## 1 Introduction  
Glasical lakes are important indicators of the regional glacier dynamics in response to climate warming and changing precipitation [1; 2; 3]. With the continuous retreating and thinning of mountain glaciers in the Tibetan Plateau, a large number of glacial lakes have developed and experienced rapid expansion in recent decades, leading to the increased hazard risk of glacial lake outburst floods (GLOFs) [4]. These GLOFs usually evolve and erupt over a short time and can trace long distances from high altitude regions, which will pose a great threat to the life and property in the downstream valleys [5; 6]. Knowledge about the glacial lake distribution and their development are of great importance for the better understanding of the associated glacial processes and hazard assessment of GLOFs [7,8]. Multitemporal mapping of glacial lakes is the first step in the evaluation of the potential hazard from GLOFs since it can be used to perform the analysis of the evolution patterns of glacial lakes in order to identify the potentially dangerous glacial lakes on the regional scale [9,10]. Terrestrial surveying has provided the traditional tools for studying glacial lakes for several decades. However, one of the great limitations of these techniques is that they have difficulties in accessing generally remote glacial lakes over a large and risky mountainous terrain area, and they are extremely costly in terms of time and money. In contrast, remote sensing techniques can provide an archive of satellite images obtained both from optical and microwave sensors over a long time, and are the only feasible tools for the detailed investigation of glacial lakes without the great expense of field measurements [11]. Optical remote sensing data, such as Landsat series satellite data, Sentinel-2A/2B, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Systeme Probatoire d'Observation de la Terre-5 (SPOT-5), and Moderate-resolution Imaging Spectroradiometer (MODIS) data, have been widely applied for studies related to glacial lake dynamic monitoring and hazard management [12, 13, 14, 15]. Based on these data, visual interpretation that depends on subjective empirical judgment is the main method used for the delineation of mountainous glacial lakes characterized by complex terrain conditions and glaciated environments [11,16,17]. Many studies have usually used the threshold segmentation of normalized difference water indices (NDWIs) for classifying glacial lakes [12,18,19]. Recently, a systematic approach that integrates the advantages of the threshold segmentation method and the Chan-Vese (C-V) model was proposed, which can effectively extract glacial lakes by removing the noise from the surroundings, mountain shadows, and adjacent glaciers [20]. For the accurate extraction of glacial lakes from heterogeneous backgrounds, an automated scheme that uses the non-local active contour approach based on the modified NDWI has been used to produce highly reliable glacial lake maps across the entire Tibetan Plateau region [21]. Although good results have been achieved through these techniques, the data acquisition is strongly hampered by weather conditions and the time of day. Selection of high-quality optical images for lake mapping over large glaciated areas is not an easy task. Furthermore, most of these studies have tried to monitor the glacial lakes by only covering a few time intervals. Because glacial lakes that are prone to outburst are likely to experience dramatic changes over several days, high-frequency mapping offers the valuable information required for the early identification of related hazards. In this paper, the southeastern Tibetan Plateau was chosen as the test site because glacial lakes in this region are more sensitive to climate change, abundant precipitation, and high ice-layer temperatures, and show high intra-annual variability in the lake extent.