Dual-satellite (Sentinel-2 and Landsat 8) remote sensing of supraglacial lakes in Greenland

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<p><strong>Abstract.</strong> Although remote sensing is commonly used to monitor supraglacial lakes on the Greenland Ice Sheet, most satellite records must trade-off high spatial resolution for high temporal resolution (e.g. MODIS) or vice versa (e.g. Landsat). Here, we overcome this issue by developing and applying a dual-sensor method that can monitor changes to lake areas and volumes at high spatial resolution (10&amp;ndash;30<span class="thinspace"></span>m) with a frequent revisit time (~<span class="thinspace"></span>3 days). We achieve this by mosaicking imagery from the Landsat 8 OLI with imagery from the recently launched Sentinel-2 MSI for a ~<span class="thinspace"></span>12<span class="thinspace"></span>000<span class="thinspace"></span>km<sup>2</sup> area of West Greenland in summer 2016. First, we validate a physically based method for calculating lake depths with Sentinel-2 by comparing measurements against those derived from the available contemporaneous Landsat 8 imagery; we find close correspondence between the two sets of values (R<sup>2</sup><span class="thinspace"></span>=<span class="thinspace"></span>0.841; RMSE<span class="thinspace"></span>=<span class="thinspace"></span>0.555<span class="thinspace"></span>m). This provides us with the methodological basis for automatically calculating lake areas, depths and volumes from all available Landsat 8 and Sentinel-2 images. These automatic methods are incorporated into an algorithm for Fully Automated Supraglacial lake Tracking at Enhanced Resolution (FASTER). The FASTER algorithm produces time series showing lake evolution during the 2016 melt season, including automated rapid (≤<span class="thinspace"></span>4 day) lake-drainage identification. With the dual Sentinel-2-Landsat 8 record, we identify 184 rapidly draining lakes, many more than identified with either imagery collection alone (93 with Sentinel-2; 66 with Landsat 8), due to their inferior temporal resolution, or would be possible with MODIS, due to its omission of small lakes<span class="thinspace"></span><<span class="thinspace"></span>0.125<span class="thinspace"></span>km<sup>2</sup>. Finally, we identify the water volumes drained into the GrIS by rapid lake-drainage events and, by using downscaled regional climate-model (RACMO2.3p2) runoff data, the water quantity that enters the GrIS via the moulins opened by such events. We find that during the lake-drainage events alone, the water drained by small lakes (<<span class="thinspace"></span>0.125<span class="thinspace"></span>km<sup>2</sup>) is only 5.1<span class="thinspace"></span>% of the total water volume drained by all lakes. However, considering the total water volume entering the GrIS after lake drainage, the moulins opened by small lakes deliver 61.5<span class="thinspace"></span>% of the total water volume delivered via all moulins (i.e. opened by large and small lakes). These findings suggest that small lakes should be included in future remote sensing and modelling work.</p>




Williamson, A. G., Banwell, A. F., Willis, I. C., & Arnold, N. S. (2018). Dual-satellite (Sentinel-2 and Landsat 8) remote sensing of supraglacial lakes in Greenland. Cryosphere, 12(9), 3045–3065. https://doi.org/10.5194/tc-12-3045-2018

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