MASSIVE – MAchine learning, Surface mass balance of glaciers, Snow cover, In-situ data, Volume change and Earth observation

In MASSIVE, the project team aims at improving glacier mapping and surface glacier mass balance estimation techniques with the help of machine learning, especially deep learning. We will develop the methodology for glaciers in Norway, Svalbard, the European Alps and the Himalayas and then expand it to regions with different glacier characteristics.

The project outcome will be a multi-temporal glacier inventory and a multi-annual time series of mass balance of the glaciers under investigation. The data cubes of glacierized regions will be open access to foster future research on these sensitive climate indicators.

Read more about the project (mn.uio.no)

Tags: Boosting, Data fusion/integration, Databases, Deep learning/neural networks, Information extraction/retrieval, Time series, Transfer learning, Unsupervised learning, Earth and environmental sciences
Published July 6, 2023 1:44 PM - Last modified Oct. 23, 2023 11:52 AM