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Dataset results
138 results for “Geospatial”
National Aggregates of Geospatial Data Collection: Population, Landscape, And Climate Estimates, Version 3 (PLACE III)
The National Aggregates of Geospatial Data Collection: Population, Landscape, And Climate Estimates, Version 3 (PLACE III) data set contains estimates of national-level aggregations in urban, rural, and total designations of territorial extent and population size by biome, climate zone, coastal proximity zone, elevation zone, and population density zone, for 232 statistical areas (countries and other UN recognized territories). This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
GIBS Geospatial Data Abstraction Library (GDAL)
GDAL is an open source translator library for raster geospatial data formats that presents a single abstract data model to the calling application for all supported formats. By providing integration into the GDAL command line utilities, GIBS imagery can be easily included in imagery processing workflows, including bulk access.
National Aggregates of Geospatial Data Collection: Population, Landscape, And Climate Estimates, Version 4 (PLACE IV)
The National Aggregates of Geospatial Data Collection: Population, Landscape, And Climate Estimates, Version 4 (PLACE IV) provides measures of population (head counts) and land area (square kilometers) as totals and by urban and rural designation, within multiple biophysical themes for 248 statistical areas (countries and other territories recognized by the United Nations (UN)), UN geographic regions and subregions, and World Bank economic classifications. It improves upon previous versions by providing these estimates at both the national level, and where possible, at subnational administrative level 1 for the years 2000, 2005, 2010, 2015, and 2020, and by 5-year and broad age groups for the year 2010.
National Aggregates of Geospatial Data Collection: Population, Landscape, And Climate Estimates, Version 2 (PLACE II)
The National Aggregates of Geospatial Data Collection: Population, Landscape, And Climate Estimates, Version 2 (PLACE II) data set contains estimates of national-level aggregations of territorial extent and population size by biome, climate zone, coastal proximity zone, elevation zone, and population density zone, a compendium of nearly 300 variables for 228 countries. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
Global Database of Light-based Geospatial Income Inequality (LGII) Measures, Version 1
The Global Database of Light-based Geospatial Income Inequality (LGII) Measures, Version 1 data set contains Gini-coefficients of inequality for 234 countries and territories from 1992 to 2013. The measurement Unit is the Gini-Coefficient (Range: 0-1), with higher values representing higher inequality. These measures are constructed using worldwide geospatial satellite data on nighttime lights emission as a proxy for economic prosperity, matched with varying sources of data on geo-located population counts. The nighttime lights data were supplied by the National Oceanic and Atmospheric Administration (NOAA), National Centers for Environmental Information (NCEI), Earth Observation Group (EOG), and Operational Linescan System (OLS) instruments. The population data used consisted of CIESIN's Gridded Population of the World (GPW) collection, and the Oak Ridge National Laboratory (ORNL) LandScan (LSC) data set. The nighttime lights and population data were combined to produce an array of geospatially-informed Gini-coefficients, which were then weighted to optimize their correlation with a benchmark - specifically, the Standardized World Income Inequality Database (SWIID), to generate a parsimonious composite inequality metric.
National Aggregates of Geospatial Data Collection: Population, Landscape, And Climate Estimates (PLACE)
The National Aggregates of Geospatial Data Collection: Population, Landscape, And Climate Estimates (PLACE) data set contains estimates of national-level aggregations of territorial extent and population size by biome, climate zone, coastal proximity, elevation and slope, a compendium of nearly 300 variables for 222 countries. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).
FIGURE 3 in Quantifying vertebrate zoogeographical regions of Australia using geospatial turnover in the species composition of mammals, birds, reptiles and terrestrial amphibians
FIGURE 3. Phytogeographical subregions of Australia (Ebach et al. 2015), based on the analysis by González-Orozco et al. (2014b).
FIGURE 6 in Quantifying vertebrate zoogeographical regions of Australia using geospatial turnover in the species composition of mammals, birds, reptiles and terrestrial amphibians
FIGURE 6. The Bassian subregion as proposed by Main et al. (1958). Note that the Bassian includes the South-West Australia subregion.
FIGURE 2 in Quantifying vertebrate zoogeographical regions of Australia using geospatial turnover in the species composition of mammals, birds, reptiles and terrestrial amphibians
FIGURE 2. Map of Australia with the location of the 3 Clusters and their corresponding Subclusters (a-c) in relation to the regions.
High-Resolution Mapping of Building Material Stocks in Major Urban Agglomerations in China Based on Multiple Geospatial Data
Open the record for dataset details and reuse information.
Syntactic Geospatial data generated in RDF format
<p>This dataset represents synthetic generated data from CALLISTO data in RDF form. It contains the equivalent of 2 billion triples in TTL format.</p> <p>Each entity contains:</p> <ul> <li>Crop category: "Grasland" and "Bouwland"</li> <li>Geo information: as Multipolygon in Well Known Text (WKT) format</li> <li>Geometry area</li> <li>Geometry length</li> <li>Object id</li> <li>Parcel</li> <li>Rdf:type owl:NamedIndividual</li> </ul> <p>Send an email to: nagpal@infai.org to have access to the dataset if you need to test GeoSparql query engine on big data.</p>
FIGURE 5 in Quantifying vertebrate zoogeographical regions of Australia using geospatial turnover in the species composition of mammals, birds, reptiles and terrestrial amphibians
FIGURE 5. Faunal subregions of Australia by Spencer (1896).
FIGURE 7 in Quantifying vertebrate zoogeographical regions of Australia using geospatial turnover in the species composition of mammals, birds, reptiles and terrestrial amphibians
FIGURE 7. The interim zoogeographic dominions of Australia.
CENTRINNO_Pilot's Geospatial Data
<p>This dataset includes a selection of geospatial data collected on pilots' urban ecosystems, including socio-demographic, ecological and land use data.</p>
A geospatial big data cloud computing-based method for constructing spatiotemporal dataset of dengue influencing factors in Brazil
<p>This datasets includes 12 dengue-associated factors of 418 epi weeks from 2013 to 2020 in microregion-level in Brazil.</p>
[SUMMER - Digital_Twin_beta_release_geospatial_platform_2024-04-29]
<p><span>Source code of the actual Digital Twin (beta version)</span></p>
Spatio-temporal analysis of glacial lakes from 1990 to 2018 in the Kashmir Himalaya, India using geospatial technology
<p>The glacial lakes were identified, delineated, and mapped to observe changes in spatial extent using multi-date/multi-sensor remote sensing data and adequately supplemented by field studies. Landsat imageries were used to delineate the spatial extent of glacial lakes for four time points i.e., 1990, 2000, 2010 and 2018. The total count of lakes as well as their spatial extent showed a discernible increase. The number has increased from 253 in 1990 to 322 in 2018 with a growth rate of 21.4 percent. The area has increased from 18.84 Km<sup>2 </sup>in 1990 to 22.11 Km<sup>2</sup> in 2018 with a growth rate of 14.7 percent. The newly formed glacial lakes including supra glacial lakes were greater in number than the lakes that have disappeared over the study period. All glacial lakes are situated at an elevation of 2700 m asl and 4500 m asl. More than 78 percent of lake expansion in the study region consists largely due to growth of existing glacial lakes. Through the area change analysis, our findings reveal that certain lakes show rapid expansion needing immediate monitoring and observation. In addition to climate variability, the presence of increasing quantities of light trapping particles could be possible causes for expanding of lakes in the Himalayas. Consequently, this study could play a significant role in devising a comprehensive risk assessment plan of potential GLOFs and develop a mechanism for continuous monitoring and management of lakes in the study region.</p>
A comprehensive geospatial database of nearly 100,000 reservoirs in China
<p><strong>Data components</strong></p><p>Folder "CRD v1.1" contains the recorded (5,143) reservoirs from yearbook and document data and all (97,435) reservoirs from CRD v1.1 (China Reservoir Database) two parts:</p><p>• <strong>CRD_v11_all_reservoirs</strong> (in both shapefile format and the comma-separated values (csv) format): This database catalogs the location information of 97,435 reservoirs in China, with an aggregated area of 50,085.21 km2 and an estimated total storage capacity of 979.62 Gt. The attributes of all the CRD v1.1 reservoirs (in all cases) include location information (longitude, latitude, province, prefecture, and county), inundation area, estimated storage capacity, river order, discharge, and residence time of reservoirs.</p><p>• <strong>CRD_v11_record_reservoirs</strong> (in both shapefile and csv): The 5,143 reservoirs in the CRD v1.1 database were directly derived from the yearbook and other documents data, accounting for 59% and 82% of the total reservoir area and storage capacity of the CRD v1.1 database, respectively. This reservoir information was mainly obtained through manual compilation. The attributes of the recorded reservoirs include the longitude and latitude of the reservoir, name, province, prefecture, and county where the reservoir is located, water area, water level of normal storage capacity, storage capacity, reservoir class, main use, and regulation type.</p><h2><strong>Note: Thank you for accessing the CRD v1.1 dataset, which is available through the new link: https://www.scidb.cn/s/zqIFVr; DOI: 10.57760/sciencedb.05331</strong></h2>
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.