Can/should I do stratified sampling for two variables when I split training/testing?

Hi all, I hope you don't mind a bit of a novice question. I'm working with a dataset where there are large imbalances in two features with a strong relationship to the target (the year and location that data was collected). In the Hands-On ML O'Reilly textbook, it mentions that you should consider stratified sampling for the train/test split in situations with highly impactful imbalanced features.

How would you handle this scenario, where two features are highly impactful and imbalanced? …

data datascience dataset features location mind o'reilly relationship sampling testing training variables