Spatial Autocorrelation

4.1.2 Spatial Autocorrelation
4.1.3 Benchmarking Interpolation Approaches
4.1.4 Assessing Interpolation Results ...

[edit] Spatial autocorrelation
Spatial autocorrelation statistics measure and analyze the degree of dependency among observations in a geographic space. Classic spatial autocorrelation statistics include Moran's I and Geary's C.

Spatial autocorrelation can be analyzed using correlograms, covariance functions and variograms (=semivariograms).
References: ...

Spatial autocorrelation statistics measure and analyze the degree of dependency among observations in a geo-space. Classic spatial autocorrelation statistics include Moran's I and Geary's C.

Spatial Autocorrelation - Global (binary variable)
Joint Count Statistics (adjacency)
Spatial Autocorrelation - Global (interval/ratio variable) ...

Spatial autocorrelation - The degree of relationship that exists between two or more spatial data variables (e.g. amount of organic matter in soil, gradient, suitability for agriculture). When one variable changes in one direction (e.g.

212 a geostatistical technique for interpolation that uses information about the spatial autocorrelation in the vicinity of each point to provide 'optimal' interpolation (in the sense of greater use of the information provided by the spatial ...

The distance value is the amount of spatial autocorrelation for the map being studied. The amount of spatial autocorrelation can be determined by using r.2Dcorrelogram with r.2Dto1D, or r.1Dcorrelogram.

[geography] A formulation of the concept of spatial autocorrelation by the geographer Waldo Tobler (1930-), which states "Everything is related to everything else, but near things are more related than distant things." ...

values often occur in runs across several cells
this is a form of spatial autocorrelation - tendency for nearby things to be more similar than distant things
data entered as pairs, first run length, then value ...

Interpolation is a justified measurement because of a Spatial Autocorrelation Principle that recognizes that data collected at any position will have a great similarity to, or influence of those locations within its immediate vicinity.

Hot spot analysis with space and time
Incremental spatial autocorrelation
Exploratory regression
Group analysis ...

Although for the presented first results it has no importance we have also computed the index of spatial autocorrelation which constitutes for the fifth level data 0.8990, and for the sixth level data 0.9595.

Other spectral-spatial models exploit a measure of image texture or the spatial autocorrelation function as an additional feature in the classification process (Shih and Schowengerdt 1983, Pickup and Chewings 1988).

See also: Relation, Correlation, Autocorrelation, Analysis, GIS