GEOSTATS: logistic regression with spatially autocorrelated data
In a +/- 25ha forest, I've mapped the forest ground flora on the basis of a
20m x 20m grid (a total of > 700 grid cells). Quite logically, the
distribution of the mapped plant species is not random, but exibits a high
degree of spatial autocorrelation.
In order to explain the spatial distributions of these plant species, I
performed a logistic regression with the species presence/absence data and pH,
soil type, illuminance, ... as indipendent variables.
To check for spatial autocorrelation I calculated semivariograms for the
deviance (residuals) of the logistic regressions. When the nugget sill ratio
was larger than 0.5, I concluded that spatial autocorrelation did not
influence my results
Is the applied method correct and are my conclusions justified?
Laboratory for forest, nature and landscape research
Vital Decosterstraat 102, B-3000 Leuven
tel. : +32-16 329737 fax. : +32-16 329760
e-mail : kris.verheyen@...
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