Deep learning based automatic grounding line delineation in DInSAR interferograms ...
This dataset contains a small subset of the AIS_cci GLL product, which covers several key glaciers and the corresponding HED-delineated grounding lines generated from our automatic delineation pipeline. A description of the attributes of the AIS_cci GLL product is provided in the Product User Guide....
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Online Access: | https://dx.doi.org/10.5281/zenodo.10785613 https://zenodo.org/doi/10.5281/zenodo.10785613 |
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ftdatacite:10.5281/zenodo.10785613 2024-09-09T19:02:19+00:00 Deep learning based automatic grounding line delineation in DInSAR interferograms ... Ramanath Tarekere, Sindhu 2024 https://dx.doi.org/10.5281/zenodo.10785613 https://zenodo.org/doi/10.5281/zenodo.10785613 en eng Zenodo https://dx.doi.org/10.5281/zenodo.10785612 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 Grounding lines Antarctica Differential SAR Interferometry dataset Dataset 2024 ftdatacite https://doi.org/10.5281/zenodo.1078561310.5281/zenodo.10785612 2024-06-17T10:19:59Z This dataset contains a small subset of the AIS_cci GLL product, which covers several key glaciers and the corresponding HED-delineated grounding lines generated from our automatic delineation pipeline. A description of the attributes of the AIS_cci GLL product is provided in the Product User Guide. We do not indicate the split of the interferograms into training, validation and test sets as the complete AIS_cci dataset is not open-access. We also provide eight double difference interferograms at 100 m pixel size to demonstrate the generation of the features stack. Please note, eight samples are not sufficient to train the neural network to achieve the delineation capability described in our work. The "UUID" attribute in both GeoJSON files is an identifier that links the vector geometries to the interferogram TiFF files. ... Dataset Antarc* Antarctica DataCite |
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Open Polar |
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ftdatacite |
language |
English |
topic |
Grounding lines Antarctica Differential SAR Interferometry |
spellingShingle |
Grounding lines Antarctica Differential SAR Interferometry Ramanath Tarekere, Sindhu Deep learning based automatic grounding line delineation in DInSAR interferograms ... |
topic_facet |
Grounding lines Antarctica Differential SAR Interferometry |
description |
This dataset contains a small subset of the AIS_cci GLL product, which covers several key glaciers and the corresponding HED-delineated grounding lines generated from our automatic delineation pipeline. A description of the attributes of the AIS_cci GLL product is provided in the Product User Guide. We do not indicate the split of the interferograms into training, validation and test sets as the complete AIS_cci dataset is not open-access. We also provide eight double difference interferograms at 100 m pixel size to demonstrate the generation of the features stack. Please note, eight samples are not sufficient to train the neural network to achieve the delineation capability described in our work. The "UUID" attribute in both GeoJSON files is an identifier that links the vector geometries to the interferogram TiFF files. ... |
format |
Dataset |
author |
Ramanath Tarekere, Sindhu |
author_facet |
Ramanath Tarekere, Sindhu |
author_sort |
Ramanath Tarekere, Sindhu |
title |
Deep learning based automatic grounding line delineation in DInSAR interferograms ... |
title_short |
Deep learning based automatic grounding line delineation in DInSAR interferograms ... |
title_full |
Deep learning based automatic grounding line delineation in DInSAR interferograms ... |
title_fullStr |
Deep learning based automatic grounding line delineation in DInSAR interferograms ... |
title_full_unstemmed |
Deep learning based automatic grounding line delineation in DInSAR interferograms ... |
title_sort |
deep learning based automatic grounding line delineation in dinsar interferograms ... |
publisher |
Zenodo |
publishDate |
2024 |
url |
https://dx.doi.org/10.5281/zenodo.10785613 https://zenodo.org/doi/10.5281/zenodo.10785613 |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
https://dx.doi.org/10.5281/zenodo.10785612 |
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.1078561310.5281/zenodo.10785612 |
_version_ |
1809816467336593408 |