Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| Võrgupõhine ruumianalüüs× | Ruumiiline autokorrelatsioon× | |
|---|---|---|
| Valdkond | Ruumianalüüs | Ruumianalüüs |
| Perekond | Regression model | Regression model |
| Tekkeaasta≠ | 1990s–2000s | 1950 |
| Looja≠ | Atsuyuki Okabe and colleagues | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| Tüüp≠ | Spatial network model | Spatial statistic / exploratory spatial data analysis |
| Algallikas≠ | 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. DOI ↗ | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| Rööpnimetused | network spatial analysis, network-constrained spatial analysis, spatial network analysis, NBSA | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| Seotud≠ | 3 | 5 |
| Kokkuvõte≠ | 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. |
| ScholarGateAndmestik ↗ |
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