input_raster_data

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

input_raster_data function

<dl><dt>dataset</dt>
<dd>A list of rasters</dd>
<dt>w</dt>
<dd>The window to use in the focal function</dd>
<dt>fun</dt>
<dd>the function to use as the focal function</dd>
<dt>standardize</dt>
<dd>A boolean to specify if the variable must be centered and
reduced (default = True)</dd></dl>

Arguments

Raster data preparation — input_raster_data

<dl>

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


<dt>w</dt>
<dd>The window to use in the focal function</dd>


<dt>fun</dt>
<dd>the function to use as the focal function</dd>


<dt>standardize</dt>
<dd>A boolean to specify if the variable must be centered and
reduced (default = True)</dd>

</dl>

input_raster_data: Raster data preparation

Description

Usage

Value

Arguments

Examples