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Мултимащабна пространствена автокорелация×Локални индикатори за пространствена асоциация (LISA)×
ОбластПространствен анализПространствен анализ
СемействоRegression modelRegression model
Година на възникване20021995
СъздателBorcard & Legendre; Csillag & KabosLuc Anselin
ТипSpatial autocorrelation decompositionLocal spatial statistic
Основополагащ източникBorcard, 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 ↗
Други названияmulti-scale spatial autocorrelation, scale-decomposed spatial autocorrelation, multiscale Moran analysis, MSALISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA
Свързани66
РезюмеMultiscale 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.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

Към търсенето Изтегляне на слайдове

ScholarGateСравнение на методи: Multiscale Spatial Autocorrelation · Local Indicators of Spatial Association. Извлечено на 2026-06-19 от https://scholargate.app/bg/compare