Applying Causal Machine Learning to Spatiotemporal Data Analysis: An Investigation of Opportunities and Challenges

Traditional spatiotemporal data analysis often relies on predictive models, which overlook the causal relationships driving observed phenomena. This limitation makes it hard to identify true drivers and develop effective interventions. To address this