Fine-Resolution Mapping of Pan-Arctic Lake Ice-Off Phenology Based on Dense Sentinel-2 Time Series Data
The timing of lake ice-off regulates biotic and abiotic processes in Arctic ecosystems. Due to the coarse spatial and temporal resolution of available satellite data, previous studies mainly focused on lake-scale investigations of melting/freezing, hindering the detection of subtle patterns within h...
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doaj-dad5440821b14b03922ff361fed955f22021-07-23T14:04:25ZengMDPI AGRemote Sensing2072-42922021-07-01132742274210.3390/rs13142742Fine-Resolution Mapping of Pan-Arctic Lake Ice-Off Phenology Based on Dense Sentinel-2 Time Series DataChong Liu0Huabing Huang1Fengming Hui2Ziqian Zhang3Xiao Cheng4School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou 510275, ChinaSchool of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou 510275, ChinaSchool of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou 510275, ChinaSchool of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou 510275, ChinaSchool of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou 510275, ChinaThe timing of lake ice-off regulates biotic and abiotic processes in Arctic ecosystems. Due to the coarse spatial and temporal resolution of available satellite data, previous studies mainly focused on lake-scale investigations of melting/freezing, hindering the detection of subtle patterns within heterogeneous landscapes. To fill this knowledge gap, we developed a new approach for fine-resolution mapping of Pan-Arctic lake ice-off phenology. Using the Scene Classification Layer data derived from dense Sentinel-2 time series images, we estimated the pixel-by-pixel ice break-up end date information by seeking the transition time point when the pixel is completely free of ice. Applying this approach on the Google Earth Engine platform, we mapped the spatial distribution of the break-up end date for 45,532 lakes across the entire Arctic (except for Greenland) for the year 2019. The evaluation results suggested that our estimations matched well with both in situ measurements and an existing lake ice phenology product. Based on the generated map, we estimated that the average break-up end time of Pan-Arctic lakes is 172 ± 13.4 (measured in day of year) for the year 2019. The mapped lake ice-off phenology exhibits a latitudinal gradient, with a linear slope of 1.02 days per degree from 55°N onward. We also demonstrated the importance of lake and landscape characteristics in affecting spring lake ice melting. The proposed approach offers new possibilities for monitoring the seasonal Arctic lake ice freeze–thaw cycle, benefiting the ongoing efforts of combating and adapting to climate change.https://www.mdpi.com/2072-4292/13/14/2742arctic lakeice-off phenologydense time seriesSentinel-2 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chong Liu Huabing Huang Fengming Hui Ziqian Zhang Xiao Cheng |
spellingShingle |
Chong Liu Huabing Huang Fengming Hui Ziqian Zhang Xiao Cheng Fine-Resolution Mapping of Pan-Arctic Lake Ice-Off Phenology Based on Dense Sentinel-2 Time Series Data Remote Sensing arctic lake ice-off phenology dense time series Sentinel-2 |
author_facet |
Chong Liu Huabing Huang Fengming Hui Ziqian Zhang Xiao Cheng |
author_sort |
Chong Liu |
title |
Fine-Resolution Mapping of Pan-Arctic Lake Ice-Off Phenology Based on Dense Sentinel-2 Time Series Data |
title_short |
Fine-Resolution Mapping of Pan-Arctic Lake Ice-Off Phenology Based on Dense Sentinel-2 Time Series Data |
title_full |
Fine-Resolution Mapping of Pan-Arctic Lake Ice-Off Phenology Based on Dense Sentinel-2 Time Series Data |
title_fullStr |
Fine-Resolution Mapping of Pan-Arctic Lake Ice-Off Phenology Based on Dense Sentinel-2 Time Series Data |
title_full_unstemmed |
Fine-Resolution Mapping of Pan-Arctic Lake Ice-Off Phenology Based on Dense Sentinel-2 Time Series Data |
title_sort |
fine-resolution mapping of pan-arctic lake ice-off phenology based on dense sentinel-2 time series data |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2021-07-01 |
description |
The timing of lake ice-off regulates biotic and abiotic processes in Arctic ecosystems. Due to the coarse spatial and temporal resolution of available satellite data, previous studies mainly focused on lake-scale investigations of melting/freezing, hindering the detection of subtle patterns within heterogeneous landscapes. To fill this knowledge gap, we developed a new approach for fine-resolution mapping of Pan-Arctic lake ice-off phenology. Using the Scene Classification Layer data derived from dense Sentinel-2 time series images, we estimated the pixel-by-pixel ice break-up end date information by seeking the transition time point when the pixel is completely free of ice. Applying this approach on the Google Earth Engine platform, we mapped the spatial distribution of the break-up end date for 45,532 lakes across the entire Arctic (except for Greenland) for the year 2019. The evaluation results suggested that our estimations matched well with both in situ measurements and an existing lake ice phenology product. Based on the generated map, we estimated that the average break-up end time of Pan-Arctic lakes is 172 ± 13.4 (measured in day of year) for the year 2019. The mapped lake ice-off phenology exhibits a latitudinal gradient, with a linear slope of 1.02 days per degree from 55°N onward. We also demonstrated the importance of lake and landscape characteristics in affecting spring lake ice melting. The proposed approach offers new possibilities for monitoring the seasonal Arctic lake ice freeze–thaw cycle, benefiting the ongoing efforts of combating and adapting to climate change. |
topic |
arctic lake ice-off phenology dense time series Sentinel-2 |
url |
https://www.mdpi.com/2072-4292/13/14/2742 |
work_keys_str_mv |
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