The omission of inhomogeneity for analyzing spatiotemporal trends of a point process could lead to wrongful conclusions regarding how geographic events are distributed and evolve in localized contexts. To address this issue, we apply an inhomogeneous point process (IPP) to address the context of a point process that is nonconstant in spatial and temporal intensity. Extending from the widely used Ripley's K function, which is often employed to detect spatial clusters in a point pattern, we discuss here a spatiotemporal inhomogeneous K function (STIK). To illustrate the usage and the effectiveness of STIK to analyze point processes, we present a series of analyses using the locations of reported urban crime in Wuhan, China.
All Science Journal Classification (ASJC) codes
- Geography, Planning and Development
- Urban Studies
- Earth and Planetary Sciences (miscellaneous)
- inhomogeneous point process
- spatiotemporal inhomogeneous K function
- urban crime