A Vector Approach to the Analysis of (Patterns with) Spatial Dependence
It is evident that the utility of an image or map will depend on the quantity of the information we can extract from it by the analysis of the spatial relationships of the phenomenon represented. For it, tools that describe aspects such as spatial dependence or autocorrelation in patterns are used. The statistic techniques that measure the spatial dependence are very varied, but all of them provide only scalar information about the variation of spatial properties in the pattern, without analyzing the possible directedness of the dependence mentioned. In this work, we make a vector approach to the analysis of spatial dependence, therefore, given a pattern, besides quantifying its autocorrelation level, we will determinate if statistics evidence of directedness exists, calculating the angle where the direction appears. For this we will use a parametric method when the normality of population can be assumed, and a non-parametric method for uniform distribution.
KeywordsSpatial Dependence Anisotropy Directional Trend Circular Statistics
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