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1,255 results for “High-resolution”
Ship Plume Dispersion in Marseille Port: A High-Resolution CFD Visualization
<p><strong><u>Description</u></strong></p> <p>This video visualizes the results of a high-resolution Computational Fluid Dynamics (CFD) model applied to study ship plume dispersion in the passenger port of Marseille, France. The video focuses on a scenario where a small cruise/pleasure ship docked at the port turns on its main engines in preparation for departure, considering seaborn prevailing wind conditions.</p> <p>The visualization concentrates on two areas. The first is the area around La Major Cathedral, which is close to the waterfront. The second is a street canyon approximately 650 meters downwind of the ship's location. Due to the local urban layout, the plume becomes entrapped within this distant street canyon. Here, the spatial distribution of pollutants can vary even between neighboring floors of a single building. Finally, a rendered video of the plume dispersion is presented, where the urban landscape is visualized to make the dispersion more comprehensible for non-technical and non-scientific audiences.</p> <p>This video was previously published on YouTube at the following link: <a href="https://www.youtube.com/watch?v=HwLFTj1D4LU&ab_channel=SCIPPERProject" target="_blank" rel="noopener">YouTube</a>. </p> <p>All data used to create this video were made available through the EU Horizon 2020 project <a href="https://www.scipper-project.eu/">SCIPPER</a>.</p> <p>The SCIPPER project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement <a href="https://doi.org/10.3030/814893">Nr. 814893</a>. </p>
High-resolution figures of Amaral et al. 2024
<p>High-resolution figures of Amaral et al. 2024 "Expanding the Mesozoic record of early brachyceran fly larvae, including new larval forms with chimera-type morphologies" in Insects (MDPI).</p>
A regional high-resolution (1/12 degree) coupled ocean-ecosystem model (INCOIS-BIO-ROMS) output for Indian Ocean
<p>The dataset contains sea-surface temperature, sea-surface salinity, sea-surface dissolved inorganic carbon, sea-surface total alkalinity, sea-surface pH, and sea-surface partial pressure of CO2 for the Indian Ocean region. The data is available from 1980 to 2019 on a monthly time scale. Each of these data has a spatial resolution of 1/12º.</p>
Considerations for high-resolution regional meteorological wind modelling over complex terrain: a typhoon case study for assessing forestry damage (data)
<p>This is the experiment data.</p> <p>The Weather Research and Forecasting (WRF) model is a popular and easily used as a numerical weather prediction (NWP) model, but configuring WRF to produce accurate results can be time-consuming. This is especially so when simulating extreme events, over complex terrain, or at high resolutions. In this study, a strong wind event from Tropical Cyclone (TC) Thad in year 1981 was simulated at 200 m resolution over an experiment forest in a mountainous region of Hokkaido island, Japan. The simulation configuration is challenging, in order to cover a larger area to produce a TC with appropriate track and intensity, and at the same time to resolve the smallest domain of sub-km grid spacing with computational stability. A mixed nesting method was applied with two-way nesting up for the first three domains, followed a separate simulation over the smallest domain. The mixed method could produce 10 min wind speed distributions similar to that of the full simulation with two-way nesting of all four domains, if a 30-minute boundary update interval was used for the separate simulation. Mixed nesting improves the efficiency of the simulation process, since the larger phenomenon scale and smaller human impact scale can be tuned separately. </p>
Data for: Influence of Anomalous Ocean Heat Transport on the Extratropical Atmospheric Circulation in a High-Resolution Slab-Ocean Coupled Model
<p>This dataset, provided in NetCDF format, supports the research presented in the paper titled "Influence of Anomalous Ocean Heat Transport on the Extratropical Atmospheric Circulation in a High-Resolution Slab-Ocean Coupled Model." Please contact Dr. Sun (ltsun@rams.colostate.edu) if you have any questions.</p>
High-resolution harvester data for estimating rolling resistance and forest trafficability
<p>This study describes an extensive, high-resolution data on rolling resistance coefficient collected in a boreal forest landscape in Southern Finland during the non-frost period of 2021, covering roughly 50~km of harvester routes and used in the following study:</p> <p>Salmivaara, A., Holmström, E., Kulju, S., Ala-Ilomäki, J., Virjonen, P., Nevalainen, P., Heikkonen, J., and Launiainen, S. 2024.High-resolution harvester data for estimating rolling resistance and forest trafficability. European Journal of Forest Reseach. doi: 10.1007/s10342-024-01717-6</p> <p>The coordinates are in metric system, and the relative position between sites are maintained. However, they have been converted and do not refer to actual locations.</p> <p>Two datasets collected by a Ponsse Ergo harvester are available: </p> <p>1) All non-frost period of 2021, with 8m*8m grid means of rolling resistance ('grid mean rr'), along with grid mean longitudinal inclination of the machine ('grid mean pitch'), time, topographic wetness index ('twi') and binary indication whether a road is within 4m radius from the grid centerpoint ('roads'). </p> <p>2) Data including all 11 test sites with all first pass harvester machine data ('time', 'E_conv', 'N_conv', 'dtorq', 'drpm', 'peng', 'cooling', 'phydr', 'pwheels', 'v_ms', 'fmotive', 'slopeforce', 'normalforce', 'pitch', 'rr') and grid means of spatial data ('grid', 'grid mean rr', 'grid mean pitch', 'roads', 'site', 'slope_rad_terrain', 'bmroot_all'. 'c_bmroot_ratio', 'broadlv_rootbm_ratio', 'p_bmroot_ratio','s_bmroot_ratio', 'age', 'diameter', 'standheight', 'b_vol', 'b_pulp_vol', 'b_timber_vol', 's_vol', 's_pulp_vol', 's_timber_vol', 'p_vol', 'p_pulp_vol', 'p_timber_vol', 'broadlv_vol','broadlv_pulp_vol', 'broadlv_timber_vol', 'canopy_cov', 'broadlv_canopy_cov', 'ba', 'volume', 'dem', 'devMeanElev16', 'devMeanElev8', 'diffMeanElev8', 'erosion risk', 'tri', 'roughness_mag', 'roughness_scale', 'dtw00_5ha', 'dtw_01_0ha', 'dtw_04_0ha', 'dtw_10_0ha', 'twi', 'sat_deficit_doy', vol_moisture_doy, 'bare_rock_areas', 'lakes', 'streams', 'peat', 'topsoil', 'aspect', 'aspect_sin', 'aspect_cos', 'main_class_fertility_class_comb')</p> <p> </p>
Data used in: Utility of thermal remote sensing for evaluation of a high-resolution weather model in a city
<p>This dataset contains the processed data and analysis code used in the article:</p> <div>Hall, T.W., Blunn, L., Grimmond, S., McCarroll, N., Merchant, C.J., Morrison, W., et al. (2024) Utility of thermal remote sensing for evaluation of a high-resolution weather model in a city. <em>Quarterly Journal of the Royal Meteorological Society</em>, 150(760), 1771–1790. Available from: <div><a href="https://doi.org/10.1002/qj.4669">https://doi.org/10.1002/qj.4669</a></div> <div> </div> <div>The data consists of LST data, UM100 model output and ancillary files (all netCDF format).</div> <div> </div> <div><em>LST_data</em> contains:</div> </div> <ol> <li>Landsat LST data retrieved in this study (CALC) on four study days, LST data from FORTH and NASA JPL on two days</li> <li>MODIS LST data for 2018-07-15</li> </ol> <p><em>UM100_output</em> contains model output from initial and final runs for the four study days</p> <p>The python script <em>plot.py </em>can be used to generate the figures shown in this article. </p>
Enhancing High-Resolution Forest Stand Mean Height Mapping in China through an Individual Tree-Based Approach with Close-Range LiDAR Data
<p><span>We</span> have developed a tree-based approach to create spatially continuous forest stand mean height maps across China through integrating high-<span>point</span> density, high-precision close-range LiDAR data and multisource remote sensing data. The accuracy analysis of the arithmetic mean height (Ha) and the weighted mean height (Hw) demonstrates the feasibility of the proposed method. A practical framework for forestry investigation based on close-range LiDAR was proposed. The mean values of Ha and Hw are 13.3 ± 3.3 m 11.3 ± 2.9 m on pixel level, respectively. Validation based on LiDAR and field sample data shows that the RMSE values, range from 2.6 to 4.1 m for Ha and 2.9 to 4.3 m for Hw, respectively, indicating that our approach outperforms existing forest canopy height maps derived from area-based approaches. Hopefully, our methods and maps will serve as a foundation for estimating carbon storage, monitoring changes in forest structure, managing forest inventory, and assessing wildlife habitat availability. </p>
Data used in manuscript "High-resolution geophysical monitoring of moisture accumulation preceding slope movement – a path to improved early warning"
<p>Data used in the study titled "High-resolution geophysical monitoring of moisture accumulation preceding slope movement – a path to improved early warning" published in Environmental Research Letters</p>
High-resolution topography data and fault trace along the Southern Riyueshan fault, NE margin of Tibetan Plateau, China
<p>High-resolution digital elevation models (DEM) topography data extracted from the uncrewed aerial vehicle (UAV) of a DJI (Dajiang Innovations Science and Technology Co., Ltd.) Phantom 4 RTK, and GF-7 satellite stereo imagery. The trace of the Riyueshan fault is interpreted based on these high-resolution topography data.</p>
Data and scripts for the paper: Evaluating and improving a PDF cloud scheme using high-resolution super-large-domain simulations
<p>This is a collection of the processed data, plotting scripts, and processing scrips used in the making of the publication: "Evaluating and improving a PDF cloud scheme using high-resolution super-large-domain simulations" By Griewank, Schemann, and Neggers. </p> <p>WARNING: These files were used exclusively used by Philipp Griewank on his local work station, and the main purpose of uploading them is for reasons of scientific transparency. They are not highly optimized tools intended for general usage, so comments are hit and miss. Feel free to contact Philipp Griewank (currently philipp.griewank@uni-koeln.de) with any questions. </p>
High-resolution cone-beam scan of an apple and pebbles with two dosage levels
<p>We release two tomographic scans with two levels of radiation dosage of two measured objects for noise-level comparative studies in data analysis, reconstruction or segmentation methods. The objects are referred to as apple and pebbles (more specific, hydrograins), respectively. The dataset collected with higher dosage is referred to as the "<em><strong>good</strong></em>" <strong>dataset</strong>; and the other as the "<em><strong>noisy</strong></em>" <strong>dataset</strong>, as a way to distinguish between the two dosage levels.</p> <p>The dataset are acquired using the custom built and highly flexible CT scanner, FlexRay Lab, developed by XRE NV and located at CWI. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1943-by-1535 pixels, 14-bit, flat detector panel. </p> <p> </p> <p>Both dataset were collected over a 360 degrees in circular and continuous motion with 2001 projections distributed evenly over the full circle for the good dataset and 501 projections distributed evenly over the full circle for the noisy dataset. The uploaded dataset are not binned or normalized; a single dark and two (pre- and post-) flat fields are included for each scan. Projections for both sets were collected with 100 ms exposure time with the good data projections averaged over 5 takes, and no averaging was made for the noisy data. The tube settings for the good and noisy dataset were 70kV, 45W and 70kV, 20W, respectively. The total scanning time were 20 minutes for the good; 3 minutes for the noisy scan. Each dataset is packaged with the full list of data and scan settings files (in .txt format). These files contain the tube settings, scan geometry and full list of motor settings.</p> <p> </p> <p>These dataset are produced by the Computational Imaging members at Centrum Wiskunde & Informatica (CI-CWI). For any useful Python/MATLAB scripts for FlexRay dataset, we refer the reader to our group's <a href="http://github.com/cicwi">GitHub page</a>.</p> <p> </p> <p>For more information or guidance in using these dataset, please get in touch with </p> <ul> <li>s.b.coban [at] cwi.nl or</li> <li>m.j.lagerwerf [at] cwi.nl</li> </ul>
High-resolution cone-beam scan of two pomegranates with two dosage levels
<p>We release tomographic scans of two pomegranates with two levels of radiation dosage of two measured objects for noise-level comparative studies in data analysis, reconstruction or segmentation methods. The dataset collected with higher dosage is referred to as the "<em><strong>good</strong></em>" <strong>dataset</strong>; and the other as the "<em><strong>noisy</strong></em>" <strong>dataset</strong>, as a way to distinguish between the two dosage levels.</p> <p>The dataset are acquired using the custom built and highly flexible CT scanner, FlexRay Lab, developed by XRE NV and located at CWI. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1943-by-1535 pixels, 14-bit, flat detector panel. </p> <p> </p> <p>Both dataset were collected over a 360 degrees in circular and continuous motion with 2001 projections distributed evenly over the full circle for the good dataset and 501 projections distributed evenly over the full circle for the noisy dataset. The uploaded dataset are not binned or normalized; a single dark and two (pre- and post-) flat fields are included for each scan. Projections for both sets were collected with 100 ms exposure time with the good data projections averaged over 5 takes, and no averaging was made for the noisy data. The tube settings for the good and noisy dataset were 70kV, 45W and 70kV, 20W, respectively. The total scanning time were 20 minutes for the good; 3 minutes for the noisy scan. Each dataset is packaged with the full list of data and scan settings files (in .txt format). These files contain the tube settings, scan geometry and full list of motor settings.</p> <p> </p> <p>These dataset are produced by the Computational Imaging members at Centrum Wiskunde & Informatica (CI-CWI). For any useful Python/MATLAB scripts for FlexRay dataset, we refer the reader to our group's <a href="http://github.com/cicwi">GitHub page</a>.</p> <p> </p> <p>For more information or guidance in using these dataset, please get in touch with </p> <ul> <li>s.b.coban [at] cwi.nl or</li> <li>m.j.lagerwerf [at] cwi.nl</li> </ul>
Scripts developed to modelling the nocturnal ecological continuum of the State of Geneva, Switzerland, based on high-resolution nighttime imagery.
<p>The zipfile contains the scripts developed in the paper on the modelling of the nocturnal ecological continuum of the State of Geneva, Switzerland, based on high-resolution nighttime imagery, as published in Remote Sensing Applications: Society and Environment journal (RSASE - Elsevier). </p> <ul> <li>Scripts developed for the extraction of light sources from night orthophotography ; [SAFE Software Inc. (2017). FME Desktop Esri Edition.Version 2017.1.]</li> <li>ModelBuilder developed for the visibility modelling of light sources ; [ESRI (2017). ArcGIS Desktop Pro.Version 2.1.]</li> </ul>
Assessing the peatland hummock-hollow classification framework using high-resolution elevation models: Implications for appropriate complexity ecosystem modelling
<p>The hummock-hollow classification framework used to categorize peatland ecosystem microtopography is pervasive throughout peatland experimental designs and current peatland ecosystem modelling approaches. However, identifying what constitutes a representative hummock-hollow pair within a site and characterizing hummock-hollow variability within or between peatlands remains largely unassessed. Using structure-from-motion (SfM), high resolution digital elevation models (DEM) of hummock-hollow microtopography were used to: 1) examine how much area needs to be sampled to characterize site-level microtopographic variation; and 2) examine the potential role of microtopographic shape/structure on biogeochemical fluxes using data from 9 northern peatlands. This data set is comprised of plot DEMs, supporting data, and the script used to analyze data and produce figures presented in the manuscript submitted to Biogeosciences Discussion "ASSESSING THE PEATLAND HUMMOCK-HOLLOW CLASSIFICATION FRAMEWORK USING HIGH-RESOLUTION ELEVATION MODELS: IMPLICATIONS FOR APPROPRIATE COMPLEXITY ECOSYSTEM MODELLING".</p>
A high-resolution speleothem record of Marine Isotope Stage 11 as a natural analog to Holocene Asian summer monsoon variations
<p>A full-spectrum characterization of past interglacial climate is a necessary prerequisite for the detection and attribution of climate changes during the current interglacial. Here we present a speleothem record of Asian summer monsoon (ASM) during Marine Isotope Stage (MIS) 11 interglacial (MIS 11c), from Yongxing cave, China. The record’s unprecedented chronologic constraints and decadal-scale temporal resolution allow a precise and direct comparison of ASM between the MIS 11c and the Holocene. Our data suggest that orbital–centennial patterns of ASM were remarkably similar during both interglacial, including their pacing and structure. Notably, a multi-millennial stronger monsoon late in MIS 11c, the ‘Late-MIS 11c shift’, is similar to the Late Holocene strengthening of the ASM, the ‘2-kyr shift’. Thus the multi-centennial ASM weakening at the end of the ‘Late-MIS 11c shift’ could imply that the current century-long ASM waning trend may persist into the future, if only natural forcings are considered.</p>
In silico prediction of high-resolution Hi-C interaction matrices (part III)
<p>The uploaded files are source datasets for the HiC-Reg approach. HiC-Reg is a regression based method that predict contact counts from one-dimensional regulatory signals such as epigenetic marks and regulatory protein binding. See more details here (<a href="https://github.com/Roy-lab/HiC-Reg">https://github.com/Roy-lab/HiC-Reg</a>). There are a total of six files in this dataset: Data.tgz, Gm12878.tgz, Hmec.tgz, K562.tgz, Huvec.tgz and Nhek.tgz. The Data.tgz include predictions and other downstream analysis such as feature importance analysis, significant interaction calling, and data files for select figures. The Gm12878.tgz, K562.tgz, Huvec.tgz, Hmec.tgz and Nhek.tgz contain trained models, predictions, feature files for two chromosomes for in each cell line.</p> <p>This is part III of the dataset which contains Nhek.tgz and Data.tgz.</p>
In silico prediction of high-resolution Hi-C interaction matrices (part I)
<p>The uploaded files are source datasets for the HiC-Reg approach. HiC-Reg is a regression based method that predict contact counts from one-dimensional regulatory signals such as epigenetic marks and regulatory protein binding. See more details here (<a href="https://github.com/Roy-lab/HiC-Reg">https://github.com/Roy-lab/HiC-Reg</a>). There are a total of six files in this dataset: Data.tgz, Gm12878.tgz, Hmec.tgz, K562.tgz, Huvec.tgz and Nhek.tgz. The Data.tgz include predictions and other downstream analysis such as feature importance analysis, significant interaction calling, and data files for select figures. The Gm12878.tgz, K562.tgz, Huvec.tgz, Hmec.tgz and Nhek.tgz contain trained models, predictions, feature files for two chromosomes for in each cell line.</p> <p>This is part I of the dataset which contains Gm12878.tgz and Hmec.tgz.</p>
In silico prediction of high-resolution Hi-C interaction matrices (part II)
<p>The uploaded files are source datasets for the HiC-Reg approach. HiC-Reg is a regression based method that predict contact counts from one-dimensional regulatory signals such as epigenetic marks and regulatory protein binding. See more details here (<a href="https://github.com/Roy-lab/HiC-Reg">https://github.com/Roy-lab/HiC-Reg</a>). There are a total of six files in this dataset: Data.tgz, Gm12878.tgz, Hmec.tgz, K562.tgz, Huvec.tgz and Nhek.tgz. The Data.tgz include predictions and other downstream analysis such as feature importance analysis, significant interaction calling, and data files for select figures. The Gm12878.tgz, K562.tgz, Huvec.tgz, Hmec.tgz and Nhek.tgz contain trained models, predictions, feature files for two chromosomes for in each cell line.</p> <p>This is part II of the dataset which contains K562.tgz and Huvec.tgz.</p>
High-resolution ptychotomography dataset of nanoporous glass
<p>This repository contains nanoporous glass tomography dataset, acquired at the cSAXS beamline at the Swiss Light Source at the Paul Scherrer Institute in Villigen (Switzerland). Details about the data acquisition can be found in Ref. [1].</p> <p><strong>Citation and acknowledgements</strong></p> <p>For use of the ptychographic X-ray computed tomography dataset on nanoporous glass:</p> <p><em>[1] M. Holler, A. Diaz, M. Guizar-Sicairos, P. Karvinen, E. Färm, E. Härkönen, M. Ritala, A. Menzel, J. Raabe and O. Bunk. Scientific Reports, 4, 3857 (2014).</em></p> <p>Alignment and tomographic reconstruction provided in "<em>aligned_phase_sinogram" and "tomogram_delta" </em> were performed by a method described in</p> <p><em>[2] M. Odstrcil, M. Holler, J. Holler, M. Guizar-Sicairos,"Alignment methods for nanotomography with deep sub-pixel accuracy", Opt. Express, (2019).</em></p> <p><strong>Dataset description</strong></p> <p>The provided dataset is saved in Matlab MAT v7.3 format.</p> <p><em>stack_object</em> - complex valued unaligned projections with dimensions [Npix_vertical, Npix_horizontal, number_of_angles]</p> <p><em>rotation_angle</em> - vector of corresponding projection angles in degrees</p> <p><em>lambda</em> - wavelength of the illumination beam [m]</p> <p><em>pixel_size</em> - size of the reconstruction pixel [m]</p> <p><em>probe_size</em> - size of the reconstruction probe in pixels</p> <p><em>aligned_phase_sinogram</em> - aligned and unwrapped phase projections</p> <p><em>tomogram_delta</em> - reconstructed tomogram of real part of refractive index delta, n = 1-delta-i*beta</p>
ScienceDex guides
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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.