Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series

Remote Sensing

Niklas Neckel¹  Angelika Humbert¹  Matthias Braun²  Nathalie Reimann²  Philipp Hochreuther² 

[1] Helmholtz Centre for Polar and Marine Research, Alfred Wegener Institute, 27570 Bremerhaven, Germany;Institute of Geography, Friedrich-Alexander University Erlangen-Nürnberg, 91058 Erlangen, Germany;

关键词: supraglacial lakes;    79 N;    Sentinel-2;    lake area;    automated detection;    Greenland;   

DOI  :  10.3390/rs13020205

来源: DOAJ

【 摘 要 】

The usability of multispectral satellite data for detecting and monitoring supraglacial meltwater ponds has been demonstrated for western Greenland. For a multitemporal analysis of large regions or entire Greenland, largely automated processing routines are required. Here, we present a sequence of algorithms that allow for an automated Sentinel-2 data search, download, processing, and generation of a consistent and dense melt pond area time-series based on open-source software. We test our approach for a ~82,000 km² area at the 79°N Glacier (Nioghalvfjerdsbrae) in northeast Greenland, covering the years 2016, 2017, 2018 and 2019. Our lake detection is based on the ratio of the blue and red visible bands using a minimum threshold. To remove false classification caused by the similar spectra of shadow and water on ice, we implement a shadow model to mask out topographically induced artifacts. We identified 880 individual lakes, traceable over 479 time-steps throughout 2016–2019, with an average size of 64,212 m². Of the four years, 2019 had the most extensive lake area coverage with a maximum of 333 km² and a maximum individual lake size of 30 km². With 1.5 days average observation interval, our time-series allows for a comparison with climate data of daily resolution, enabling a better understanding of short-term climate-glacier feedbacks.

【 授权许可】

Unknown