Supraglacial lakes and channels in West Antarctica and Antarctic Peninsula during January 2017 - Sentinel-2 Group 1

The maximum extent of supraglacial lakes and channels in West Antarctica and the Antarctic Peninsula in January 2017 was produced by a Dual-NDWI (Normalised Difference Water Index) approach with thresholds. >2000 individual scenes were captured by Sentinel-2 (S2) and Landsat-8 (L8) satellite sens...

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Main Authors: Corr, Diarmuid, Leeson, Amber, McMillan, Mal, Zhang, Ce, Barnes, Thomas
Format: Dataset
Language:unknown
Published: Zenodo 2021
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.5589494
https://zenodo.org/record/5589494
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record_format openpolar
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
description The maximum extent of supraglacial lakes and channels in West Antarctica and the Antarctic Peninsula in January 2017 was produced by a Dual-NDWI (Normalised Difference Water Index) approach with thresholds. >2000 individual scenes were captured by Sentinel-2 (S2) and Landsat-8 (L8) satellite sensors during the entire month of January 2017. To obtain maximum coverage on the cloudy Antarctic Peninsula, the time period is extended to February 10, 2017 over this region. This dataset consists of the maximum extent of supraglacial hydrological activity during January 2017 and detailed 10,478 supraglacial features (10,223 lakes and 255 channels), with cumulative area 119.4 square km in total on the West Antarctic ice sheet and Antarctic Peninsula. In addition to the final product, the supraglacial hydrological features from both sensors (23,389 polygons for S2 and 17,571 polygons for L8) overlapping the final map are included. The supraglacial lake and channel polygons are available as digital GIS, Geographic Information System, shapefiles (.shp) and GeoJSON files as well as Google Earth format (.kmz). The code used to produce the lake and channel dataset for each sensor (S2 and L8) is implemented using Python, and can be accessed on Zenodo (https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.4906097&data=04%7C01%7Ccorrd%40live.lancs.ac.uk%7Ce16045ed14e34f2cb4f108d92b70565e%7C9c9bcd11977a4e9ca9a0bc734090164a%7C0%7C0%7C637588586902880130%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&sdata=JPsWDkSk9wqxEcoxMGWzbNgleTFB1NoIFn7t0WlDg3Q%3D&reserved=0) . Landsat-8 and Sentinel-2 imagery are freely available at (https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fearthexplorer.usgs.gov%2F&data=04%7C01%7Ccorrd%40live.lancs.ac.uk%7Ce16045ed14e34f2cb4f108d92b70565e%7C9c9bcd11977a4e9ca9a0bc734090164a%7C0%7C0%7C637588586902880130%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&sdata=RidpbAMFz28isbZM6vNZWPMTdl3bl5OxO3SVWvBu6MQ%3D&reserved=0) and (https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fscihub.copernicus.eu%2F&data=04%7C01%7Ccorrd%40live.lancs.ac.uk%7Ce16045ed14e34f2cb4f108d92b70565e%7C9c9bcd11977a4e9ca9a0bc734090164a%7C0%7C0%7C637588586902880130%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&sdata=lZINlehD3i%2BN%2BPSVZgSJnZa%2FruFq2vGHoEnkQGMmq%2Fg%3D&reserved=0), respectively. The products provide a scientific benchmark to monitor the development of these features in a warming climate, and thus enhancing our capability to predict the calving and collapse of any ice shelves in the future. The results provide a baseline for future monitoring of supraglacial hydrology and can be particularly useful to train supervised machine learning algorithms. The lake and channel dataset will be valuable as training data for pixel-based or object-based approaches to map large-scale features automatically using machine learning. This dataset can also provide an a-priori lake distribution for studies incorporating synthetic-aperture radar, SAR and other sensors and platforms. Alongside Sentinel-2 Group 2, this dataset provides the 23,389 polygons from S2 imagery. : This work was supported by the European Space Agency 4D Antarctica project (contract no. 5 4000128611/19/IDT) and a UK Engineering and Physical Sciences Research Council PhD award.
format Dataset
author Corr, Diarmuid
Leeson, Amber
McMillan, Mal
Zhang, Ce
Barnes, Thomas
spellingShingle Corr, Diarmuid
Leeson, Amber
McMillan, Mal
Zhang, Ce
Barnes, Thomas
Supraglacial lakes and channels in West Antarctica and Antarctic Peninsula during January 2017 - Sentinel-2 Group 1
author_facet Corr, Diarmuid
Leeson, Amber
McMillan, Mal
Zhang, Ce
Barnes, Thomas
author_sort Corr, Diarmuid
title Supraglacial lakes and channels in West Antarctica and Antarctic Peninsula during January 2017 - Sentinel-2 Group 1
title_short Supraglacial lakes and channels in West Antarctica and Antarctic Peninsula during January 2017 - Sentinel-2 Group 1
title_full Supraglacial lakes and channels in West Antarctica and Antarctic Peninsula during January 2017 - Sentinel-2 Group 1
title_fullStr Supraglacial lakes and channels in West Antarctica and Antarctic Peninsula during January 2017 - Sentinel-2 Group 1
title_full_unstemmed Supraglacial lakes and channels in West Antarctica and Antarctic Peninsula during January 2017 - Sentinel-2 Group 1
title_sort supraglacial lakes and channels in west antarctica and antarctic peninsula during january 2017 - sentinel-2 group 1
publisher Zenodo
publishDate 2021
url https://dx.doi.org/10.5281/zenodo.5589494
https://zenodo.org/record/5589494
geographic Antarctic
The Antarctic
Antarctic Peninsula
West Antarctica
West Antarctic Ice Sheet
geographic_facet Antarctic
The Antarctic
Antarctic Peninsula
West Antarctica
West Antarctic Ice Sheet
genre Antarc*
Antarctic
Antarctic Peninsula
Antarctica
Ice Sheet
Ice Shelves
West Antarctica
genre_facet Antarc*
Antarctic
Antarctic Peninsula
Antarctica
Ice Sheet
Ice Shelves
West Antarctica
op_relation https://dx.doi.org/10.5281/zenodo.5589522
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https://dx.doi.org/10.5281/zenodo.5589525
https://dx.doi.org/10.5281/zenodo.5589493
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.5589494
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spelling ftdatacite:10.5281/zenodo.5589494 2023-05-15T13:48:40+02:00 Supraglacial lakes and channels in West Antarctica and Antarctic Peninsula during January 2017 - Sentinel-2 Group 1 Corr, Diarmuid Leeson, Amber McMillan, Mal Zhang, Ce Barnes, Thomas 2021 https://dx.doi.org/10.5281/zenodo.5589494 https://zenodo.org/record/5589494 unknown Zenodo https://dx.doi.org/10.5281/zenodo.5589522 https://dx.doi.org/10.5281/zenodo.5588496 https://dx.doi.org/10.5281/zenodo.5589460 https://dx.doi.org/10.5281/zenodo.5589525 https://dx.doi.org/10.5281/zenodo.5589493 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.5589494 https://doi.org/10.5281/zenodo.5589522 https://doi.org/10.5281/zenodo.5588496 https://doi.org/10.5281/zenodo.5589460 https://doi.org/10.5281/zenodo.5589525 https://doi.org/10.5281/zenodo.5589493 2021-11-05T12:55:41Z The maximum extent of supraglacial lakes and channels in West Antarctica and the Antarctic Peninsula in January 2017 was produced by a Dual-NDWI (Normalised Difference Water Index) approach with thresholds. >2000 individual scenes were captured by Sentinel-2 (S2) and Landsat-8 (L8) satellite sensors during the entire month of January 2017. To obtain maximum coverage on the cloudy Antarctic Peninsula, the time period is extended to February 10, 2017 over this region. This dataset consists of the maximum extent of supraglacial hydrological activity during January 2017 and detailed 10,478 supraglacial features (10,223 lakes and 255 channels), with cumulative area 119.4 square km in total on the West Antarctic ice sheet and Antarctic Peninsula. In addition to the final product, the supraglacial hydrological features from both sensors (23,389 polygons for S2 and 17,571 polygons for L8) overlapping the final map are included. The supraglacial lake and channel polygons are available as digital GIS, Geographic Information System, shapefiles (.shp) and GeoJSON files as well as Google Earth format (.kmz). The code used to produce the lake and channel dataset for each sensor (S2 and L8) is implemented using Python, and can be accessed on Zenodo (https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.4906097&data=04%7C01%7Ccorrd%40live.lancs.ac.uk%7Ce16045ed14e34f2cb4f108d92b70565e%7C9c9bcd11977a4e9ca9a0bc734090164a%7C0%7C0%7C637588586902880130%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&sdata=JPsWDkSk9wqxEcoxMGWzbNgleTFB1NoIFn7t0WlDg3Q%3D&reserved=0) . Landsat-8 and Sentinel-2 imagery are freely available at (https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fearthexplorer.usgs.gov%2F&data=04%7C01%7Ccorrd%40live.lancs.ac.uk%7Ce16045ed14e34f2cb4f108d92b70565e%7C9c9bcd11977a4e9ca9a0bc734090164a%7C0%7C0%7C637588586902880130%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&sdata=RidpbAMFz28isbZM6vNZWPMTdl3bl5OxO3SVWvBu6MQ%3D&reserved=0) and (https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fscihub.copernicus.eu%2F&data=04%7C01%7Ccorrd%40live.lancs.ac.uk%7Ce16045ed14e34f2cb4f108d92b70565e%7C9c9bcd11977a4e9ca9a0bc734090164a%7C0%7C0%7C637588586902880130%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&sdata=lZINlehD3i%2BN%2BPSVZgSJnZa%2FruFq2vGHoEnkQGMmq%2Fg%3D&reserved=0), respectively. The products provide a scientific benchmark to monitor the development of these features in a warming climate, and thus enhancing our capability to predict the calving and collapse of any ice shelves in the future. The results provide a baseline for future monitoring of supraglacial hydrology and can be particularly useful to train supervised machine learning algorithms. The lake and channel dataset will be valuable as training data for pixel-based or object-based approaches to map large-scale features automatically using machine learning. This dataset can also provide an a-priori lake distribution for studies incorporating synthetic-aperture radar, SAR and other sensors and platforms. Alongside Sentinel-2 Group 2, this dataset provides the 23,389 polygons from S2 imagery. : This work was supported by the European Space Agency 4D Antarctica project (contract no. 5 4000128611/19/IDT) and a UK Engineering and Physical Sciences Research Council PhD award. Dataset Antarc* Antarctic Antarctic Peninsula Antarctica Ice Sheet Ice Shelves West Antarctica DataCite Metadata Store (German National Library of Science and Technology) Antarctic The Antarctic Antarctic Peninsula West Antarctica West Antarctic Ice Sheet