Credit only granted for GEOG498N or GEOG788L.

Concepts and techniques in spatial and spatio-temporal data mining from a computational perspective will be introduced. Topics include types of spatial and spatiotemporal data; foundations of spatial statistics; spatial pattern families (spatial clustering & hotspot detection, colocation, cascading, outlier detection, spatial prediction and classification); advanced topics including deep learning, adversarial learning, reinforcement learning and spatial big data platforms. Application domains of the techniques include smart cities, transportation, public health, public safety, agriculture, etc.