Land-surface models require knowledge of subsurface properties especially in the uppermost few meters, such as stratigraphies of soil type, porosity and organic and water contents. However, these ground properties are highly variable in space, especially in mountain areas, and existing maps are not detailed enough, and often even outright wrong.
The goal of the thesis is to develop and test methods to compile high-resolution maps of ground properties by combining information from remote sensing (e.g. NDVI) with terrain properties (e.g. detecting areas that collect water) and climate-derived variables (e.g. a simplified water balance). In the above example, a high NDVI combined with a low-slope area with large upstream area and high amounts of precipitation suggest that the pixel in question is a mire area with high water table and organic soils.
The master thesis will evaluate different workflows with satellite images, geomorphological maps and field observations. The candidate should have the ability to conduct fieldwork in Norwegian mountain areas to obtain own validation data sets of subsurface properties.