Distribution and Evolution of Supraglacial Lakes in Greenland during the 2016–2018 Melt Seasons

• Published in: Remote Sensing
• Main Authors: Jinjing Hu, Huabing Huang, Zhaohui Chi, Xiao Cheng, Zixin Wei, Peimin Chen, Xiaoqing Xu, Shengliang Qi, Yifang Xu, Yang Zheng
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2021
• Subjects: supraglacial lakes; GEE; distribution and evolution; sentinel-2 images; Greenland; Science; Q; Ice Sheet
• Online Access: https://doi.org/10.3390/rs14010055; https://doaj.org/article/819ce45a90694848930a6fdcf1048399

In recent decades, the melting of the Greenland Ice Sheet (GrIS) has become one of the major causes of global sea-level rise. Supraglacial lakes (SGLs) are typical hydrological features produced on the surface of the GrIS during the melt seasons. The existence and evolution of SGLs play an important role in the melting process of the ice sheet surface. To understand the distribution and recent changes of SGLs in Greenland, this study developed a random forest (RF) algorithm incorporating the texture and morphological features to automatically identify SGLs based on the Google Earth Engine (GEE) platform. Sentinel-2 imagery was used to map the SGLs inventory in Greenland during the 2016–2018 melt seasons and to explore the spatial and temporal variability characteristics of SGLs. Our results show changes in SGLs from 2016 to 2018, with the total area decreasing by ~1152.22 km 2 and the number increasing by 1134; SGLs are mainly distributed in western Greenland (SW, CW, NW) and northeastern Greenland (NE), where the NE region has the largest number of observed SGLs and the largest SGL was with the surface area of 16.60 km 2 (2016). SGLs were found to be most active in the area with the elevation of 800–1600 m and the slope of 0–5°, and showed a phenomenon of retreating to lower elevation areas and developing to steeper slope areas. Our work provided a method for rapid inventory of SGLs. This study will help monitor the mass balance of the GrIS and predict future rapid ice loss from Greenland.