mlsanityData to 7 Oct 2026

Recent Ice Trends in Swiss Mountain Lakes: 20-year Analysis of MODIS Imagery

arXiv 2103.12434 ↗First posted 23 Mar 2021cs.CVcited by 1

Not on the map. Why?

Abstract (arXiv)

Depleting lake ice is a climate change indicator, just like sea-level rise or glacial retreat. Monitoring Lake Ice Phenology (LIP) is useful because long-term freezing and thawing patterns serve as sentinels to understand regional and global climate change. We report a study for the Oberengadin region of Switzerland, where several small- and medium-sized mountain lakes are located. We observe the LIP events, such as freeze-up, break-up and ice cover duration, across two decades (2000-2020) from optical satellite images. We analyse the time series of MODIS imagery 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 webcam images. From the ice maps, we derive long-term LIP trends. Since the webcam data are only available for two winters, we cross-check our results against the operational MODIS and VIIRS snow products. We find a change in complete freeze duration of -0.76 and -0.89 days per annum for lakes Sils and Silvaplana, respectively. Furthermore, we observe plausible correlations of the LIP trends with climate data measured at nearby meteorological stations. We notice that mean winter air temperature has a negative correlation with the freeze duration and break-up events and a positive correlation with the freeze-up events. Additionally, we observe a strong negative correlation of sunshine during the winter months with the freeze duration and break-up events.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 12 of its 71 references that are in the map. First posted on arXiv 23 Mar 2021.

Builds on

12 of 71 references.

References · 12

  1. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,120
  2. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,210
  3. 2019Tackling Climate Change with Machine Learningcited by 264
  4. 2016The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentationcited by 122
  5. 2020Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profilescited by 59
  6. 2020Physics-Aware Gaussian Processes in Remote Sensingcited by 14
  7. 2016Comparison of 14 different families of classification algorithms on 115 binary datasetscited by 5
  8. 2020Lake Ice Monitoring with Webcams and Crowd-Sourced Imagescited by 4
  9. 2020Living in the Physics and Machine Learning Interplay for Earth Observationcited by 4
  10. 2020Lake Ice Detection from Sentinel-1 SAR with Deep Learningcited by 3
  11. 2020Integrated monitoring of ice in selected Swiss lakes. Final project reportcited by 2
  12. 2020Ice Monitoring in Swiss Lakes from Optical Satellites and Webcams using Machine Learningcited by 2

Built on by

Cited by year

Citing papers per year: 2021: 1.

1 paper.