Assessing the Performance of Methods for Monitoring Ice Phenology of the World’s Largest High Arctic Lake Using High-Density Time Series Analysis of Sentinel-1 Data
Lake ice is a dominant component of Canada’s landscape and can act as an indicator for how freshwater aquatic ecosystems are changing with warming climates. While lake ice monitoring through government networks has decreased in the last three decades, the increased availability of remote sensing ima...
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ftmdpi:oai:mdpi.com:/2072-4292/12/3/382/ 2023-08-20T04:04:48+02:00 Assessing the Performance of Methods for Monitoring Ice Phenology of the World’s Largest High Arctic Lake Using High-Density Time Series Analysis of Sentinel-1 Data Justin Murfitt Claude R. Duguay agris 2020-01-25 application/pdf https://doi.org/10.3390/rs12030382 EN eng Multidisciplinary Digital Publishing Institute Remote Sensing in Geology, Geomorphology and Hydrology https://dx.doi.org/10.3390/rs12030382 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 3; Pages: 382 Synthetic Aperture Radar lake ice Cryosphere High Density Time Series Sentinel-1 Text 2020 ftmdpi https://doi.org/10.3390/rs12030382 2023-07-31T23:02:29Z Lake ice is a dominant component of Canada’s landscape and can act as an indicator for how freshwater aquatic ecosystems are changing with warming climates. While lake ice monitoring through government networks has decreased in the last three decades, the increased availability of remote sensing images can help to provide consistent spatial and temporal coverage for areas with annual ice cover. Synthetic aperture radar (SAR) data are commonly used for lake ice monitoring, due to the acquisition of images in any condition (time of day or weather). Using Sentinel-1 A/B images, a high-density time series of SAR images was developed for Lake Hazen in Nunavut, Canada, from 2015–2018. These images were used to test two different methods of monitoring lake ice phenology: one method using the first difference between SAR images and another that applies the Otsu segmentation method. Ice phenology dates determined from the two methods were compared with visual interpretation of the Sentinel-1 images. Mean errors for the pixel comparison of the first difference method ranged 3–10 days for ice-on and ice-off, while average error values for the Otsu method ranged 2–10 days. Mean errors for comparisons of different sections of the lake ranged 0–15 days for the first difference method and 2–17 days for the Otsu method. This research demonstrates the value of temporally consistent image acquisition for improving the accuracy of lake ice monitoring. Text Arctic Lake Hazen Nunavut MDPI Open Access Publishing Arctic Nunavut Canada Arctic Lake ENVELOPE(-130.826,-130.826,57.231,57.231) The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) Lake Hazen ENVELOPE(-71.017,-71.017,81.797,81.797) Remote Sensing 12 3 382 |
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Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
Synthetic Aperture Radar lake ice Cryosphere High Density Time Series Sentinel-1 |
spellingShingle |
Synthetic Aperture Radar lake ice Cryosphere High Density Time Series Sentinel-1 Justin Murfitt Claude R. Duguay Assessing the Performance of Methods for Monitoring Ice Phenology of the World’s Largest High Arctic Lake Using High-Density Time Series Analysis of Sentinel-1 Data |
topic_facet |
Synthetic Aperture Radar lake ice Cryosphere High Density Time Series Sentinel-1 |
description |
Lake ice is a dominant component of Canada’s landscape and can act as an indicator for how freshwater aquatic ecosystems are changing with warming climates. While lake ice monitoring through government networks has decreased in the last three decades, the increased availability of remote sensing images can help to provide consistent spatial and temporal coverage for areas with annual ice cover. Synthetic aperture radar (SAR) data are commonly used for lake ice monitoring, due to the acquisition of images in any condition (time of day or weather). Using Sentinel-1 A/B images, a high-density time series of SAR images was developed for Lake Hazen in Nunavut, Canada, from 2015–2018. These images were used to test two different methods of monitoring lake ice phenology: one method using the first difference between SAR images and another that applies the Otsu segmentation method. Ice phenology dates determined from the two methods were compared with visual interpretation of the Sentinel-1 images. Mean errors for the pixel comparison of the first difference method ranged 3–10 days for ice-on and ice-off, while average error values for the Otsu method ranged 2–10 days. Mean errors for comparisons of different sections of the lake ranged 0–15 days for the first difference method and 2–17 days for the Otsu method. This research demonstrates the value of temporally consistent image acquisition for improving the accuracy of lake ice monitoring. |
format |
Text |
author |
Justin Murfitt Claude R. Duguay |
author_facet |
Justin Murfitt Claude R. Duguay |
author_sort |
Justin Murfitt |
title |
Assessing the Performance of Methods for Monitoring Ice Phenology of the World’s Largest High Arctic Lake Using High-Density Time Series Analysis of Sentinel-1 Data |
title_short |
Assessing the Performance of Methods for Monitoring Ice Phenology of the World’s Largest High Arctic Lake Using High-Density Time Series Analysis of Sentinel-1 Data |
title_full |
Assessing the Performance of Methods for Monitoring Ice Phenology of the World’s Largest High Arctic Lake Using High-Density Time Series Analysis of Sentinel-1 Data |
title_fullStr |
Assessing the Performance of Methods for Monitoring Ice Phenology of the World’s Largest High Arctic Lake Using High-Density Time Series Analysis of Sentinel-1 Data |
title_full_unstemmed |
Assessing the Performance of Methods for Monitoring Ice Phenology of the World’s Largest High Arctic Lake Using High-Density Time Series Analysis of Sentinel-1 Data |
title_sort |
assessing the performance of methods for monitoring ice phenology of the world’s largest high arctic lake using high-density time series analysis of sentinel-1 data |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2020 |
url |
https://doi.org/10.3390/rs12030382 |
op_coverage |
agris |
long_lat |
ENVELOPE(-130.826,-130.826,57.231,57.231) ENVELOPE(73.317,73.317,-52.983,-52.983) ENVELOPE(-71.017,-71.017,81.797,81.797) |
geographic |
Arctic Nunavut Canada Arctic Lake The Sentinel Lake Hazen |
geographic_facet |
Arctic Nunavut Canada Arctic Lake The Sentinel Lake Hazen |
genre |
Arctic Lake Hazen Nunavut |
genre_facet |
Arctic Lake Hazen Nunavut |
op_source |
Remote Sensing; Volume 12; Issue 3; Pages: 382 |
op_relation |
Remote Sensing in Geology, Geomorphology and Hydrology https://dx.doi.org/10.3390/rs12030382 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs12030382 |
container_title |
Remote Sensing |
container_volume |
12 |
container_issue |
3 |
container_start_page |
382 |
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1774715201551073280 |