Spatial Causal Discovery
With Applications in R
Preface
Understanding the world is, at its heart, a quest to uncover cause from correlation — to distinguish what truly drives change from what merely follows.
This book brings that quest into the spatial domain, where patterns unfold not just across time, but across geography and scale. By uniting causal reasoning with spatial data science, we take a step closer to interpreting the invisible forces that shape landscapes, cities, and environments.
With R as our companion, we explore both theory and practice — from fundamental concepts to computational techniques — building the tools to see why spatial systems behave the way they do.
“In every map lies a hidden story; in every cause, a hidden map.”
