  Depleting lake ice can serve as an indicator for climate change, just like
sea level rise or glacial retreat. Several Lake Ice Phenological (LIP) events
serve as sentinels to understand the regional and global climate change. Hence,
monitoring the long-term lake freezing and thawing patterns can prove very
useful. In this paper, we focus on observing the LIP events such as freeze-up,
break-up and temporal freeze extent in the Oberengadin region of Switzerland,
where there are several small- and medium-sized mountain lakes, across two
decades (2000-2020) from optical satellite images. We analyse time-series of
MODIS imagery (and additionally cross-check with VIIRS data when available), by
estimating spatially resolved maps of lake ice for these Alpine lakes with
supervised machine learning. To train the classifier we rely on reference data
annotated manually based on publicly available webcam images. From the ice maps
we derive long-term LIP trends. Since the webcam data is only available for two
winters, we also validate our results against the operational MODIS and VIIRS
snow products. We find a change in Complete Freeze Duration (CFD) of -0.76 and
-0.89 days per annum (d/a) for lakes Sils and Silvaplana respectively.
Furthermore, we correlate the lake freezing and thawing trends with climate
data such as temperature, sunshine, precipitation and wind measured at nearby
meteorological stations.
