Identification and analysis of landslides and their triggering mechanisms using seismological and remote sensing data

As landslides are among the most frequent and impactful geohazards in Norway, this PhD project aims to improve the detection, mapping, and understanding of landslides and their triggering mechanisms by integrating remote sensing and seismological data.

The core objective is to enhance existing methods for landslide mapping to better capture their spatial extent, timing, and triggering mechanisms. A key part of this work involves updating and expanding the national landslide database (Fig. 1B) maintained by the Norwegian Water Resources and Energy Directorate (NVE) with the use of spaceborne and airborne optical data. To process these vast datasets, we apply object-based deep learning (DL) techniques. These DL models help semi-automatically extract landslide features from satellite imagery (Fig. 1C), which would improve the speed and accuracy of inventory updates.

In addition to this, we are also extracting landslide seismic signatures (Fig. 1D) from the continuous seismic records of the Norwegian National Seismic Network (NNSN). This allows us to precisely pinpoint the timing of landslides detected via optical satellite imagery, overcoming challenges such as cloud coverage and limited temporal resolution.

Finally, we correlate landslide occurrences with meteorological data (MET station records), earthquake catalogues (Fig. 1A and 1B), and other environmental datasets to better understand the triggering mechanisms. By linking conditioning factors (such as topography, geology, climate, land cover, and hydrology) with triggering events (like rainfall or seismic activity), we aim to improve landslide prediction and identify areas most susceptible to future events.

This interdisciplinary approach not only enhances the quality and completeness of landslide inventories but also contributes to better urban planning, hazard assessment, and disaster preparedness across Norway.

People

Project members

Nina Hećej - PhD candidate

Mathilde Bøttger Sørensen - Principle supervisor

Benjamin Aubrey Robson - Internal co-supervisor

Reginald Leonhard Manfred Hermanns - External co-supervisor, NGU