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Dataset results
708 results for “Global dataset”
Dataset supporting "On the resolution sensitivity of equatorical precipitation in a GFDL global atmospheric model"
<p>Specification of the model vertical coordinate, selected analysis script, and selected variables from aquaplanet simulations from a GFDL global atmospheric model at different horizontal resolutions: c192 (corresponding to a nominal resolution of 50 km), c384 (~25 km), c768 (~13 km), c1536 (~6 km). Details of the simulations are documented in a manuscript titled "On the resolution sensitivity of equatorial precipitation in a GFDL global atmospheric model" to be submitted to the Journal of Advances in Modeling Earth Systems.</p>
SILAC, Global Metabolomics and Targeted Lipidomics datasets
<p>3 dataset files are uploaded:</p> <p>1. SILAC dataset (Figure 2g, S2f)</p> <p>2. Global metabolites profiling (Figure 3a)</p> <p>3. Targeted lipid metabolites profiling (Figure 4a, 5l, S9g)</p>
WHUS2-CRv a global thin cloud removal dataset for Sentinel-2 images——Validation and testing parts
<p>The validation and testing parts of WHUS2-CRv dataset in which the paired cloud and cloud-free Sentinel-2 images are from different regions of the world. The types of land cover are rich and the acquisition dates of the experimental data cover a long time period (from 2015 to 2020) and all seasons.</p> <p>If you use this dataset for your research, please cite us accordingly:</p> <p>#Reference: </p> <p>[1]J. Li, Z. W, Z. Hu, J. Z, M. Li, L. Mo and M. Molinier, “Thin cloud removal in optical remote sensing images based on generative adversarial networks and physical model of cloud distortion,” ISPRS J. Photogramm. Remote Sens., vol. 166, pp. 373-389, Aug. 2020,http://doi.org/10.1016/j.isprsjprs.2020.06.021.</p> <p>[2]J. Li, Z. Wu, Z. Hu, Z. Li, Y. Wang, and M. Molinier, “Deep learning based thin cloud removal fusing vegetation red edge and short wave infrared spectral information for Sentinel-2A imagery,” Remote Sens., vol. 13, no. 1, p. 157, Jan. 2021, http://doi.org/10.3390/rs13010157.</p> <p>[3]J. Li, Y. Zhang, Q. Sheng, Z. Wu, B. Wang, Z. Hu, G. Shen, M. Schmitt, M. Molinier, “Thin Cloud Removal Fusing Full Spectral and Spatial Features for Sentinel-2 Imagery,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 8759-8775, 2022, doi: 10.1109/JSTARS.2022.3211857.</p>
Global in situ ocean POC flux compilation dataset
<p>Global dataset of 1,841 <em>in situ</em> carbon flux (C flux) estimates measured at 100 ± 75 m using sediment traps and <sup>234</sup>Thorium methods. <em>Start date </em>(column 2), and <em>End date</em> (column 3) indicate the dates (dd/mm/yyyy) at which C flux measurements started and ended. <em>Duration</em> (column 4) indicates the time period over which the C flux was measured (assumed at 16 days for <sup>234</sup>Th-derived measurements, see Materials and Methods). <em>Lat</em> (column 5) and <em>Lon</em> (column 6) indicate the Latitude (º) and Longitude (º) of the measurements. <em>C flux</em> (column 7) are reported in mg C m<sup>-2</sup> d<sup>-1</sup>. <em>Method</em> (column 9) indicates the method used for the measurements (1 for <sup>234</sup>Th and 2 for sediment traps). <em>Reference ID</em> refers to the origin of the measurement (list given in header).</p>
Dataset for manuscript "Regional variability of aerosol impacts on clouds and radiation in global kilometer-scale simulations"
<p>This dataset includes two Jupyterlab book python script and a folder of compressed data. (latest version includes updated script to fix mising variable)</p> <p>Due to the size of the dataset we are unable to include the raw simulation output but have instead inluded all datasets required to plot the figures.</p> <p>The python script "original_analysis_script.ipynb" contains the code that was used to perform the analysis on the outputs from the simulations. This is not intended for public use.</p> <p>The python script "figure_plotting_scripts.ipynb" is a cut-down verison of the original code that can be used to plot the figures as presented in the manuscript. All neccessary data to achieve this can be found in the compressed folder "data_arrays". </p> <p>The scripts will run on Jupyterlab book. Providing the user has the neccessary python modules available the plotting script can be run by amending the paths for the figure outout directory and the uncompressed "data_arrays" directory. These paths can be found at the top of the script.</p> <p> </p>
Mechanisms of crystalline silica-induced pulmonary toxicity revealed by global gene expression profiling (A549 cells dataset 4)
GEO Series GSE30214. Homo sapiens. 10 samples. Type: Expression profiling by array.
Data from: A global experimental dataset for assessing grain legume production
Open the record for dataset details and reuse information.
Last of the Wild Project, Version 2, 2005 (LWP-2): Global Human Footprint Dataset (Geographic)
The Global Human Footprint Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset in Clarke 1866 Geographic Coordinate System is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN).
Randolph Glacier Inventory - A Dataset of Global Glacier Outlines, Version 2
The Randolph Glacier Inventory (RGI) is a global set of glacier outlines; it is intended as a snapshot of the world’s glaciers. This data set provides a single outline for each glacier and is produced in coordination with the Global Land Ice Measurements from Space (GLIMS) initiative. The RGI is not suitable for measuring glacier-by-glacier rates of area change, but can be used to estimate glacier volumes, rates of elevation change at regional and global scales, and cryospheric responses to climatic forcing.Glacier mapping data are contributed to both GLIMS and the RGI from the glaciological community. RGI is produced by the Working Group on the Randolph Glacier Inventory and Infrastructure for Glacier Monitoring, a body of the International Association of Cryospheric Sciences (IACS). This data set is updated approximately annually.Glacier outlines are distributed as Shapefiles. Hypsometric data (CSV files) and gridded auxiliary data (GeoTIFFs) are also available. All RGI data are packaged globally and by region, with regions based upon the Global Terrestrial Network for Glaciers.
Global Urban Polygons and Points Dataset (GUPPD), Version 1
The Global Urban Polygons and Points Dataset (GUPPD), Version 1 is a global data set of 123,034 urban settlements with place names and population for the years 1975-2030 in five-year increments. The data set builds on and expands the European Commission, Joint Research Centre's (JRC) 2015 Global Human Settlement (GHS) Urban Centre Database (UCDB). The JRC Settlement Model (GHS-SMOD) data set includes a hierarchy of urban settlements, from urban centre (level 30), to dense urban cluster (level 23), to semi-dense urban cluster (level 22). The UCDB only includes level 30, whereas the GUPPDv1 adds levels 23 and 22, and uses open data sources to both check and validate the names that JRC assigned to its UCDB polygons and to label the newly added settlements. The methodology described in the documentation was able to consistently label a greater percentage of UCDB polygons than were previously labeled by JRC.
Last of the Wild Project, Version 1, 2002 (LWP-1): Global Human Footprint Dataset (IGHP)
The Global Human Footprint Dataset of the Last of the Wild Project, Version 1, 2002 (LWP-1) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density, population settlements), human land use and infrastructure (built up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset in Interrupted Goode Homolosine Projection (IGHP) is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN).
Global Human Built-up And Settlement Extent (HBASE) Dataset From Landsat
The Global Human Built-up And Settlement Extent (HBASE) Dataset from Landsat is a global map of HBASE derived from the Global Land Survey (GLS) Landsat dataset for the target year 2010. The HBASE dataset consists of two layers: 1) the HBASE mask; and 2) the pixel-wise probability of HBASE. These layers are co-registered to the same spatial extent at a common 30m spatial resolution. The spatial extent covers the entire globe except Antarctica and some small islands. This dataset is one of the first global, 30m datasets of urban extent to be derived from the GLS data for 2010 and is a companion dataset to the Global Man-made Impervious Surface (GMIS) dataset. The HBASE mask was created for post-processing of the GMIS dataset, but can also be utilized by users needing a binary map. The dataset is expected to have a rather broad spectrum of users, from those wishing to examine/study the fine details of urban land cover over the globe at full 30m resolution to global modelers trying to understand the climate/environmental impacts of man-made surfaces at continental to global scales. For example, the data are applicable to local modeling studies of urban impacts on the energy, water, and carbon cycles, as well as analyses at the individual country level.
Randolph Glacier Inventory - A Dataset of Global Glacier Outlines, Version 4
The Randolph Glacier Inventory (RGI) is a global set of glacier outlines; it is intended as a snapshot of the world’s glaciers. This data set provides a single outline for each glacier and is produced in coordination with the Global Land Ice Measurements from Space (GLIMS) initiative. The RGI is not suitable for measuring glacier-by-glacier rates of area change, but can be used to estimate glacier volumes, rates of elevation change at regional and global scales, and cryospheric responses to climatic forcing.Glacier mapping data are contributed to both GLIMS and the RGI from the glaciological community. RGI is produced by the Working Group on the Randolph Glacier Inventory and Infrastructure for Glacier Monitoring, a body of the International Association of Cryospheric Sciences (IACS). This data set is updated approximately annually.Glacier outlines are distributed as Shapefiles. Hypsometric data (CSV files) and gridded auxiliary data (GeoTIFFs) are also available. All RGI data are packaged globally and by region, with regions based upon the Global Terrestrial Network for Glaciers.
Last of the Wild Project, Version 2, 2005 (LWP-2): Global Human Footprint Dataset (IGHP)
The Global Human Footprint Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is the Human Influence Index (HII) normalized by biome. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset in Interrupted Goode Homolosine Projection (IGHP) is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN).
Randolph Glacier Inventory - A Dataset of Global Glacier Outlines, Version 7
The Randolph Glacier Inventory (RGI) is a global set of glacier outlines intended as a snapshot of the world’s glaciers outside of ice sheets. It provides a single outline for each glacier from approximately the year 2000, as well as a set of attributes and other relevant auxiliary information. Glacier outlines are distributed as Shapefiles. Hypsometric data and attributes (CSV files) and metadata (json) are also available. All RGI data are packaged both globally and by region (as defined by the Global Terrestrial Network for Glaciers (GTN-G) Glacier Regions).The RGI is not suitable for measuring glacier-by-glacier rates of area change. However, it can be used to estimate glacier volumes; rates of elevation change at regional and global scales; and glacier responses to climatic forcing.RGI version 7.0 was developed by the “Working Group on the Randolph Glacier Inventory (RGI) and its role in future glacier monitoring” of the International Association of Cryospheric Sciences (IACS). The glaciological community contributes glacier mapping data to the Global Land Ice Measurements from Space (GLIMS) database. A subset of the glacier outlines in GLIMS are then extracted and reprocessed to produce the RGI.See the RGI documentation under "User Guide" (below) for more information.
Randolph Glacier Inventory - A Dataset of Global Glacier Outlines, Version 3
The Randolph Glacier Inventory (RGI) is a global set of glacier outlines; it is intended as a snapshot of the world’s glaciers. This data set provides a single outline for each glacier and is produced in coordination with the Global Land Ice Measurements from Space (GLIMS) initiative. The RGI is not suitable for measuring glacier-by-glacier rates of area change, but can be used to estimate glacier volumes, rates of elevation change at regional and global scales, and cryospheric responses to climatic forcing.Glacier mapping data are contributed to both GLIMS and the RGI from the glaciological community. RGI is produced by the Working Group on the Randolph Glacier Inventory and Infrastructure for Glacier Monitoring, a body of the International Association of Cryospheric Sciences (IACS). This data set is updated approximately annually.Glacier outlines are distributed as Shapefiles. Hypsometric data (CSV files) and gridded auxiliary data (GeoTIFFs) are also available. All RGI data are packaged globally and by region, with regions based upon the Global Terrestrial Network for Glaciers.
Randolph Glacier Inventory - A Dataset of Global Glacier Outlines, Version 6
The Randolph Glacier Inventory (RGI) is a global set of glacier outlines; it is intended as a snapshot of the world’s glaciers. This data set provides a single outline for each glacier and is produced in coordination with the Global Land Ice Measurements from Space (GLIMS) initiative. The RGI is not suitable for measuring glacier-by-glacier rates of area change, but can be used to estimate glacier volumes, rates of elevation change at regional and global scales, and cryospheric responses to climatic forcing.Glacier mapping data are contributed to both GLIMS and the RGI from the glaciological community. RGI is produced by the Working Group on the Randolph Glacier Inventory and Infrastructure for Glacier Monitoring, a body of the International Association of Cryospheric Sciences (IACS). This data set is updated approximately annually.Glacier outlines are distributed as Shapefiles. Hypsometric data (CSV files) and gridded auxiliary data (GeoTIFFs) are also available. All RGI data are packaged globally and by region, with regions based upon the Global Terrestrial Network for Glaciers.
Last of the Wild Project, Version 2, 2005 (LWP-2): Global Human Influence Index (HII) Dataset (IGHP)
The Global Human Influence Index Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset in Interrupted Goode Homolosine Projection (IGHP) is produced by the Wildlife Conservation Society (WCS) and Columbia University Center for International Earth Science Information Network (CIESIN).
Last of the Wild Project, Version 2, 2005 (LWP-2): Global Human Influence Index (HII) Dataset (Geographic)
The Global Human Influence Index Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset in Clarke 1866 Geographic Coordinate System is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN).
Randolph Glacier Inventory - A Dataset of Global Glacier Outlines, Version 1
The Randolph Glacier Inventory (RGI) is a global set of glacier outlines; it is intended as a snapshot of the world’s glaciers. This data set provides a single outline for each glacier and is produced in coordination with the Global Land Ice Measurements from Space (GLIMS) initiative. The RGI is not suitable for measuring glacier-by-glacier rates of area change, but can be used to estimate glacier volumes, rates of elevation change at regional and global scales, and cryospheric responses to climatic forcing.Glacier mapping data are contributed to both GLIMS and the RGI from the glaciological community. RGI is produced by the Working Group on the Randolph Glacier Inventory and Infrastructure for Glacier Monitoring, a body of the International Association of Cryospheric Sciences (IACS). This data set is updated approximately annually.Glacier outlines are distributed as Shapefiles. Hypsometric data (CSV files) and gridded auxiliary data (GeoTIFFs) are also available. All RGI data are packaged globally and by region, with regions based upon the Global Terrestrial Network for Glaciers.
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.