Krahasoni metodat

	Vlerësimi i Dendësisë Bërthamore Hapësinore-Kohore (ST-KDE)	Autokorrelacioni Hapësinor Kohë-Hapësirë
Fusha	Analiza hapësinore	Analiza hapësinore
Familja	Regression model	Regression model
Viti i origjinës	2010 (space-time extension); 1956 (KDE origin)	1981–1992
Krijuesi	Nakaya & Yano (space-time formulation); KDE foundation by Rosenblatt and Parzen	Cliff & Ord; extended by Anselin and others
Lloji	Non-parametric density estimation	Spatial autocorrelation statistic
Burimi themelues	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.	Clifford, P., Richardson, S., & Hemon, D. (1989). Assessing the significance of the correlation between two spatial processes. Biometrics, 45(1), 123–134.
Emërtime të tjera	ST-KDE, spatiotemporal kernel density estimation, space-time KDE, 3D kernel density estimation	STSA, spatiotemporal autocorrelation, space-time Moran's I, temporal spatial dependence
Të lidhura	5	5
Përmbledhja	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.	Space-Time Spatial Autocorrelation extends classic spatial autocorrelation measures — most notably Moran's I — to data that vary across both geographic units and time periods. It detects whether nearby locations that are also temporally close tend to share similar attribute values, revealing clusters, trends, or anomalies that purely spatial or purely temporal analyses would miss.