Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet - data

Data used in our paper "Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet". This dataset includes all training, validation and testing images used for the convolutional neural network described in our paper (CNN_data.zip), shapefiles...

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Bibliographic Details
Main Authors: Dunmire, Devon, Banwell, Alison F., Nander Wever, Lenaerts, Jan T.M., Rajashree Tri Datta
Format: Dataset
Language:unknown
Published: Zenodo 2021
Subjects:
Greenland
Ice Sheet
Online Access:https://dx.doi.org/10.5281/zenodo.4813833
https://zenodo.org/record/4813833
id ftdatacite:10.5281/zenodo.4813833
record_format openpolar
spelling ftdatacite:10.5281/zenodo.4813833 2023-05-15T16:25:29+02:00 Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet - data Dunmire, Devon Banwell, Alison F. Nander Wever Lenaerts, Jan T.M. Rajashree Tri Datta 2021 https://dx.doi.org/10.5281/zenodo.4813833 https://zenodo.org/record/4813833 unknown Zenodo https://dx.doi.org/10.5281/zenodo.4813832 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess CC-BY dataset Dataset 2021 ftdatacite https://doi.org/10.5281/zenodo.4813833 https://doi.org/10.5281/zenodo.4813832 2021-11-05T12:55:41Z Data used in our paper "Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet". This dataset includes all training, validation and testing images used for the convolutional neural network described in our paper (CNN_data.zip), shapefiles for all detected buried and surface lakes (lakes.zip), and our convolutional neural network model (CNN_model.zip). Dataset Greenland Ice Sheet DataCite Metadata Store (German National Library of Science and Technology) Greenland
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
description Data used in our paper "Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet". This dataset includes all training, validation and testing images used for the convolutional neural network described in our paper (CNN_data.zip), shapefiles for all detected buried and surface lakes (lakes.zip), and our convolutional neural network model (CNN_model.zip).
format Dataset
author Dunmire, Devon
Banwell, Alison F.
Nander Wever
Lenaerts, Jan T.M.
Rajashree Tri Datta
spellingShingle Dunmire, Devon
Banwell, Alison F.
Nander Wever
Lenaerts, Jan T.M.
Rajashree Tri Datta
Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet - data
author_facet Dunmire, Devon
Banwell, Alison F.
Nander Wever
Lenaerts, Jan T.M.
Rajashree Tri Datta
author_sort Dunmire, Devon
title Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet - data
title_short Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet - data
title_full Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet - data
title_fullStr Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet - data
title_full_unstemmed Contrasting regional variability of buried meltwater extent over two years across the Greenland Ice Sheet - data
title_sort contrasting regional variability of buried meltwater extent over two years across the greenland ice sheet - data
publisher Zenodo
publishDate 2021
url https://dx.doi.org/10.5281/zenodo.4813833
https://zenodo.org/record/4813833
geographic Greenland
geographic_facet Greenland
genre Greenland
Ice Sheet
genre_facet Greenland
Ice Sheet
op_relation https://dx.doi.org/10.5281/zenodo.4813832
op_rights Open Access
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
info:eu-repo/semantics/openAccess
op_rightsnorm CC-BY
op_doi https://doi.org/10.5281/zenodo.4813833
https://doi.org/10.5281/zenodo.4813832
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