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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Main Authors: Chong Liu, Huabing Huang, Fengming Hui, Ziqian Zhang, Xiao Cheng
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/14/2742
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spelling 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 AT chongliu fineresolutionmappingofpanarcticlakeiceoffphenologybasedondensesentinel2timeseriesdata
AT huabinghuang fineresolutionmappingofpanarcticlakeiceoffphenologybasedondensesentinel2timeseriesdata
AT fengminghui fineresolutionmappingofpanarcticlakeiceoffphenologybasedondensesentinel2timeseriesdata
AT ziqianzhang fineresolutionmappingofpanarcticlakeiceoffphenologybasedondensesentinel2timeseriesdata
AT xiaocheng fineresolutionmappingofpanarcticlakeiceoffphenologybasedondensesentinel2timeseriesdata
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