a total of all layers. The aerosols are averaged instantaneous values from the co-located imager.CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument, the protoflight model (PFM), was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the Earth Observing System (EOS) flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board Earth Observing System (EOS) Aqua on May 4, 2002. The CERES FM5 instrument was launched on board the Suomi NPP satellite on October 28, 2011. The newest CERES instrument (FM6) was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now called NOAA-20, on November 18, 2017.
OCO-2 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V11r (OCO2_L2_Met) at GES DISC
Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass meteorological parameters interpolated from global assimilation model for each sounding.
CERES Time-Interpolated TOA Fluxes, Clouds and Aerosols Daily NOAA-20 Edition1B
The Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint One Degree (SSF1deg) Day provides daily averages of regional constant meteorology temporally interpolated CERES Top of Atmosphere (TOA) fluxes, clouds derived from a co-located imager and aerosols on a 1-degree latitude and longitude grid. This single satellite product uses the primary CERES instrument in cross-track mode. TOA fluxes are provided for clear-sky and all-sky conditions for longwave (LW), shortwave (SW), and window wavelength bands. The incoming daily solar irradiance is from the Solar Radiation and Climate Experiment (SORCE) and Total Solar Irradiance (TSI). The cloud properties are averaged for day and night (24-hour) and day-only periods. Cloud properties are stratified into four atmospheric layers (surface-700 hPa, 700 hPa - 500 hPa, 500 hPa - 300 hPa, 300 hPa - 100 hPa) and all layers. The aerosols are averaged instantaneous values from the co-located imager. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument (PFM) was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the EOS flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board EOS Aqua on May 4, 2002. The CERES instrument (FM5) was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The newest CERES instrument (FM6) was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite on November 18, 2017.
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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.