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I'll start off by prefacing this with the fact that I'm not even sure if I'm asking the right question and what I'm really looking for is some guidance to dig in the right direction.

I have a set of 3D spatial data (latitude, longitude, time) on a regular spatial grid.

I expect there to be anomalies/outliers in this data that are of interest. They may be spatial or temporal in nature.

Are there machine learning or statistical methods that are tailored towards identifying such anomalies?

I think I'm struggling as it's such a vague question so some direction (even just the name of a method to go and google) would be really helpful.

Does this answer your question?

– Pedro Henrique Monforte – 2020-08-14T14:31:07.870