Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series
The usability of multispectral satellite data for detecting and monitoring supraglacial meltwater ponds has been demonstrated for western Greenland. For a multitemporal analysis of large regions or entire Greenland, largely automated processing routines are required. Here, we present a sequence of a...
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Online Access: | https://epic.awi.de/id/eprint/53576/ https://epic.awi.de/id/eprint/53576/1/remotesensing-13-00205-v2.pdf https://hdl.handle.net/10013/epic.2b53132c-33d6-4a3e-8d6b-a3b7f94bef8b https://hdl.handle.net/ |
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ftawi:oai:epic.awi.de:53576 2023-05-15T16:21:06+02:00 Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series Hochreuther, Philipp Neckel, Niklas Reimann, Nathalie Humbert, Angelika Braun, Matthias 2021-01 application/pdf https://epic.awi.de/id/eprint/53576/ https://epic.awi.de/id/eprint/53576/1/remotesensing-13-00205-v2.pdf https://hdl.handle.net/10013/epic.2b53132c-33d6-4a3e-8d6b-a3b7f94bef8b https://hdl.handle.net/ unknown https://epic.awi.de/id/eprint/53576/1/remotesensing-13-00205-v2.pdf https://hdl.handle.net/ Hochreuther, P. , Neckel, N. orcid:0000-0003-4300-5488 , Reimann, N. , Humbert, A. and Braun, M. (2021) Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series , Remote Sensing, 13 , p. 205 . doi:10.3390/rs13020205 <https://doi.org/10.3390/rs13020205> , hdl:10013/epic.2b53132c-33d6-4a3e-8d6b-a3b7f94bef8b EPIC3Remote Sensing, 13, pp. 205 Article isiRev 2021 ftawi https://doi.org/10.3390/rs13020205 2021-12-24T15:46:07Z The usability of multispectral satellite data for detecting and monitoring supraglacial meltwater ponds has been demonstrated for western Greenland. For a multitemporal analysis of large regions or entire Greenland, largely automated processing routines are required. Here, we present a sequence of algorithms that allow for an automated Sentinel-2 data search, download, processing, and generation of a consistent and dense melt pond area time-series based on open-source software. We test our approach for a ~82,000 km2 area at the 79°N Glacier (Nioghalvfjerdsbrae) in northeast Greenland, covering the years 2016, 2017, 2018 and 2019. Our lake detection is based on the ratio of the blue and red visible bands using a minimum threshold. To remove false classification caused by the similar spectra of shadow and water on ice, we implement a shadow model to mask out topographically induced artifacts. We identified 880 individual lakes, traceable over 479 time-steps throughout 2016-2019, with an average size of 64,212 m2. Of the four years, 2019 had the most extensive lake area coverage with a maximum of 333 km2 and a maximum individual lake size of 30 km2. With 1.5 days average observation interval, our time-series allows for a comparison with climate data of daily resolution, enabling a better understanding of short-term climate-glacier feedbacks. Article in Journal/Newspaper glacier Greenland Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Greenland Remote Sensing 13 2 205 |
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Open Polar |
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Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
op_collection_id |
ftawi |
language |
unknown |
description |
The usability of multispectral satellite data for detecting and monitoring supraglacial meltwater ponds has been demonstrated for western Greenland. For a multitemporal analysis of large regions or entire Greenland, largely automated processing routines are required. Here, we present a sequence of algorithms that allow for an automated Sentinel-2 data search, download, processing, and generation of a consistent and dense melt pond area time-series based on open-source software. We test our approach for a ~82,000 km2 area at the 79°N Glacier (Nioghalvfjerdsbrae) in northeast Greenland, covering the years 2016, 2017, 2018 and 2019. Our lake detection is based on the ratio of the blue and red visible bands using a minimum threshold. To remove false classification caused by the similar spectra of shadow and water on ice, we implement a shadow model to mask out topographically induced artifacts. We identified 880 individual lakes, traceable over 479 time-steps throughout 2016-2019, with an average size of 64,212 m2. Of the four years, 2019 had the most extensive lake area coverage with a maximum of 333 km2 and a maximum individual lake size of 30 km2. With 1.5 days average observation interval, our time-series allows for a comparison with climate data of daily resolution, enabling a better understanding of short-term climate-glacier feedbacks. |
format |
Article in Journal/Newspaper |
author |
Hochreuther, Philipp Neckel, Niklas Reimann, Nathalie Humbert, Angelika Braun, Matthias |
spellingShingle |
Hochreuther, Philipp Neckel, Niklas Reimann, Nathalie Humbert, Angelika Braun, Matthias Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series |
author_facet |
Hochreuther, Philipp Neckel, Niklas Reimann, Nathalie Humbert, Angelika Braun, Matthias |
author_sort |
Hochreuther, Philipp |
title |
Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series |
title_short |
Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series |
title_full |
Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series |
title_fullStr |
Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series |
title_full_unstemmed |
Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series |
title_sort |
fully automated detection of supraglacial lake area for northeast greenland using sentinel-2 time-series |
publishDate |
2021 |
url |
https://epic.awi.de/id/eprint/53576/ https://epic.awi.de/id/eprint/53576/1/remotesensing-13-00205-v2.pdf https://hdl.handle.net/10013/epic.2b53132c-33d6-4a3e-8d6b-a3b7f94bef8b https://hdl.handle.net/ |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
glacier Greenland |
genre_facet |
glacier Greenland |
op_source |
EPIC3Remote Sensing, 13, pp. 205 |
op_relation |
https://epic.awi.de/id/eprint/53576/1/remotesensing-13-00205-v2.pdf https://hdl.handle.net/ Hochreuther, P. , Neckel, N. orcid:0000-0003-4300-5488 , Reimann, N. , Humbert, A. and Braun, M. (2021) Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series , Remote Sensing, 13 , p. 205 . doi:10.3390/rs13020205 <https://doi.org/10.3390/rs13020205> , hdl:10013/epic.2b53132c-33d6-4a3e-8d6b-a3b7f94bef8b |
op_doi |
https://doi.org/10.3390/rs13020205 |
container_title |
Remote Sensing |
container_volume |
13 |
container_issue |
2 |
container_start_page |
205 |
_version_ |
1766009122656878592 |