In recent years many methods for ancestry inference have been proposed, particularly model based methods such as STRUCTURE in which a generative probabilistic model is explicitly described, and classical methods such as principal component analysis that are designed for spatial ancestry inference. We have recently developed a couple of methods (SPA and LOCO-LD) that combine the best of both worlds - these methods incorporate a probabilistic model, but they provide spatial ancestry inference with high accuracy. I will describe these methods, the evaluation of their performance, as well as some insights about the mathematical relations between the methods.