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.
1,255
datasets available to search
ShareScore release 0.9.0
Dataset results
1,255 results for “High-resolution”
High-resolution time series of leaf length and leaf thickness of strawberry and tomato measured in a growth chamber
<p>This dataset captures leaf thickness and leaf length of two strawberry plants and one tomato seeding. Leaf thickness measurements are only available of the strawberry plants. Additional data included light intensity data, soil water content (of one plant), relative humidity and temperature data. All sensors were read every second over a period of two weeks.</p>
High-resolution (30m) LULC images for Nanjing
<p># High-resolution (30m) LULC images for Nanjing</p> <ul> <li>resolution: 30m</li> <li>range: from 1985-2015</li> <li>interval: 5 years</li> <li>coordinate reference systems: EPSG:4326(wgs 1984), EPSG:32650 (wgs 1984 utm zone 50n)</li> <li>finished date: 2019/08/30</li> <li>available / original published on <a href="https://code.earthengine.google.com/?asset=users/XiaolongLiu/Nanjing/nanjing_lulc">Google Earth Engine Assets</a></li> </ul> <p># Land use land cover types</p> <p>| value | type|<br> |---------------|-----------------|<br> | 0 | urban and buit-up lands |<br> | 1 | Water bodies |<br> | 2 | Mixed forests |<br> | 3 | Cropland |<br> | 4 | Grass lands |</p>
High-Resolution Spectra of Habitable Zone Planets
<p>This dataset contains the simulated high-resolution spectra and profiles of 360 different Earth-like exoplanets around 12 different host star types and 30 different surface types.</p> <p><strong>Journal article for spectra:</strong> Madden & Kaltenegger (2020) High-resolution Spectra for a Wide Range of Habitable Zone Planets around Sun-like Stars. ApJL (<a href="https://doi.org/10.3847/2041-8213/aba535">https://doi.org/10.3847/2041-8213/aba535</a>)</p> <p><strong>Journal article for profiles:</strong> Madden & Kaltenegger (2020) How surfaces shape the climate of habitable exoplanets. MNRAS (<a href="https://doi.org/10.1093/mnras/staa387">https://doi.org/10.1093/mnras/staa387</a>)</p> <p> </p> <p><em><strong>Contents</strong></em></p> <p><em>ExampleSpectra_Total_HighRes.txt</em><strong> </strong>- This is a sample spectrum to get familiar with working with the data. All spectrum files are in <span class="math-tex">\(W/m^2/\mu m\)</span> and match with the included wavelength grid. </p> <p><em>WavelengthGrid_Microns_HighRes.txt </em>- Wavelength grid is spaced at <span class="math-tex">\(0.01cm^{-1}\)</span> intervals and converted to microns from 0.4 to 20. </p> <p><em>Spectra_Total_HighRes.zip</em> - Contains the combined emission and reflection spectra of all 360 simulations. All spectrum files are in <span class="math-tex">\(W/m^2/\mu m\)</span> and match with the included wavelength grid. </p> <p><em>Spectra_ReflectanceOnly_HighRes.zip</em> - Contains just the reflection spectra of all 360 simulations. All spectrum files are in <span class="math-tex">\(W/m^2/\mu m\)</span> and match with the included wavelength grid. </p> <p><em>Spectra_EmissionOnly_HighRes.zip</em> - Contains just the emission spectra of all 360 simulations. All spectrum files are in <span class="math-tex">\(W/m^2/\mu m\)</span> and match with the included wavelength grid. </p> <p><em>Profiles.zip </em>- Contains the mixing ratios, temperature (K), and pressure (bar) profiles with altitude (cm) for each simulation.</p>
Data repository from Boudewijn van Lieshout' thesis A comparison between Normalized Difference Vegetation Indices calculated from Sentinel 2A satellite data and high-resolution UAV imagery in Tanzania
<p>Monitoring vegetation is imperative for policy design and efficiency measurements. Frequent data collection, easy and inexpensive accessibility of images and the possibility of large area analysis, makes it still valuable to use satellite imagery. This study aims to examine how a Normalized Difference Vegetation Index (NDVI) measured with Sentinel-2A satellite data relates to an NDVI from Unmanned Aerial Vehicles (UAV henceforth) in study areas Chamwino Mlimwa and Chemba Waida, Tanzania.</p>
High-resolution gridded climate data for Europe based on bias-corrected EURO-CORDEX: the ECLIPS-2.0 dataset
<p>We developed a new climate dataset for Europe referred to as ECLIPS (European CLimate Index ProjectionS), which contains gridded data for 80 annual, seasonal, and monthly climate variables for two past (1961-1990, 1991-2010) and five future periods (2011-2020, 2021-2140, 2041-2060, 2061-2080, 2081-2100). The future data are based on five Regional Climate Models (RCMs)driven by two greenhouse gas concentration scenarios, RCP 4.5 and 8.5.</p> <p>The ECLIPS dataset has two versions; ECLIPS 1.1 contains data with spatial resolution of 0.11° × 0.11°, which is the resolution of underlying RCMs. ECLIPS1.1 is available at <a href="https://doi.org/10.5281/zenodo.1181780">https://doi.org/10.5281/zenodo.1181780</a>.</p> <p>The ECLIPS 2.0 presented here contains a subset of climate indices of ECLIPS 1.1, downscaled to the resolution of 30 arcsec by means of the delta correction approach. Both ECLIPS versions were evaluated by testing their relationship with independent station data from the European Climate Assessment (ECA) dataset. Correlations of the empirical testing data to ECLIPS 1.1 ranged from 0.63 to 0.78,and to ECLIPS 2.0 from 0.78 to 0.93. suggesting substantial improvement due to downscaling. A large number of climate projections, time periods and indices as well as the availability of these data at two different spatial resolutions can support diverse studies across a range of disciplines and thus extend our understanding of climate-sensitive dynamics of many social-ecological systems</p> <p>The zipfile ECLIPS2.0 contains 5 folders with subfolders</p> <p>File naming system for the subfolders / folder are as follows</p> <p>ECLIPS2.0_196191: past climate 1961-1990: < climate index><period></p> <p>ECLIPS2.0_199110: past climate 1991-2010 < climate index><period></p> <p>ECLIPS2.0_45 : future climate RCP4.5 <subfolder-Model name> < climate index><period></p> <p>ECLIPS2.0_85 : future climate RCP8.5 <subfolder-Model name> < climate index><period></p> <p>Incase zpfile reader 7zip is not available, please install from here: <a href="https://www.7-zip.org/">https://www.7-zip.org/</a></p>
High-resolution stem radius changes of Juniperus excelsa and Cedrus libani from the Taurus Mountain range of SW-Turkey
<p>This dataset is related to our article published in Annals of Forest Science (2020):<br> Güney, A., Zweifel, R., Türkan, S. et al. Drought responses and their effects on radial stem growth of two co-occurring conifer species in the Mediterranean mountain range. Annals of Forest Science 77, 105 (2020). <a href="https://doi.org/10.1007/s13595-020-01007-2">https://doi.org/10.1007/s13595-020-01007-2</a></p> <p>The dataset includes hourly resolved stem radius change (SRC) measurements of adult <em>Juniperus excelsa</em> (JUEX) and <em>Cedrus libani</em> (CDLI) individuals. It further includes metadata, environmental data, and data about tree water relations and growth parameters which were calculated from stem radius change measurements.<br> Stem radius change measurements were performed with point dendrometers on five adult <em>J. excelsa</em> and four adult <em>C. libani</em> individuals growing at 1350 m asl in the Elmali Cedar Research forest in Antalya, Turkey. Meaurements started in October 2012 and lasted until December 2014. Concurrently, environmental conditions were measured at site.</p> <p>Metadata and datasheets are provided as excel-files and also separately in the ".csv" format. The figure shows the study site (a circular plot with a radius of 30 m as indicated by the red circle) with the studied <em>J. excelsa</em> (J1–J5) and <em>C. libani</em> (C1–C4) individuals at the Elmali Cedar Research Forest, Antalya, Turkey (W= Weather station).</p> <p>Datasheet 4 includes three variables that were calculated from the raw dendrometer measurements (SRC), which are:<br> 1) GROrate= rate of irreversible stem increment<br> 2) TWD= tree water deficit induced shrinkage of the stem<br> 3) MDS= maximum daily shrinkage of the stem<br> These generated data represent daily averages per species. TWD and MDS represent normalized data. These three variables were used to investigate species-specific and year-to-year differences. They were further analyzed for their relationship with environmental parameters using statistical analyses.<br> The supplementary material file (excel) includes (1) the results of the environmental conditions during periods when irreversible stem growth (GRO) occured (spreadsheet 1), and (2) results from statistical analyses (MARS) that analyzed the relationship between the generated data from dendrometer measurements (GROrate, TWD, MDS) and climate data (spreadsheet 2).</p> <p>Detailed information about the study site, the data set and the variables can be found in the metadata file.<br> </p>
Depressurization of CO2 in a pipe: High-resolution pressure and temperature data and comparison with model predictions – dataset
<p>This dataset contains data from depressurization of pure CO<sub>2</sub> and nitrogen in a tube from a gaseous and a dense-liquid state. The data are described in the accompanying paper (DOI: <a href="https://doi.org/10.1016/j.energy.2020.118560">10.1016/j.energy.2020.118560</a>).</p> <p>Test number; fluid; pressure (MPa); temperature (deg C):<br> 3; CO2; 4.04; 10.2<br> 4; CO2; 12.54; 21.1<br> 6; CO2; 10.40; 40.0<br> 8; CO2; 12.22; 24.6<br> 11; N2; 5.13; 10.0</p> <p><br> </p>
High-resolution soil erodibility map of Brazil
<p>This dataset provides high-resolution (250 m cell size) spatially explicit soil erodibility map across Brazil. The content is described below:</p> <ul> <li>K-factor_nomo.zip => soil erodibility estimated by the algebraic solution of USLE nomograph [t ha h ha<sup>-1</sup> MJ<sup>-1</sup> mm<sup>-1</sup>]</li> <li>K-factor_EPIC.zip => soil erodibility estimated by the EPIC Model [t ha h ha<sup>-1</sup> MJ<sup>-1</sup> mm<sup>-1</sup>]</li> <li>structure-code.zip => USLE structure code assigned to Brazilian soil groups.</li> <li>permeability.zip => USLE permeability code.</li> </ul> <p>Contact for further information: rachgodoi@gmail.com</p>
Data from: A new approach using high-resolution computed tomography to test the buoyant properties of chambered cephalopod shells
The chambered shell of modern cephalopods functions as a buoyancy apparatus, allowing the animal to enter the water column without expending a large amount of energy to overcome its own weight. Indeed, the chambered shell is largely considered a key adaptation that allowed the earliest cephalopods to leave the ocean floor and enter the water column. It has been argued by some, however, that the iconic chambered shell of Paleozoic and Mesozoic ammonoids did not provide a sufficiently buoyant force to compensate for the weight of the entire animal, thus restricting ammonoids to a largely benthic lifestyle reminiscent of some octopods. Here we develop a technique using high-resolution computed tomography to quantify the buoyant properties of chambered shells without reducing the shell to ideal spirals or eliminating inherent biological variability by using mathematical models that characterize past work in this area. This technique has been tested on Nautilus pompilius and is now extended to the extant deep-sea squid Spirula spirula and the Jurassic ammonite Cadoceras sp. hatchling. Cadoceras is found to have possessed near-neutral to positive buoyancy if hatched when the shell possessed between three and five chambers. However, we show that the animal could also overcome degrees of negative buoyancy through swimming, similar to the paralarvae of modern squids. These calculations challenge past inferences of benthic life habits based solely on calculations of negative buoyancy. The calculated buoyancy of Cadoceras supports the possibility of planktonic dispersal of ammonite hatchlings. This information is essential to understanding ammonoid ecology as well as biotic interactions and has implications for the interpretation of geochemical data gained from the isotopic analysis of the shell.
Data and code for a high-resolution summary of Cambrian to Early Triassic marine invertebrate biodiversity
<p>Data compilation and standardization were conducted through the Geobiodiversity Database from 2013 to 2017. The raw dataset contained 266,110 local Cambrian to Triassic records of 45,318 taxonomic units from 3,766 published stratigraphic sections. These were collected from all major Chinese tectonic plates. The authors spent three years verifying the taxonomic assignments into a consistent paleontological taxonomic classification system. Identifications to genus or higher taxonomic ranks were omitted. All non-marine fossil groups (e.g., plants, vertebrates, pollen, spores) were also removed. Species recovered from only a single locality were removed after a few test calculations in order to partially standardize the sampling and research efforts and avoid the "monograph effect". The final dataset retained after all standardization procedures included 116,060 local records of the stratigraphic ranges of 11,268 species in 3,112 published stratigraphic sections. </p> <p>The CONOP.SAGA program was designed for high-performance computing of geological time scale and biodiversity analysis in 2017. We designed a special hybrid algorithm that combined simulated annealing and a genetic algorithm to overcome the limitations of classic CONOP program designed by Pete Sadler.</p>
Data from: Analysing small insect glands with UV-LDI MS: high-resolution spatial analysis reveals the chemical composition and use of the osmeterium secretion in Themira superba (Sepsidae: Diptera)
For many insect species, pheromones are important communication tools, but chemical analysis and experimental study can be technically challenging because they require the detection and handling of complex chemicals in small quantities. One drawback of traditional mass spectrometry methods such as gas chromatography mass spectrometry is that whole-body extractions from one to several hundred individuals are required, with the consequence that intra- and interindividual differences cannot be detected. Here, we used the recently introduced UV-LDI MS (ultraviolet laser desorption/ionization mass spectrometry) to profile the 'osmeterium' of the sepsid fly Themira superba that is located on the edge of the hind tibia of males. Based on analyses of individual legs, we established that the gland produced a secretion that consisted of oxygenated hydrocarbons and putative isoprenoids. The secretion was first detected 24 h after eclosion, and its transfer to the wings of females during mating was demonstrated using UV-LDI MS. We then tested whether the secretion had an anti-aphrodisiac function, but experimental transfer of the secretion to virgin females did not affect mating success or copulation duration. Throughout the study, UV-LDI MS proved invaluable, because it allowed tracking the natural and experimental transfer of small quantities of pheromones to specific body parts of small flies.
Data from: Mapping migration in a songbird using high-resolution genetic markers
Neotropical migratory birds are declining across the Western Hemisphere, but conservation efforts have been hampered by the inability to assess where migrants are most limited – the breeding grounds, migratory stopover sites, or wintering areas. A major challenge has been the lack of an efficient, reliable, and broadly applicable method for measuring the strength of migratory connections between populations across the annual cycle. Here we show how high-resolution genetic markers can be used to identify genetically distinct groups of a migratory bird, the Wilson's warbler (Cardellina pusilla), at fine enough spatial scales to facilitate assessing regional drivers of demographic trends. By screening 1626 samples using 96 highly divergent single nucleotide polymorphisms (SNPs) selected from a large pool of candidates (~450,000), we identify novel region-specific migratory routes and timetables of migration along the Pacific Flyway. Our results illustrate that high-resolution genetic markers are more reliable, precise, and amenable to high throughput screening than previously described intrinsic marking techniques, making them broadly applicable to large-scale monitoring and conservation of migratory organisms.
Data from: Evidence for amino acid snorkeling from a high-resolution, in vivo analysis of Fis1 tail anchor insertion at the mitochondrial outer membrane
Proteins localized to mitochondria by a carboxyl-terminal tail anchor (TA) play roles in apoptosis, mitochondrial dynamics, and mitochondrial protein import. To reveal characteristics of TAs that may be important for mitochondrial targeting, we focused our attention upon the TA of the Saccharomyces cerevisiae Fis1 protein. Specifically, we generated a library of Fis1p TA variants fused to the Gal4 transcription factor, then, using next-generation sequencing, revealed which Fis1p TA mutations inhibited membrane insertion and allowed Gal4p activity in the nucleus. Prompted by our global analysis, we subsequently analyzed the ability of individual Fis1p TA mutants to localize to mitochondria. Our findings suggest that the membrane-associated domain of the Fis1p TA may be bipartite in nature, and we encountered evidence that the positively charged patch at the carboxyl-terminus of Fis1p is required for both membrane insertion and organelle specificity. Furthermore, lengthening or shortening of the Fis1p TA by up to three amino acids did not inhibit mitochondrial targeting, arguing against a model in which TA length directs insertion of TAs to distinct organelles. Most importantly, positively charged residues were more acceptable at several positions within the membrane-associated domain of the Fis1p TA than negatively charged residues. These findings, emerging from the first high-resolution analysis of an organelle targeting sequence by deep mutational scanning, provide strong, in vivo evidence that lysine and arginine can "snorkel," or become stably incorporated within a lipid bilayer by placing terminal charges of their side chains at the membrane interface.
Datasets and codes for "Exploiting high-resolution ADS-B data for flight operation reconstruction towards environmental impact assessment"
<p>Here you can find all the datasets and Python codes used to obtain the results illustrated in "Exploiting high-resolution ADS-B data for flight operation reconstruction towards environmental impact assessment" (authors: Marco Pretto, Lorenzo Dorbolò, Pietro Giannattasio).</p><p>Folders are in the following order:</p><ul><li>0_files: flight tracking data (from the OpenSky Network) and open databeses</li><li>1_preproc: flight separation algorithm</li><li>2_preproc: runway assignment algorithm</li><li>3_proc: ground track reconstruction algorithm</li><li>4_postproc: postprocessing codes (for figures)</li></ul>
Long time-series (2020-2100) high-resolution (1km) multi-scenario and multi-depth soil organic carbon dataset in China
<p>unit: kg C m-2 (soil oganic carbon density)</p><p>0100: denote 0-100 cm</p><p>020: denote 0-20 cm</p><p>Example 2020: 2020-2024 (five years mean soc)</p>
High-resolution snow depth prediction using Random Forest algorithm with topographic parameters
Open the record for dataset details and reuse information.
SWECA: High-resolution daily Snow Water Equivalent estimates for Mountainous Central Asia (1979–2016)
<p>The dataset provides daily estimates of snow water equivalent (SWE) for Central Asia, at a spatial resolution of 1km, covering the period from 1979 to 2016. The dataset were generated within the <a href="https://www.iamo.de/en/research/research-projects/details/sweca/">SWECA</a> project, supported by GEO Mountains under the Adaptation at Altitude Programme (Swiss Agency for Development and Cooperation Project Number: 7F-10208.01.02).</p> <p><strong>Spatial Domain:</strong><br>The dataset encompasses the Central Asian region within the bounding coordinates 61W, 81E, 44N, 34S, which covers the Tian-Shan and Pamir mountains, a larger extent of the Hindukush mountains, and the northern part of the Karakoram mountains.</p> <p><strong>Data Generation and Validation:</strong><br>The SWE data was generated using the <a href="../records/10161423">GEMS snow mode</a>l (Umirbekov, Essery, and Müller, 2024), forced by CHELSA-W5E5 daily climate data (Karger et al., 2023). Simulated SWE was validated using historical records of SWE from 1980 to 1992 from Central Asian Snow Survey database (Bedford and Tsarev, 2001), and by comparing extent of the modelled SWE with MODIS derived snowcover for two consecutive hydrological years (2015-2016). Data generation procedures and validation results will be provided in upcoming data description paper (TBD).</p> <p><strong>File Descriptions:</strong><br>The daily SWE estimates (in millimeters) are compiled into 37 GeoTIFF files, each corresponding to a hydrological year from 1979 to 2016. The hydrological year begins on October 1st and concludes on September 30th of next year. To avoid the need for auxiliary files, the corresponding date of each layer in the GeoTIFF file is incorporated as a layer`s name. </p> <p>References: </p> <ul> <li>Bedford, D. and Tsarev, B. (2001) ‘Central Asian Snow Cover from Hydrometeorological Surveys, Version 1 [Dataset]’. Boulder, Colorado USA.: National Snow and Ice Data Center. doi: <a href="https://doi.org/10.7265/N51Z4291">10.7265/N51Z4291</a>.</li> <li>Karger, D. N. et al. (2023) ‘CHELSA-W5E5: daily 1km meteorological forcing data for climate impact studies’, Earth System Science Data, 15(6), pp. 2445–2464. doi: <a href="https://doi.org/10.5194/essd-15-2445-2023">10.5194/essd-15-2445-2023</a>.</li> <li>Riggs, G., Hall, D. and Salomonson, V. (2019) ‘MODIS snow products user guide to collection 6.1: MODIS-derived snow cover retrievals using the cloud-gap-filled MOD10A1F product’.</li> <li>Umirbekov, A., Essery, R. and Müller, D. (2024) ‘GEMS v1.0: Generalizable Empirical Model of Snow Accumulation and Melt, based on daily snow mass changes in response to climate and topographic drivers’, Geoscientific Model Development, 17(2), pp. 911–929. doi: <a href="https://doi.org/10.5194/gmd-17-911-2024">10.5194/gmd-17-911-2024</a>. </li> </ul>
High-resolution (10-meter) Dynamic Water body map of the Hindu Kush Himalaya region (DWH10) for the year 2022
Open the record for dataset details and reuse information.
Facilitating circularity of end-of-life photovoltaic in China by mid-century with environmental benefits and costs informed by a high-resolution waste map
Open the record for dataset details and reuse information.
Supplementary material to "Food and habitats requirements of the Scops Owl (Otus scops) in Switzerland revealed by very high-resolution multi-scale models"
<p><strong>Abstract</strong></p> <p>In Europe, agricultural practices have progressively evolved towards high productivity leading either to the intensification of productive and accessible areas or to the abandonment of less profitable sites. Both processes have led to the degradation of semi-natural habitats like extensive grasslands, threatening species such as the Eurasian Scops Owl <em>Otus scops</em> that rely on extensively managed agricultural landscapes. In this work, we aimed to assess the habitat preferences of the Scops Owl using habitat suitability models combined with a multi-scale approach. We generated a set of multi-scale predictors, considering both biotic and abiotic variables, built on two newly developed vegetation management and orthopteran abundance models. To select the variables to incorporate in a ‘best multi-scale model’, we chose the best spatial scale for each variable using univariate models and by calculating their relative importance through multi-model inference. Next, we built ensembles of small models (ESMs) at 10 different scales from 50 to 1000 m, and an additional model with each variable at its best scale (‘best multi-scale model’). The latter performed better than most of the other ESMs and allowed the creation of a high-resolution habitat suitability map for the species. Scops Owls showed a preference for dry sites with extensive and well-structured habitats with 30–40% bush cover, and relied strongly on semi-extensive grasslands covering at least 30% of the surface within 300 m of the territory centre and with high orthopteran availability near the centre (50-m radius), revealing a need for good foraging grounds near the nest. At a larger spatial scale within a radius of 1000 m, the habitat suitability of Scops Owls was negatively related to forest cover. The resulting ESM predictions provide valuable tools for conservation planning, highlighting sites in need of particular conservation efforts together with offering estimates of the percentage of habitat types and necessary prey abundance that could be used as targets in future management plans to ensure the persistence of the population.</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.