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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| Format: | Article |
| Language: | English |
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MDPI AG
2021-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/2/205 |
| _version_ | 1797414271436455936 |
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| author | Philipp Hochreuther Niklas Neckel Nathalie Reimann Angelika Humbert Matthias Braun |
| author_facet | Philipp Hochreuther Niklas Neckel Nathalie Reimann Angelika Humbert Matthias Braun |
| author_sort | Philipp Hochreuther |
| collection | DOAJ |
| 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 km<sup>2</sup> 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 m<sup>2</sup>. Of the four years, 2019 had the most extensive lake area coverage with a maximum of 333 km<sup>2</sup> and a maximum individual lake size of 30 km<sup>2</sup>. 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. |
| first_indexed | 2024-03-09T05:30:37Z |
| format | Article |
| id | doaj.art-c59e1b62ad84433284d01967e50388ee |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T05:30:37Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-c59e1b62ad84433284d01967e50388ee2023-12-03T12:33:15ZengMDPI AGRemote Sensing2072-42922021-01-0113220510.3390/rs13020205Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-SeriesPhilipp Hochreuther0Niklas Neckel1Nathalie Reimann2Angelika Humbert3Matthias Braun4Institute of Geography, Friedrich-Alexander University Erlangen-Nürnberg, 91058 Erlangen, GermanyHelmholtz Centre for Polar and Marine Research, Alfred Wegener Institute, 27570 Bremerhaven, GermanyInstitute of Geography, Friedrich-Alexander University Erlangen-Nürnberg, 91058 Erlangen, GermanyHelmholtz Centre for Polar and Marine Research, Alfred Wegener Institute, 27570 Bremerhaven, GermanyInstitute of Geography, Friedrich-Alexander University Erlangen-Nürnberg, 91058 Erlangen, GermanyThe 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 km<sup>2</sup> 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 m<sup>2</sup>. Of the four years, 2019 had the most extensive lake area coverage with a maximum of 333 km<sup>2</sup> and a maximum individual lake size of 30 km<sup>2</sup>. 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.https://www.mdpi.com/2072-4292/13/2/205supraglacial lakes79 °NSentinel-2lake areaautomated detectionGreenland |
| spellingShingle | Philipp Hochreuther Niklas Neckel Nathalie Reimann Angelika Humbert Matthias Braun Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series Remote Sensing supraglacial lakes 79 °N Sentinel-2 lake area automated detection Greenland |
| title | 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_short | 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 |
| topic | supraglacial lakes 79 °N Sentinel-2 lake area automated detection Greenland |
| url | https://www.mdpi.com/2072-4292/13/2/205 |
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