📝 Description

This project focuses on analyzing time series of geological activity in Norway, such as landslides, Earth movements, and infrastructure-related displacements, using Earth observation data from InSAR (Interferometric Synthetic Aperture Radar). The time series, available from the InSAR Norway website, represent ground displacement measured by SAR sensors and are spatially related. The thesis will explore spatio-temporal models to cluster and forecast these time series, aiming to identify areas of high geological activity and detect potential processing errors in the data.

The student will work with advanced techniques for time series analysis, including clustering methods to group similar displacement patterns and forecasting models to predict future geological activity. The spatially related nature of the data will be leveraged using spatio-temporal models, which can capture both temporal dynamics and spatial dependencies. The student will implement spatiotemporal models using PyTorch and Torch Spatiotemporal. By the end of the project, the student will gain hands-on experience in processing Earth observation data, applying spatio-temporal models, and interpreting results for real-world geological monitoring applications.

Data: Time series of ground displacement from InSAR Norway, representing geological activity across various regions in Norway.

📨 Contact:

Filippo Maria Bianchi filippo.m.bianchi@uit.no