Permafrost signature dataset ...
Dataset for the comparison between permafrost and non permafrost meandering rivers extracted with PyRIS from Landsat imagery. The dataset is split in two folders for permafrost and non permafrost river, with a subfolder for each rivers. In the rivers subfolders there is an axis folder, containing al...
Main Authors: | , , , , |
---|---|
Format: | Dataset |
Language: | unknown |
Published: |
Zenodo
2024
|
Subjects: | |
Online Access: | https://dx.doi.org/10.5281/zenodo.10837908 https://zenodo.org/doi/10.5281/zenodo.10837908 |
id |
ftdatacite:10.5281/zenodo.10837908 |
---|---|
record_format |
openpolar |
spelling |
ftdatacite:10.5281/zenodo.10837908 2024-04-28T08:35:28+00:00 Permafrost signature dataset ... Bonanomi, Riccardo Ragno, Niccolò Crivellaro, Marta Monegaglia, Federico Tubino, Marco 2024 https://dx.doi.org/10.5281/zenodo.10837908 https://zenodo.org/doi/10.5281/zenodo.10837908 unknown Zenodo https://dx.doi.org/10.5281/zenodo.10837156 https://dx.doi.org/10.5281/zenodo.10837907 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 dataset Dataset 2024 ftdatacite https://doi.org/10.5281/zenodo.1083790810.5281/zenodo.1083715610.5281/zenodo.10837907 2024-04-02T11:43:54Z Dataset for the comparison between permafrost and non permafrost meandering rivers extracted with PyRIS from Landsat imagery. The dataset is split in two folders for permafrost and non permafrost river, with a subfolder for each rivers. In the rivers subfolders there is an axis folder, containing all the axis files extracted from the river masks, and there can be a migration folder, with all the data for the axis migration evaluation, where this was possible. All the files are in the '.npy' format produced and read by the Python package Numpy and the structure of the files is described in the PyRIS manual, at https://doi.org/10.5281/zenodo.10837156. ... Dataset permafrost DataCite Metadata Store (German National Library of Science and Technology) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
description |
Dataset for the comparison between permafrost and non permafrost meandering rivers extracted with PyRIS from Landsat imagery. The dataset is split in two folders for permafrost and non permafrost river, with a subfolder for each rivers. In the rivers subfolders there is an axis folder, containing all the axis files extracted from the river masks, and there can be a migration folder, with all the data for the axis migration evaluation, where this was possible. All the files are in the '.npy' format produced and read by the Python package Numpy and the structure of the files is described in the PyRIS manual, at https://doi.org/10.5281/zenodo.10837156. ... |
format |
Dataset |
author |
Bonanomi, Riccardo Ragno, Niccolò Crivellaro, Marta Monegaglia, Federico Tubino, Marco |
spellingShingle |
Bonanomi, Riccardo Ragno, Niccolò Crivellaro, Marta Monegaglia, Federico Tubino, Marco Permafrost signature dataset ... |
author_facet |
Bonanomi, Riccardo Ragno, Niccolò Crivellaro, Marta Monegaglia, Federico Tubino, Marco |
author_sort |
Bonanomi, Riccardo |
title |
Permafrost signature dataset ... |
title_short |
Permafrost signature dataset ... |
title_full |
Permafrost signature dataset ... |
title_fullStr |
Permafrost signature dataset ... |
title_full_unstemmed |
Permafrost signature dataset ... |
title_sort |
permafrost signature dataset ... |
publisher |
Zenodo |
publishDate |
2024 |
url |
https://dx.doi.org/10.5281/zenodo.10837908 https://zenodo.org/doi/10.5281/zenodo.10837908 |
genre |
permafrost |
genre_facet |
permafrost |
op_relation |
https://dx.doi.org/10.5281/zenodo.10837156 https://dx.doi.org/10.5281/zenodo.10837907 |
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/10.5281/zenodo.1083790810.5281/zenodo.1083715610.5281/zenodo.10837907 |
_version_ |
1797567564119801856 |