MATLAB script for grain images and grain-shape metrics of glacial sediments from Antarctica, Northwest Greenland, and the central Barents Sea ...

This project explores grain-scale signatures of subglacial sediment transport and subglacial hydrologic processes using grain shape and microtexture. We compare grain-shape distributions for grains from meltwater plume deposits to those of subglacial till and ice-proximal diamicton from the same gla...

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Main Authors: Lepp, Allison, Simkins, Lauren M, Anderson, John B, O'Regan, Matt, Winsborrow, Monica, Smith, James A, Hillenbrand, Claus-Dieter, Wellner, Julia S, Prothro, Lindsay O, Podolskiy, Evgeny
Format: Dataset
Language:English
Published: PANGAEA 2023
Subjects:
Online Access:https://dx.doi.org/10.1594/pangaea.961704
https://doi.pangaea.de/10.1594/PANGAEA.961704
id ftdatacite:10.1594/pangaea.961704
record_format openpolar
spelling ftdatacite:10.1594/pangaea.961704 2024-03-31T07:48:49+00:00 MATLAB script for grain images and grain-shape metrics of glacial sediments from Antarctica, Northwest Greenland, and the central Barents Sea ... Lepp, Allison Simkins, Lauren M Anderson, John B O'Regan, Matt Winsborrow, Monica Smith, James A Hillenbrand, Claus-Dieter Wellner, Julia S Prothro, Lindsay O Podolskiy, Evgeny 2023 text/tab-separated-values https://dx.doi.org/10.1594/pangaea.961704 https://doi.pangaea.de/10.1594/PANGAEA.961704 en eng PANGAEA https://dx.doi.org/10.5194/tc-2023-70 https://dx.doi.org/10.31223/x58934 https://dx.doi.org/10.5194/tc-10-1003-2016 https://dx.doi.org/10.1016/j.quascirev.2022.107460 https://dx.doi.org/10.1016/0033-5894(89)90008-2 https://dx.doi.org/10.1016/j.quascirev.2012.01.017 https://dx.doi.org/10.3389/feart.2022.863200 https://dx.doi.org/10.5194/tc-15-4073-2021 https://dx.doi.org/10.1016/j.margeo.2017.09.012 https://dx.doi.org/10.1111/j.1502-3885.2011.00244.x https://dx.doi.org/10.1038/ngeo3012 https://dx.doi.org/10.1038/nature20136 https://dx.doi.org/10.1016/j.quascirev.2013.11.021 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 grain micromorphology meltwater plume deposits sediment transport subglacial hydrology subglacial till Binary Object File content Rotary core drilling Gravity corer Piston corer Kasten corer Jumbo gravity core Percussion corer Grab Ice drill NBP19-02 Nathaniel B. Palmer dataset Dataset 2023 ftdatacite https://doi.org/10.1594/pangaea.96170410.5194/tc-2023-7010.31223/x5893410.5194/tc-10-1003-201610.1016/j.quascirev.2022.10746010.1016/0033-5894(89)90008-210.1016/j.quascirev.2012.01.01710.3389/feart.2022.86320010.5194/tc-15-4073-202110.1016/j.margeo.2017.0 2024-03-04T13:56:14Z This project explores grain-scale signatures of subglacial sediment transport and subglacial hydrologic processes using grain shape and microtexture. We compare grain-shape distributions for grains from meltwater plume deposits to those of subglacial till and ice-proximal diamicton from the same glacial setting. The study incorporates samples from marine sediment cores collected offshore of Ryder Glacier in northwest Greenland, in the central Barents Sea, and Antarctic samples from Marguerite Bay, offshore Thwaites and Pine Island glaciers, and in the western Ross Sea. This dataset contains a MATLAB script used to process grain images and calculate individual grain-shape metrics (including circularity, solidity, and eccentricity), and an Excel spreadsheet containing the grain-shape measurements. Grain images were collected in 2022-23 using a Bettersizer S3 Plus particle size and shape analyzer at the University of Virginia. ... : File descriptions: The excel file GrainShapeMetrics.xlsx contains the values of grain-shape measurements with each study region in a different tab, with the first tab called READ_ME providing details of the metrics, units, references to documentation, and explanations of each column header. The MATLAB script, GrainShapeAnalysis_Binarized.mlx, which is used to process grain images, convert images to binary, and calculate the measurements presented in the Excel file is also included. Sample metadata is available in the Excel file Events_Metadata.xlsx. ... Dataset Antarc* Antarctic Antarctica Barents Sea glacier Greenland Pine Island Ross Sea DataCite Metadata Store (German National Library of Science and Technology) Antarctic Barents Sea Ross Sea Greenland Marguerite ENVELOPE(141.378,141.378,-66.787,-66.787) Marguerite Bay ENVELOPE(-68.000,-68.000,-68.500,-68.500) Ryder ENVELOPE(-68.333,-68.333,-67.566,-67.566) Ryder Glacier ENVELOPE(-67.250,-67.250,-71.116,-71.116)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic grain micromorphology
meltwater plume deposits
sediment transport
subglacial hydrology
subglacial till
Binary Object
File content
Rotary core drilling
Gravity corer
Piston corer
Kasten corer
Jumbo gravity core
Percussion corer
Grab
Ice drill
NBP19-02
Nathaniel B. Palmer
spellingShingle grain micromorphology
meltwater plume deposits
sediment transport
subglacial hydrology
subglacial till
Binary Object
File content
Rotary core drilling
Gravity corer
Piston corer
Kasten corer
Jumbo gravity core
Percussion corer
Grab
Ice drill
NBP19-02
Nathaniel B. Palmer
Lepp, Allison
Simkins, Lauren M
Anderson, John B
O'Regan, Matt
Winsborrow, Monica
Smith, James A
Hillenbrand, Claus-Dieter
Wellner, Julia S
Prothro, Lindsay O
Podolskiy, Evgeny
MATLAB script for grain images and grain-shape metrics of glacial sediments from Antarctica, Northwest Greenland, and the central Barents Sea ...
topic_facet grain micromorphology
meltwater plume deposits
sediment transport
subglacial hydrology
subglacial till
Binary Object
File content
Rotary core drilling
Gravity corer
Piston corer
Kasten corer
Jumbo gravity core
Percussion corer
Grab
Ice drill
NBP19-02
Nathaniel B. Palmer
description This project explores grain-scale signatures of subglacial sediment transport and subglacial hydrologic processes using grain shape and microtexture. We compare grain-shape distributions for grains from meltwater plume deposits to those of subglacial till and ice-proximal diamicton from the same glacial setting. The study incorporates samples from marine sediment cores collected offshore of Ryder Glacier in northwest Greenland, in the central Barents Sea, and Antarctic samples from Marguerite Bay, offshore Thwaites and Pine Island glaciers, and in the western Ross Sea. This dataset contains a MATLAB script used to process grain images and calculate individual grain-shape metrics (including circularity, solidity, and eccentricity), and an Excel spreadsheet containing the grain-shape measurements. Grain images were collected in 2022-23 using a Bettersizer S3 Plus particle size and shape analyzer at the University of Virginia. ... : File descriptions: The excel file GrainShapeMetrics.xlsx contains the values of grain-shape measurements with each study region in a different tab, with the first tab called READ_ME providing details of the metrics, units, references to documentation, and explanations of each column header. The MATLAB script, GrainShapeAnalysis_Binarized.mlx, which is used to process grain images, convert images to binary, and calculate the measurements presented in the Excel file is also included. Sample metadata is available in the Excel file Events_Metadata.xlsx. ...
format Dataset
author Lepp, Allison
Simkins, Lauren M
Anderson, John B
O'Regan, Matt
Winsborrow, Monica
Smith, James A
Hillenbrand, Claus-Dieter
Wellner, Julia S
Prothro, Lindsay O
Podolskiy, Evgeny
author_facet Lepp, Allison
Simkins, Lauren M
Anderson, John B
O'Regan, Matt
Winsborrow, Monica
Smith, James A
Hillenbrand, Claus-Dieter
Wellner, Julia S
Prothro, Lindsay O
Podolskiy, Evgeny
author_sort Lepp, Allison
title MATLAB script for grain images and grain-shape metrics of glacial sediments from Antarctica, Northwest Greenland, and the central Barents Sea ...
title_short MATLAB script for grain images and grain-shape metrics of glacial sediments from Antarctica, Northwest Greenland, and the central Barents Sea ...
title_full MATLAB script for grain images and grain-shape metrics of glacial sediments from Antarctica, Northwest Greenland, and the central Barents Sea ...
title_fullStr MATLAB script for grain images and grain-shape metrics of glacial sediments from Antarctica, Northwest Greenland, and the central Barents Sea ...
title_full_unstemmed MATLAB script for grain images and grain-shape metrics of glacial sediments from Antarctica, Northwest Greenland, and the central Barents Sea ...
title_sort matlab script for grain images and grain-shape metrics of glacial sediments from antarctica, northwest greenland, and the central barents sea ...
publisher PANGAEA
publishDate 2023
url https://dx.doi.org/10.1594/pangaea.961704
https://doi.pangaea.de/10.1594/PANGAEA.961704
long_lat ENVELOPE(141.378,141.378,-66.787,-66.787)
ENVELOPE(-68.000,-68.000,-68.500,-68.500)
ENVELOPE(-68.333,-68.333,-67.566,-67.566)
ENVELOPE(-67.250,-67.250,-71.116,-71.116)
geographic Antarctic
Barents Sea
Ross Sea
Greenland
Marguerite
Marguerite Bay
Ryder
Ryder Glacier
geographic_facet Antarctic
Barents Sea
Ross Sea
Greenland
Marguerite
Marguerite Bay
Ryder
Ryder Glacier
genre Antarc*
Antarctic
Antarctica
Barents Sea
glacier
Greenland
Pine Island
Ross Sea
genre_facet Antarc*
Antarctic
Antarctica
Barents Sea
glacier
Greenland
Pine Island
Ross Sea
op_relation https://dx.doi.org/10.5194/tc-2023-70
https://dx.doi.org/10.31223/x58934
https://dx.doi.org/10.5194/tc-10-1003-2016
https://dx.doi.org/10.1016/j.quascirev.2022.107460
https://dx.doi.org/10.1016/0033-5894(89)90008-2
https://dx.doi.org/10.1016/j.quascirev.2012.01.017
https://dx.doi.org/10.3389/feart.2022.863200
https://dx.doi.org/10.5194/tc-15-4073-2021
https://dx.doi.org/10.1016/j.margeo.2017.09.012
https://dx.doi.org/10.1111/j.1502-3885.2011.00244.x
https://dx.doi.org/10.1038/ngeo3012
https://dx.doi.org/10.1038/nature20136
https://dx.doi.org/10.1016/j.quascirev.2013.11.021
op_rights Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
op_doi https://doi.org/10.1594/pangaea.96170410.5194/tc-2023-7010.31223/x5893410.5194/tc-10-1003-201610.1016/j.quascirev.2022.10746010.1016/0033-5894(89)90008-210.1016/j.quascirev.2012.01.01710.3389/feart.2022.86320010.5194/tc-15-4073-202110.1016/j.margeo.2017.0
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