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| Wieloskalowa autokorelacja przestrzenna× | Lokalne Wskaźniki Zależności Przestrzennej (LISA)× | |
|---|---|---|
| Dziedzina | Analiza przestrzenna | Analiza przestrzenna |
| Rodzina | Regression model | Regression model |
| Rok powstania≠ | 2002 | 1995 |
| Twórca≠ | Borcard & Legendre; Csillag & Kabos | Luc Anselin |
| Typ≠ | Spatial autocorrelation decomposition | Local spatial statistic |
| Źródło pierwotne≠ | 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 ↗ | Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| Inne nazwy | multi-scale spatial autocorrelation, scale-decomposed spatial autocorrelation, multiscale Moran analysis, MSA | LISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA |
| Pokrewne | 6 | 6 |
| Podsumowanie≠ | 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. | LISA, introduced by Luc Anselin in 1995, decomposes a global spatial autocorrelation index into a location-specific statistic for every observation. It identifies where statistically significant spatial clusters and outliers occur on a map, enabling researchers to move beyond a single global summary and pinpoint the geographic sources of spatial dependence. |
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