Is 4D (2D) geospatial data anomaly detection supported?

I just discovered this package and I was wondering whether is possible to perform anomaly detection of geospatial data, for example data coming from a network of weather stations which all measure air temperature.

In the past we used either a simple statistical model, that checks if a certain station measured value falls in the IQR of the neighbouring stations, or a supervised model (using SVM) trained with values from neighbouring stations and models. I was wondering if it would be possible to apply one of the model of pyod on this kind of data to identify outliers.

The data can be thought as 4D since we have variable[id_station, time, latitude, longitude], but in practice we always apply the model in 2D as we compare the value of a station to its neighbours. Still, it would be good to have a generalized model that can consider all dimensions at the same time.

Thanks for any info :)