Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Ruimtelijke-Temporele Lokale Indicatoren van Ruimtelijke Associatie (ST-LISA)× | Ruimtelijke-temporele Moran's I× | |
|---|---|---|
| Vakgebied | Ruimtelijke analyse | Ruimtelijke analyse |
| Familie | Regression model | Regression model |
| Jaar van ontstaan≠ | 1995 (LISA); space-time extensions developed 2000s–2010s | 1981 |
| Grondlegger≠ | Extension of Anselin (1995) LISA framework to the space-time domain | Cliff & Ord (extended to space-time domain) |
| Type≠ | Local spatial statistic (space-time) | Spatial autocorrelation statistic |
| Oorspronkelijke bron≠ | Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ | Cliff, A. D., & Ord, J. K. (1981). Spatial Processes: Models and Applications. Pion. ISBN: 978-0850860818 |
| Aliassen | ST-LISA, space-time LISA, spatiotemporal local indicators of spatial association, STLISA | space-time autocorrelation index, ST Moran's I, spatiotemporal Moran's I, space-time I statistic |
| Verwant≠ | 6 | 5 |
| Samenvatting≠ | Space-Time Local Indicators of Spatial Association (ST-LISA) extend the classic LISA framework of Anselin (1995) into the temporal dimension, identifying locations that exhibit statistically significant spatial clustering or spatial outlier behavior consistently or intermittently across multiple time periods. They decompose global space-time autocorrelation into local contributions, revealing where and when spatial clusters emerge, persist, or dissolve. | Space-Time Moran's I extends the classic Moran's I statistic into the spatiotemporal domain, measuring whether observations that are close in both space and time tend to be more similar than those that are distant. It detects clustering, dispersion, or randomness across a combined space-time weight matrix, making it a foundational tool in epidemiology, criminology, and environmental monitoring. |
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