Monthly lake area retrieval with full Landsat archives from 1970s to 2019——a specific analysis on small lakes from the Tibetan Plateau as an indicator for the climate change

As still-water bodies, change of lakes reflects the resultant effect of climate change and human activities. Although many studies have tackled the long-term change of lakes in Tibetan Plateau (TP), detailed monthly area change of lakes is still unknown. This paper provides an innovative methodology to extract lake boundary, leveraging the full Landsat archives (159368 scenes, 1972-2019) in the TP area via the Google Earth Engine (GEE) platform, instead of only selecting the best quality ones as previous studies. The resulted monthly area data of over 9,000 TP lakes (larger than 0.1 km² each) for the period of 1972 to 2019 is unprecedented, as compared with the previous efforts, such as (1) the decade-level TP lake dataset (Wan, et al. 2016), (2) the long-term changes of lakes of larger than 10 km² (Zhang, et al. 2017), (3) the snapshot lake boundary (Messager, et al. 2016), and (4) the raster-format long-term global surface water (GSW) with large patches of no-data (Pekel, et al. 2016), which is not suitable for lake-level analysis, e.g. lake intensity, lake area statistics and trends, without further extracting lakes and some preprocessing operations like gap filling. Through analyzing the area change of small lakes (no greater than 1 km²), it is found that small lakes can be a sensitive indicator for the climate change through emergence and disappearance. The dataset and the indicator can further support assessment of the impact of human and climate change, and in return, the possible effects on human lives by the changes of lakes.

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