Datasets for "Unexplored Antarctic meteorite collection sites revealed through machine learning"

This archive provides datasets related to the following publication: V. Tollenaar, H. Zekollari, S. Lhermitte, D. Tax, V. Debaille, S. Goderis, P. Claeys, F. Pattyn, Unexplored Antarctic meteorite collection sites revealed through machine learning. Science Advances 8, eabj8138 (2022). DOI:10.1126/sc...

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Main Authors: Tollenaar, Veronica, Zekollari, Harry, Lhermitte, Stef, Tax, David M.J., Debaille, Vinciane, Goderis, Steven, Claeys, Philippe, Pattyn, Frank
Format: Other/Unknown Material
Language:English
Published: Zenodo 2021
Subjects:
Online Access:https://doi.org/10.5281/zenodo.5749753
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record_format openpolar
spelling ftzenodo:oai:zenodo.org:5749753 2024-09-15T17:41:01+00:00 Datasets for "Unexplored Antarctic meteorite collection sites revealed through machine learning" Tollenaar, Veronica Zekollari, Harry Lhermitte, Stef Tax, David M.J. Debaille, Vinciane Goderis, Steven Claeys, Philippe Pattyn, Frank 2021-12-02 https://doi.org/10.5281/zenodo.5749753 eng eng Zenodo https://zenodo.org/communities/amgclabpublications https://doi.org/10.5281/zenodo.5749752 https://doi.org/10.5281/zenodo.5749753 oai:zenodo.org:5749753 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/other 2021 ftzenodo https://doi.org/10.5281/zenodo.574975310.5281/zenodo.5749752 2024-07-26T12:53:45Z This archive provides datasets related to the following publication: V. Tollenaar, H. Zekollari, S. Lhermitte, D. Tax, V. Debaille, S. Goderis, P. Claeys, F. Pattyn, Unexplored Antarctic meteorite collection sites revealed through machine learning. Science Advances 8, eabj8138 (2022). DOI:10.1126/sciadv.abj8138 Contact: Veronica Tollenaar, Veronica.Tollenaar@ulb.be Users should cite the original publication when using all or part of the data. About the datasets: it includes a shapefile with the outline of the 613 Meteorite Stranding Zones (Fig. 7, "613MSZs.zip"), the observations used for classification, and the continent-wide probability to find meteorites (at 450-meter resolution, Fig. 5, "positive_classified.nc"). References to the literature are provided in the corresponding publication. Meteorite locations are based on the Meteoritical Bulletin Database (available at https://www.lpi.usra.edu/meteor/). - bias_above200m1kmbuff_expanded_dissolved: shapefile of polygons of unlabelled observations - meteorite_locations_raw.csv: contains locations of meteorite finds as defined in the meteoritical bulletin consulted on 05/07/2019 - meteorite_types.csv: contains meteorite names and types as defined in the meteoritical bulletin consulted on 05/07/2019 - validation_neg.csv: contains locations of negative observations used for validation - TEST_neg.csv: contains locations of negative test observations - TEST_pos.csv: contains locations of positive test obesrvations - MSZs_ranked: shapefile of ranked meteorite stranding zones - Test_neg4326: shapefile of locations used as negative test data - Cal_neg4326: shapefile of locations used as negative calibration/validation data - TestMSZs_pos4326: shapefile of locations used as positive test data in MSZ-level assesment - 613MSZs: shapefile of outlines of meteorite stranding zones - positive_classified.nc: netcdf of positive classified observations with their estimated a posteriori probabilities Other/Unknown Material Antarc* Antarctic Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language English
description This archive provides datasets related to the following publication: V. Tollenaar, H. Zekollari, S. Lhermitte, D. Tax, V. Debaille, S. Goderis, P. Claeys, F. Pattyn, Unexplored Antarctic meteorite collection sites revealed through machine learning. Science Advances 8, eabj8138 (2022). DOI:10.1126/sciadv.abj8138 Contact: Veronica Tollenaar, Veronica.Tollenaar@ulb.be Users should cite the original publication when using all or part of the data. About the datasets: it includes a shapefile with the outline of the 613 Meteorite Stranding Zones (Fig. 7, "613MSZs.zip"), the observations used for classification, and the continent-wide probability to find meteorites (at 450-meter resolution, Fig. 5, "positive_classified.nc"). References to the literature are provided in the corresponding publication. Meteorite locations are based on the Meteoritical Bulletin Database (available at https://www.lpi.usra.edu/meteor/). - bias_above200m1kmbuff_expanded_dissolved: shapefile of polygons of unlabelled observations - meteorite_locations_raw.csv: contains locations of meteorite finds as defined in the meteoritical bulletin consulted on 05/07/2019 - meteorite_types.csv: contains meteorite names and types as defined in the meteoritical bulletin consulted on 05/07/2019 - validation_neg.csv: contains locations of negative observations used for validation - TEST_neg.csv: contains locations of negative test observations - TEST_pos.csv: contains locations of positive test obesrvations - MSZs_ranked: shapefile of ranked meteorite stranding zones - Test_neg4326: shapefile of locations used as negative test data - Cal_neg4326: shapefile of locations used as negative calibration/validation data - TestMSZs_pos4326: shapefile of locations used as positive test data in MSZ-level assesment - 613MSZs: shapefile of outlines of meteorite stranding zones - positive_classified.nc: netcdf of positive classified observations with their estimated a posteriori probabilities
format Other/Unknown Material
author Tollenaar, Veronica
Zekollari, Harry
Lhermitte, Stef
Tax, David M.J.
Debaille, Vinciane
Goderis, Steven
Claeys, Philippe
Pattyn, Frank
spellingShingle Tollenaar, Veronica
Zekollari, Harry
Lhermitte, Stef
Tax, David M.J.
Debaille, Vinciane
Goderis, Steven
Claeys, Philippe
Pattyn, Frank
Datasets for "Unexplored Antarctic meteorite collection sites revealed through machine learning"
author_facet Tollenaar, Veronica
Zekollari, Harry
Lhermitte, Stef
Tax, David M.J.
Debaille, Vinciane
Goderis, Steven
Claeys, Philippe
Pattyn, Frank
author_sort Tollenaar, Veronica
title Datasets for "Unexplored Antarctic meteorite collection sites revealed through machine learning"
title_short Datasets for "Unexplored Antarctic meteorite collection sites revealed through machine learning"
title_full Datasets for "Unexplored Antarctic meteorite collection sites revealed through machine learning"
title_fullStr Datasets for "Unexplored Antarctic meteorite collection sites revealed through machine learning"
title_full_unstemmed Datasets for "Unexplored Antarctic meteorite collection sites revealed through machine learning"
title_sort datasets for "unexplored antarctic meteorite collection sites revealed through machine learning"
publisher Zenodo
publishDate 2021
url https://doi.org/10.5281/zenodo.5749753
genre Antarc*
Antarctic
genre_facet Antarc*
Antarctic
op_relation https://zenodo.org/communities/amgclabpublications
https://doi.org/10.5281/zenodo.5749752
https://doi.org/10.5281/zenodo.5749753
oai:zenodo.org:5749753
op_rights info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5281/zenodo.574975310.5281/zenodo.5749752
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