Linganisha mbinu

	Uchanganuzi wa Angani wa Msingi wa Mtandao	Uhusiano wa Kiasilia
Nyanja	Uchanganuzi wa Kimaeneo	Uchanganuzi wa Kimaeneo
Familia	Regression model	Regression model
Mwaka wa asili	1990s–2000s	1950
Mwanzilishi	Atsuyuki Okabe and colleagues	P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
Aina	Spatial network model	Spatial statistic / exploratory spatial data analysis
Chanzo asilia	Okabe, A., Satoh, T., Furuta, T., Sugihara, K., & Okano, K. (2006). Generalized network Voronoi diagrams: Concepts, computational methods, and applications. International Journal of Geographical Information Science, 22(9), 965–994.	Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23.
Majina mbadala	network spatial analysis, network-constrained spatial analysis, spatial network analysis, NBSA	spatial dependence, geographic autocorrelation, spatial clustering measure, SA
Zinazohusiana	3	5
Muhtasari	Network-based spatial analysis (NBSA) analyzes the distribution and interaction of spatial phenomena constrained to a network structure — such as roads, railways, or rivers — using network distance rather than straight-line (Euclidean) distance. It is the appropriate framework whenever movement, proximity, or risk is governed by the underlying network topology rather than open space.	Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations.