Fabian Schumacher

ESSI Earth and Space Science Informatics

The 2024 Outstanding Student and PhD candidate Presentation (OSPP) Award is awarded to Fabian Schumacher for the poster/PICO entitled:

Assessing the area of applicability of spatial prediction models through a local data point density approach (Schumacher, F.; Knoth, C.; Ludwig, M.; Meyer, H.)

Click here to download the poster/PICO file.

Fabian Schumacher is a bachelor graduate at the Institute for Geoinformatics at the University of M¨unster. Currently he is working as student research assistant under the supervision of Hanna Meyer in the Remote Sensing and Spatial Modelling Research Group (Institute of Landscape Ecology) focusing on the assessment of spatial prediction model uncertainty.

The work he has presented at the EGU24 introduced a novel approach to assess the uncertainty of machine learning-based spatial prediction models by calculating local training data point densities (LPD). The LPD is a quantitative measure that indicates, for a new prediction location, how many similar reference data points have been included in the model training.