Lecture
This lecture covers point processes in spatial analysis, focusing on the spatial variation of discrete spatial objects and the dissemination of spatial objects in space. It delves into the study of spatial autocorrelation, point patterns, measures of concentration of events, and validity domains caveats. The instructor explains the concept of point processes, the emergence of spatial patterns, and the use of Poisson processes as a reference. Various methods such as density-based and distance-based analyses, nearest neighbor methods, and K- and L-functions are discussed to detect underlying influences and patterns in spatial data.