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- Creator:
- Adam Schneider and Mark Flanner
- Description:
- This dataset contains all data used to generate the figures in The Cryosphere manuscript “Measuring Snow Specific Surface Area with 1.30 and 1.55 micro-meter Bidirectional Reflectance Factors,” by Adam Schneider, Mark Flanner, and Roger De Roo. These data support the theory, calibration, and application of the Near-Infrared Emitting and Reflectance Monitoring Dome (NERD), an instrument engineered to rapidly retrieve surface snow specific surface area in the field. Note that this deposit includes a microCT scan database for natural snowfall samples collected in New Hampshire during 2015-2017, comprised of raw tiff files as well as reconstructions, binarized reconstructions, and some 3D model reconstructions. and Running python scripts generally require that the following packages are installed: NumPy, SciPy, Matplotlib, Pandas, and ipdb (for debugging).
- Keyword:
- Snow specific surface area, Monte Carlo, X-ray micro-computed tomography, SNICAR, Near-Infrared Emitting and Reflectance-Monitoring Dome, Bidirectional reflectance factor, Cryosphere, and 3D
- Discipline:
- Science
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- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:mammals:123037 (Tscherskia TRITON) - WholeBody. Raw Dataset includes 1601 TIF images (each 715 x 1288 x 1 voxel at 0.0493711582967448 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:123037 (Tscherskia TRITON) - WholeBody. Reconstructed Dataset includes 2000 TIF images (each 715 x 1288 x 1 voxel at 0.049371 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Mammalia, Rodentia, Cricetidae, Tscherskia TRITON, 1987305166, computed tomography, X-ray, and 3D
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1987305166
- Discipline:
- Science
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- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:mammals:111984 (Handleyomys ALFAROI ALFAROI) - WholeBody. Raw Dataset includes 1601 TIF images (each 815 x 1310 x 1 voxel at 0.0421497172804555 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:111984 (Handleyomys ALFAROI ALFAROI) - WholeBody. Reconstructed Dataset includes 2000 TIF images (each 815 x 1310 x 1 voxel at 0.042150 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Mammalia, Rodentia, Cricetidae, Handleyomys ALFAROI ALFAROI, 1987286466, computed tomography, X-ray, and 3D
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1987286466
- Discipline:
- Science
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- Creator:
- Trung, Huy-Sinh, Liemohn, Michael W, and Ilie, Raluca
- Description:
- The goal of this research was to understand structures where the solar wind plasma contribution to the total plasma was equal to the ionospheric plasma. This simulation was performed over a simulation time of 12 hours for 4 different plasma compositions for 2 different solar wind profiles., The SWMF used the Block Adaptive Tree Solar wind Roe-type Upwind Scheme version 9.20. It can be found at http://csem.engin.umich.edu/tools/swmf/downloads.php. These data can be processed using the simulation code deposited at the Deep Blue Data record indicated in the "Citation to related material" field., and To cite this data set: Trung, H.-S., Liemohn, M., W., Ilie, R. (2019). 12 hour data for magnetospheric simulations for a multifluid plasma for 8 different configurations [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/fwq2-ey41
- Keyword:
- Space Physics, Magnetospheres, and 3D
- Citation to related publication:
- Trung, H.-S., Liemohn, M.W. Ilie, R. (2019). Steady State Characteristics of the Terrestrial Geopause [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/7w13-kq27
- Discipline:
- Science