calcWdataRaster

Calculate lagged values for a raster dataset given a window
and an agregation function

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

calcWdataRaster function

<dl><dt>w</dt>
<dd>A matrix</dd>
<dt>dataset</dt>
<dd>A list of rasters</dd>
<dt>fun</dt>
<dd>A string giving the name of a function or a function or "nl"
for non-local method</dd>
<dt>missing_pxl</dt>
<dd>A boolean vector of missing (FALSE) pixels</dd></dl>

Arguments

Calculate lagged values for a raster dataset — calcWdataRaster

<dl>

<dt>w</dt>
<dd>A matrix</dd>


<dt>dataset</dt>
<dd>A list of rasters</dd>


<dt>fun</dt>
<dd>A string giving the name of a function or a function or "nl"
for non-local method</dd>


<dt>missing_pxl</dt>
<dd>A boolean vector of missing (FALSE) pixels</dd>

</dl>

calcWdataRaster: Calculate lagged values for a raster dataset

Description

Usage

Arguments

Examples