Linganisha mbinu

	Ujihusiano wa Anga wa Nyanja Nyingi	Uhusiano Nafasi wa Kienyeji
Nyanja	Uchanganuzi wa Kimaeneo	Uchanganuzi wa Kimaeneo
Familia	Regression model	Regression model
Mwaka wa asili	2002	1995
Mwanzilishi	Borcard & Legendre; Csillag & Kabos	Luc Anselin
Aina	Spatial autocorrelation decomposition	Spatial association analysis
Chanzo asilia	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.	Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115.
Majina mbadala	multi-scale spatial autocorrelation, scale-decomposed spatial autocorrelation, multiscale Moran analysis, MSA	local spatial association, local SA, LISA methods, local spatial clustering
Zinazohusiana	6	6
Muhtasari	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.