What Does Personal Success Look Like in an Uncertain World?
How graph theory, cellular automata and deep learning are silently coming together to shape the future of spatial modelling. The topic under discussion is very broad, as we will need to discuss the entire scope of spatial analysis before projecting into the future. For the first thing you need to predict the future is knowing the past. So I will narrow down the scope of discussion progressively to the area of spatial analysis that has intrigued me the most. I have been involved in numerous deep learning projects, and also have some experience in modelling urban processes as temporal graphs. This combination of exposure gave me a particular perspective, and I frequently try to compare all these paradigms(just inside my head). Hence, in this post I will discuss the unification of these three paradigms, this is what I perceive the future of spatial analysis to be.