Antarctic Supraglacial Lake Detection Using Landsat 8 and Sentinel-2 Imagery: Towards Continental Generation of Lake Volumes

Melt and supraglacial lakes are precursors to ice shelf collapse and subsequent accelerated ice sheet mass loss. We used data from the Landsat 8 and Sentinel-2 satellites to develop a threshold-based method for detection of lakes found on the Antarctic ice shelves, calculate their depths and thus th...

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Published in:Remote Sensing
Main Authors: Mahsa Moussavi, Allen Pope, Anna Halberstadt, Luke Trusel, Leanne Cioffi, Waleed Abdalati
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2020
Subjects:
Online Access:https://doi.org/10.3390/rs12010134
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spelling ftmdpi:oai:mdpi.com:/2072-4292/12/1/134/ 2023-08-20T03:59:31+02:00 Antarctic Supraglacial Lake Detection Using Landsat 8 and Sentinel-2 Imagery: Towards Continental Generation of Lake Volumes Mahsa Moussavi Allen Pope Anna Halberstadt Luke Trusel Leanne Cioffi Waleed Abdalati agris 2020-01-01 application/pdf https://doi.org/10.3390/rs12010134 EN eng Multidisciplinary Digital Publishing Institute Environmental Remote Sensing https://dx.doi.org/10.3390/rs12010134 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 1; Pages: 134 supraglacial lake antarctica meltwater volumes ice shelf stability supervised classification satellite imagery Landsat 8 Sentinel-2 Text 2020 ftmdpi https://doi.org/10.3390/rs12010134 2023-07-31T22:57:22Z Melt and supraglacial lakes are precursors to ice shelf collapse and subsequent accelerated ice sheet mass loss. We used data from the Landsat 8 and Sentinel-2 satellites to develop a threshold-based method for detection of lakes found on the Antarctic ice shelves, calculate their depths and thus their volumes. To achieve this, we focus on four key areas: the Amery, Roi Baudouin, Nivlisen, and Riiser-Larsen ice shelves, which are all characterized by extensive surface meltwater features. To validate our products, we compare our results against those obtained by an independent method based on a supervised classification scheme (e.g., Random Forest algorithm). Additional verification is provided by manual inspection of results for nearly 1000 Landsat 8 and Sentinel-2 images. Our dual-sensor approach will enable constructing high-resolution time series of lake volumes. Therefore, to ensure interoperability between the two datasets, we evaluate depths from contemporaneous Landsat 8 and Sentinel-2 image pairs. Our assessments point to a high degree of correspondence, producing an average R2 value of 0.85, no bias, and an average RMSE of 0.2 m. We demonstrate our method’s ability to characterize lake evolution by presenting first evidence of drainage events outside of the Antarctic Peninsula on the Amery Ice shelf. The methods presented here pave the way to upscaling throughout the Landsat 8 and Sentinel-2 observational record across Antarctica to produce a first-ever continental dataset of supraglacial lake volumes. Such a dataset will improve our understanding of the influence of surface hydrology on ice shelf stability, and thus, future projections of Antarctica’s contribution to sea level rise. Text Amery Ice Shelf Antarc* Antarctic Antarctic Peninsula Antarctica Ice Sheet Ice Shelf Ice Shelves MDPI Open Access Publishing Antarctic The Antarctic Antarctic Peninsula Amery ENVELOPE(-94.063,-94.063,56.565,56.565) Amery Ice Shelf ENVELOPE(71.000,71.000,-69.750,-69.750) Riiser-Larsen ENVELOPE(50.667,50.667,-66.783,-66.783) Roi Baudouin ENVELOPE(24.461,24.461,-70.438,-70.438) Nivlisen ENVELOPE(11.000,11.000,-70.333,-70.333) Remote Sensing 12 1 134
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic supraglacial lake
antarctica
meltwater volumes
ice shelf stability
supervised classification
satellite imagery
Landsat 8
Sentinel-2
spellingShingle supraglacial lake
antarctica
meltwater volumes
ice shelf stability
supervised classification
satellite imagery
Landsat 8
Sentinel-2
Mahsa Moussavi
Allen Pope
Anna Halberstadt
Luke Trusel
Leanne Cioffi
Waleed Abdalati
Antarctic Supraglacial Lake Detection Using Landsat 8 and Sentinel-2 Imagery: Towards Continental Generation of Lake Volumes
topic_facet supraglacial lake
antarctica
meltwater volumes
ice shelf stability
supervised classification
satellite imagery
Landsat 8
Sentinel-2
description Melt and supraglacial lakes are precursors to ice shelf collapse and subsequent accelerated ice sheet mass loss. We used data from the Landsat 8 and Sentinel-2 satellites to develop a threshold-based method for detection of lakes found on the Antarctic ice shelves, calculate their depths and thus their volumes. To achieve this, we focus on four key areas: the Amery, Roi Baudouin, Nivlisen, and Riiser-Larsen ice shelves, which are all characterized by extensive surface meltwater features. To validate our products, we compare our results against those obtained by an independent method based on a supervised classification scheme (e.g., Random Forest algorithm). Additional verification is provided by manual inspection of results for nearly 1000 Landsat 8 and Sentinel-2 images. Our dual-sensor approach will enable constructing high-resolution time series of lake volumes. Therefore, to ensure interoperability between the two datasets, we evaluate depths from contemporaneous Landsat 8 and Sentinel-2 image pairs. Our assessments point to a high degree of correspondence, producing an average R2 value of 0.85, no bias, and an average RMSE of 0.2 m. We demonstrate our method’s ability to characterize lake evolution by presenting first evidence of drainage events outside of the Antarctic Peninsula on the Amery Ice shelf. The methods presented here pave the way to upscaling throughout the Landsat 8 and Sentinel-2 observational record across Antarctica to produce a first-ever continental dataset of supraglacial lake volumes. Such a dataset will improve our understanding of the influence of surface hydrology on ice shelf stability, and thus, future projections of Antarctica’s contribution to sea level rise.
format Text
author Mahsa Moussavi
Allen Pope
Anna Halberstadt
Luke Trusel
Leanne Cioffi
Waleed Abdalati
author_facet Mahsa Moussavi
Allen Pope
Anna Halberstadt
Luke Trusel
Leanne Cioffi
Waleed Abdalati
author_sort Mahsa Moussavi
title Antarctic Supraglacial Lake Detection Using Landsat 8 and Sentinel-2 Imagery: Towards Continental Generation of Lake Volumes
title_short Antarctic Supraglacial Lake Detection Using Landsat 8 and Sentinel-2 Imagery: Towards Continental Generation of Lake Volumes
title_full Antarctic Supraglacial Lake Detection Using Landsat 8 and Sentinel-2 Imagery: Towards Continental Generation of Lake Volumes
title_fullStr Antarctic Supraglacial Lake Detection Using Landsat 8 and Sentinel-2 Imagery: Towards Continental Generation of Lake Volumes
title_full_unstemmed Antarctic Supraglacial Lake Detection Using Landsat 8 and Sentinel-2 Imagery: Towards Continental Generation of Lake Volumes
title_sort antarctic supraglacial lake detection using landsat 8 and sentinel-2 imagery: towards continental generation of lake volumes
publisher Multidisciplinary Digital Publishing Institute
publishDate 2020
url https://doi.org/10.3390/rs12010134
op_coverage agris
long_lat ENVELOPE(-94.063,-94.063,56.565,56.565)
ENVELOPE(71.000,71.000,-69.750,-69.750)
ENVELOPE(50.667,50.667,-66.783,-66.783)
ENVELOPE(24.461,24.461,-70.438,-70.438)
ENVELOPE(11.000,11.000,-70.333,-70.333)
geographic Antarctic
The Antarctic
Antarctic Peninsula
Amery
Amery Ice Shelf
Riiser-Larsen
Roi Baudouin
Nivlisen
geographic_facet Antarctic
The Antarctic
Antarctic Peninsula
Amery
Amery Ice Shelf
Riiser-Larsen
Roi Baudouin
Nivlisen
genre Amery Ice Shelf
Antarc*
Antarctic
Antarctic Peninsula
Antarctica
Ice Sheet
Ice Shelf
Ice Shelves
genre_facet Amery Ice Shelf
Antarc*
Antarctic
Antarctic Peninsula
Antarctica
Ice Sheet
Ice Shelf
Ice Shelves
op_source Remote Sensing; Volume 12; Issue 1; Pages: 134
op_relation Environmental Remote Sensing
https://dx.doi.org/10.3390/rs12010134
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs12010134
container_title Remote Sensing
container_volume 12
container_issue 1
container_start_page 134
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