Abstract
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.
Highlights
Lakes are a major component of the landscape at high latitudes
Recent analysis of lake ice phenology trends in the Canadian Arctic have shown that the end of break-up (BUE, when the lake is fully clear of ice) is occurring one day earlier per year (2000–2013, significant trends only) [4] and future predictions (2041–2070) of lake ice phenology estimate that the mean dates of when full ice cover occurs could shift to up to 15 days later, dates for the complete disappearance of ice up to 25 days earlier, and lead to an overall decrease in ice duration by up to 35 days [5,6]
This study aims to use a Remote Sens. 2020, 12, 382 method based on backscatter evolution and a two-class segmentation method to assess their accuracy in identifying lake ice phenology events for a large Arctic lake, Lake Hazen, using high-density time series of Sentinel-1 A/B data
Summary
Lakes are a major component of the landscape at high latitudes They can cover 15%–40% of the land in some regions [1]. Observed changes in lake ice phenology have been related to recent, accelerated winter warming observed in the Arctic, resulting in shifts of >1 ◦C since 1990 [7]. These changes in lake ice dates have an impact on northern communities as the formation of lake ice establishes supply routes via ice roads, access to hunting camps and for travel between communities [8,9]. Recent research has demonstrated that the timing of ice-off can affect ecosystem variables such as residence time, lake stratification, and chlorophyll-a concentrations [12]
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