calc_raster_spinconsistency

Calculate the spatial inconsistency sum for a set of rasters

internal

Provides functions to apply spatial fuzzy unsupervised classification, visualize and interpret results. This method is well suited when the user wants to analyze data with a fuzzy clustering algorithm and to account for the spatial dimension of the dataset. In addition, indexes for estimating the spatial consistency and classification quality are proposed.
The methods were originally proposed in the field of brain imagery (seed Cai and al. 2007 <doi:10.1016/j.patcog.2006.07.011> and Zaho and al. 2013 <doi:10.1016/j.dsp.2012.09.016>) and recently applied in geography (see Gelb and Apparicio <doi:10.4000/cybergeo.36414>).

Jeremy Gelb

geocmeans

Implementing Methods for Spatial Fuzzy Unsupervised
Classification

Philippe Apparicio

calc_raster_spinconsistency function

<dl><dt>matrices</dt>
<dd>A list of matrices</dd>
<dt>window</dt>
<dd>The window to use to define spatial neighbouring</dd>
<dt>adj</dt>
<dd>A boolean indicating if the adjusted version of the algorithm must be
calculated</dd>
<dt>dataset</dt>
<dd>A list of matrices with the original data (if adj = TRUE)</dd>
<dt>mindist</dt>
<dd>When adj is true, a minimum value for distance between two observations. If two
neighbours have exactly the same values, then the euclidean distance between
them is 0, leading to an infinite spatial weight. In that case, the minimum
distance is used instead of 0.</dd></dl>

Arguments

calculate spatial inconsistency for raster — calc_raster_spinconsistency

<dl>

<dt>matrices</dt>
<dd>A list of matrices</dd>


<dt>window</dt>
<dd>The window to use to define spatial neighbouring</dd>


<dt>adj</dt>
<dd>A boolean indicating if the adjusted version of the algorithm must be
calculated</dd>


<dt>dataset</dt>
<dd>A list of matrices with the original data (if adj = TRUE)</dd>


<dt>mindist</dt>
<dd>When adj is true, a minimum value for distance between two observations. If two
neighbours have exactly the same values, then the euclidean distance between
them is 0, leading to an infinite spatial weight. In that case, the minimum
distance is used instead of 0.</dd>

</dl>

calc_raster_spinconsistency: calculate spatial inconsistency for raster

Description

Usage

Value

Arguments

Examples