Using machine learning to characterise modern hydrological extreme events.
This Master's project is available from the intake of Autumn 2023 (August). Contact the listed supervisors for more information.
Main content
Project description:
The aim of this project is to use time series of remote sensing data combined with machine learning, to characterise modern hydrological extreme events in the catchment of Arresjøen, Svalbard. The student will use high-resolution aerial and satellite imagery to create training data that will later be used to map debris flows and avalanches, as well as chart the occurrence of surface water and winter melt events. This can then potentially be expanded in order to put Arresjøen in a regional context.
Proposed course plan during the master's degree (60 ECTS):
GEOV316
GEOV336
Prerequisites
Must have experience with GIS. Knowledge of programming an advantage
Felt- lab- og analysearbeid
This is a desktop study with all analyses being conducted on computers. The student will have access to the Geomatics room (GEO), and if needed can have a virtual machine set up for them to run on the UiB server.
