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.
8
datasets available to search
ShareScore release 0.9.0
Dataset results
8 results for “Urban boundaries”
City boundary and urban district boundaries, Vienna, 1920
<p><strong>This data repository</strong> includes geospatial datasets on city and urban district boundaries as well as background data.</p> <p>In detail, the following datasets are included:</p> <ol> <li>City boundary 1920 (CB_1920.shp)</li> <li>Urban district boundaries 1920 (UDB_1920.shp)</li> <li>Background data <ol> <li>Vienna and surroundings map (VSM.tif). Retrieved from <a href="http://wais.wien.gv.at//archive.xhtml?id=Stueck++00000461ma8KartoSlg#Stueck__00000461ma8KartoSlg">Municipal and provincial archives of Vienna</a>. Georeferenced by the authors.</li> <li>Building age map 1920 (BAM.tif). Retrieved from <a href="http://wais.wien.gv.at//archive.xhtml?id=Stueck++A629C2CD-82BD-43FE-B474-D49161ADF381#Stueck__A629C2CD-82BD-43FE-B474-D49161ADF381">Municipal and provincial archives of Vienna</a>. Georeferenced by the authors.</li> <li>City boundary (raw data). Complementary to CB_1920.shp</li> <li>Urban district boundaries (raw data). Complementary to UDB_1920.shp</li> <li>City boundary 2020 (CB_2020.shp). Dataset " Verwaltungsgrenzen (VGD) - Stichtagsdaten Wien" retrieved from Federal Office of Metrology and Surveying via <a href="https://www.data.gv.at">Open Data Österreich</a>. Modified by the authors.</li> </ol> </li> </ol>
The urban boundaries of 196 cities in China for deriving urban precipitation intensity-duration-frequency curves
<p>The shapefiles of urban boundaries of 196 cities in China are generated by processing and filtering the outputs of Li et al., (2018). Mapping global urban boundaries from the global artificial impervious area (GAIA) data. </p>
Global Hierarchical Urban Boundaries (GHUB)
<p>Global Hierarchical Urban Boundaries (GHUB) vector Database 2018.</p> <p>GeoPackage (gpkg) format.</p> <p>Please cite the following article when using this data,</p> <p>Xu, Z., Jiao, L., Lan, T., Zhou, Z., Cui, H., Li, C., Xu, G., & Liu, Y. (2021). Mapping hierarchical urban boundaries for global urban settlements. <em>International Journal of Applied Earth Observation and Geoinformation</em>, <em>103</em>, 102480. https://doi.org/10.1016/j.jag.2021.102480</p> <p> </p>
Data from the article "Modulation of wintertime canopy Urban Heat Island (CUHI) intensity in Beijing by synoptic weather pattern in planetary boundary layer"
<p>The link includes four datasets, "pcttype" is weather typing data, "pblh" is PBLH data, "uhii-UV" is the mean value of CUHII and wind direction UV of all urban stations, and "uhii-sws" is the value of CUHII, wind speed and wind direction of all urban stations.</p>
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
<p>This dataset accompanies the GMD article 'A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0' (https://doi.org/10.5194/egusphere-2024-96).</p> <ul> <li>The input files to run the presented cases using uDALES are contained in 'inputs'.</li> <li>The model outputs are contained in separate folders: 'XCC', 'indoor-outdoor', 'XCB', and 'SEB'. When downloaded, move into a folder called 'outputs' so that the paths defined in the scripts work as intended (see below).</li> <li>The Matlab scripts to plot the figures are contained in 'scripts'.</li> <li>The figures shown in the article are contained in 'figures'.</li> </ul>
Data from: A worldwide model for boundaries of urban settlements
The shape of urban settlements plays a fundamental role in their sustainable planning. Properly defining the boundaries of cities is challenging and remains an open problem in the science of cities. Here, we propose a worldwide model to define urban settlements beyond their administrative boundaries through a bottom-up approach that takes into account geographical biases intrinsically associated with most societies around the world, and reflected in their different regional growing dynamics. The generality of the model allows one to study the scaling laws of cities at all geographical levels: countries, continents and the entire world. Our definition of cities is robust and holds to one of the most famous results in social sciences: Zipf's law. According to our results, the largest cities in the world are not in line with what was recently reported by the United Nations. For example, we find that the largest city in the world is an agglomeration of several small settlements close to each other, connecting three large settlements: Alexandria, Cairo and Luxor. Our definition of cities opens the doors to the study of the economy of cities in a systematic way independently of arbitrary definitions that employ administrative boundaries.
Data from: A worldwide model for boundaries of urban settlements
Open the record for dataset details and reuse information.
Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): National Administrative Boundaries
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): National Administrative Boundaries are derived from the land area grid to show the outlines of pixels (cells) that contain administrative Units in GRUMPv1 on a per-country/territory basis. They are derived from the pixels as polygons and thus have rectilinear boundaries at a large scale. The polygons that outline the countries and territories are not official representations; rather they represent the area covered by the statistical data as provided. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).
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.