On Tuesday I gave another talk at the MLU with a remixed auditorium and I
received a lot of additional input for my work and my PhD thesis. There’s a lot
of geospatial analysis to be done, as pointed out by Joachim Spilke.

The two main tasks clarified on Tuesday for the first half of my thesis revolve
around the continuation of Georg Weigert’s work on the yield (potential)
prediction. The first is whether it’s actually necessary to consider the
spatial information in the regression, i.e. whether the spatial
cross-validation I’ve developed is necessary and useful in practice. The second
is which regression model is to be chosen in a practical setup. Currently, it’s
a neural network, but if a different technique turns out to produce better
(whatever “better” means) predictions, that might be tried.