time

name

affiliation

Topic / Working title

13:30

Edzer Pebesma

U Muenster

Welcome

13:35-13:55

Anton Thielmann

U Goettingen

Machine learning for 3d point clouds arising from terrestrial laser scans in forestry

13:55-14:15

Marius Appel

U Muenster

Multi-resolution approximations to map global phenomena from massive datasets

14:15-14:35

Ribana Roscher (t.b.c.)

U Bonn / München

explainable machine learning, uncertainty quantification

14:35-14:55

Emanuel Büechi

TU Vienna

Forecasting crop yields by combining the advantages of Earth Observation, in-situ data, and seasonal forecasts through Machine Learning

14:55-15:10

break

15:10-15-30

Jana Gierse

TU Dortmund

Robust  Variogram estimation in the presence of outlier blocks with application to satellite data

15:30-15:50

Maite Lezama-Valdes

U Muenster

Bridging scales: From point and satellite data to high spatio-temporal resolution environmental variables

15:50-16:10

Marvin Ludwig

U Muenster

Increasing the transferability of global spatial prediction models

16:10-16:30

Discussion: the way forward

all