Regression modelGIS / spatial

Space-Time Kernel Density Estimation (ST-KDE)

Space-Time Kernel Density Estimation extends classical KDE into three dimensions — two spatial and one temporal — to reveal how the intensity of point events (crimes, accidents, disease cases) varies continuously across both geographic space and time. It produces a smooth probabilistic surface that highlights where and when events concentrate most densely.

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Sources

  1. Nakaya, T., & Yano, K. (2010). Visualising crime clusters in a space-time cube: An exploratory data-analysis approach using space-time kernel density estimation and scan statistics. Transactions in GIS, 14(3), 223-239. DOI: 10.1111/j.1467-9671.2010.01194.x
  2. Kernel density estimation. Wikipedia. link

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Referenced by

ScholarGateSpace-Time Kernel Density Estimation (Space-Time Kernel Density Estimation). Retrieved 2026-06-04 from https://scholargate.app/en/spatial-analysis/space-time-kernel-density-estimation