Sammenlign metoder
Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.
| Multiskala romlig autokorrelasjon× | Romlig autokorrelasjon× | |
|---|---|---|
| Fagfelt | Romlig analyse | Romlig analyse |
| Familie | Regression model | Regression model |
| Opprinnelsesår≠ | 2002 | 1950 |
| Opphavsperson≠ | Borcard & Legendre; Csillag & Kabos | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| Type≠ | Spatial autocorrelation decomposition | Spatial statistic / exploratory spatial data analysis |
| Opprinnelig kilde≠ | Borcard, D., & Legendre, P. (2002). All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecological Modelling, 153(1-2), 51-68. DOI ↗ | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| Alias | multi-scale spatial autocorrelation, scale-decomposed spatial autocorrelation, multiscale Moran analysis, MSA | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| Relaterte≠ | 6 | 5 |
| Sammendrag≠ | Multiscale spatial autocorrelation extends classical spatial autocorrelation analysis by computing and comparing autocorrelation statistics (such as Moran's I) across a range of spatial scales simultaneously. This reveals at which geographic distances or resolutions spatial clustering or dispersion is strongest, providing a richer picture than a single global measure. | 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. |
| ScholarGateDatasett ↗ |
|
|