Salīdzināt metodes
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| Laika telpas Geary C× | Telpiskās asociācijas vietējie indikatori (ST-LISA)× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1954 / 2010s | 1995 (LISA); space-time extensions developed 2000s–2010s |
| Autors≠ | Geary (1954); extended to space-time by Anselin and others | Extension of Anselin (1995) LISA framework to the space-time domain |
| Tips≠ | Spatial autocorrelation statistic | Local spatial statistic (space-time) |
| Pirmavots≠ | Geary, R. C. (1954). The Contiguity Ratio and Statistical Mapping. The Incorporated Statistician, 5(3), 115-145. DOI ↗ | Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| Citi nosaukumi | ST-Geary's C, spatiotemporal Geary C, space-time contiguity ratio, space-time local spatial autocorrelation | ST-LISA, space-time LISA, spatiotemporal local indicators of spatial association, STLISA |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | Space-Time Geary's C extends the classical Geary contiguity ratio to panel or longitudinal spatial data, measuring autocorrelation across both geographic neighbors and adjacent time periods simultaneously. Values below 1 indicate positive space-time clustering; values above 1 indicate dispersion, and a value near 1 suggests random arrangement across the space-time lattice. | 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. |
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