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Illinois Data Bank Dataset Search Results
Dataset Search Results
published: 2020-01-27
Cisneros, Julia (2020): Data for: Dunes in the world’s big rivers are characterised by low-angle leeside slopes and a complex shape. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7525764_V2
Morphologic data of dunes in the World's big rivers. Morphologic descriptors for large dunes include: dune height, dune mean leeside angle, dune maximum leeside angle, dune wavelength, dune flow depth (at the crest), and the fractional height of the maximum slope on the leeside for each dune. Morphologic descriptors for small dunes include: dune height, dune mean leeside angle, dune maximum leeside angle, dune wavelength, and dune flow depth (at the crest).
keywords:
dune; bedform; rivers; morphology;
published: 2019-12-17
Zhang, Yujie; Araiza Bravo, Rodrigo; Chitambar, Eric; Lorenz, Virginia (2019): Dataset for "Channel Activation of CHSH Nonlocality". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3686727_V1
This dataset provides the raw data, code and related figures for the paper, "Channel Activation of CHSH Nonlocality"
keywords:
Super-activation; Non-locality breaking channel
published: 2018-06-05
Soliman, Aiman; Mackay, Andrew; Schmidt , Arthur; Allan, Brian; Wang, Shaowen (2018): Dataset for: Quantifying the geographic distribution of building coverage across the US for urban sustainability studies. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4137411_V1
A complete building coverage area dataset (i.e. area occupied by building structures, excluding other built surfaces such as roads, parking lots, and public parks) at the level of census block groups for the contiguous United States (CONUS). The dataset was assembled based on an ensemble prediction of nonlinear hierarchical models to account for spatial heterogeneities in the distribution of built surfaces across different urban communities. Percentage of impervious land and housing density were used as predictors of the estimated area of buildings and cross-validation results showed that the product estimated area represented by buildings with a mean error of 0.049 %.
keywords:
Building Coverage Area; Urban Geography; Regional; Sustainability; US Census Block Groups; CONUS Data
published: 2019-03-05
Zhao, Jifu (2019): UIUC Campus Gamma-Ray Radiation Data. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9119873_V1
This dataset contains the raw nuclear background radiation data collected in the engineering campus of University of Illinois at Urbana-Champaign. It contains three columns, x, y, and counts, which corresponds to longitude, latitude, and radiation count rate (counts per second). In addition to the original background radiation data, there are several separate files that contain the simulated radioactive sources. For more detailed README file, please refer to this documentation: <a href= "https://www.dropbox.com/s/xjhmeog7fvijml7/README.pdf?dl=0">https://www.dropbox.com/s/xjhmeog7fvijml7/README.pdf?dl=0</a>
keywords:
Nuclear Radiation
published: 2018-05-16
Lewis, Quinn; Bruce, Rhoads (2018): Lewis, Quinn; Bruce, Rhoads (2018): Data from: LSPIV Measurements of Two-dimensional Flow Structure in Streams using Small Unmanned Aerial Systems: Parts 1 and 2. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0360762_V1
These data are for two companion papers on use of LSPIV obtained from UAS (i.e. drones) to measure flow structure in streams. The LSPIV1 folder contains spreadsheet data used in each case referred to in Table 1 in the manuscript. In the spreadsheets, there is a cell that denotes which figure was constructed with which data. The LSPIV2 folder contains spreadsheets with data used for the constructed figures, and are labeled by figure.
keywords:
LSPIV; drone; UAS; flow structure; rivers
published: 2017-12-12
Zhang, Qian; Li, Chunyan (2017): Meterology and ocean data collected at LSU WAVCIS Lab. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2436375_V1
This dataset includes both meteorology and oceanography data collected at stations (CSI03, CSI06, and CSI09) near the Gulf of Mexico from the LSU WAVCIS (Waves-Current-Surge Information System) lab. The associated data analysis visualization is also saved in separate directories.
keywords:
WAVCIS; Gulf of Mexico; Meteorology; Oceanography