Fine-Resolution Mapping of Pan-Arctic Lake Ice-Off Phenology Based on Dense Sentinel-2 Time Series Data

Chong Liu,Fengming Hui,Ziqian Zhang,Xiao Cheng,Huabing Huang

doi:10.3390/rs13142742

Abstract

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.

Highlights

Lakes, through their seasonal ice cover extent and duration, are a major landscape in the Arctic [1,2,3,4,5]
Exceptfor forshoreline shorelinedevelopment, development,we we found that lake ice is significantly impacted by the selected parameters, including lake found that lake ice break-up end (BUE) is significantly impacted by the selected parameters, including area
We developed a novel approach for fine-resolution BUE mapping with the use of dense Sentinel-2 time series data via the Google Earth Engine (GEE) platform

Summary

Introduction

Through their seasonal ice cover extent and duration, are a major landscape in the Arctic [1,2,3,4,5]. Regional coherence or synchrony of lake break-up timing regulates greenhouse gas emissions from fresh water into the atmosphere [9,10,11,12], affecting the land surface energy balance [13], which in turn generates feedbacks into the climate system. Given their wide-ranging importance, accurately estimating the spatial distribution of lake ice-off phenology is essential to understand Arctic ecosystem functions and project their responses to global environmental dynamics under various climate change scenarios [14,15]. The microwave brightness temperature, with long available archives and the all-weather imaging capability, is perhaps the most widely used

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