Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Мультимасштабный пространственный автокорреляционный анализ× | Локальная пространственная автокорреляция× | |
|---|---|---|
| Область | Пространственный анализ | Пространственный анализ |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2002 | 1995 |
| Автор метода≠ | Borcard & Legendre; Csillag & Kabos | Luc Anselin |
| Тип≠ | Spatial autocorrelation decomposition | Spatial association analysis |
| Основополагающий источник≠ | 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 ↗ |
| Другие названия | multi-scale spatial autocorrelation, scale-decomposed spatial autocorrelation, multiscale Moran analysis, MSA | local spatial association, local SA, LISA methods, local spatial clustering |
| Связанные | 6 | 6 |
| Сводка≠ | 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. | Local Spatial Autocorrelation methods decompose global spatial clustering into location-specific statistics, revealing where in a study area significant clustering or dispersion occurs. Each observation receives its own association score and significance value, enabling the detection of spatial hot spots, cold spots, and spatial outliers rather than reporting a single summary statistic. |
| ScholarGateНабор данных ↗ |
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