SAGA.statistics_grid.15: Focal PCA on a Grid

This tool uses the difference in cell values of a center cell and its neighbours (as specified by the kernel) as features for a Principal Component Analysis (PCA). This method has been used by Thomas and Herzfeld (2004) to parameterize the topography for a subsequent regionalization of climate variables with the principal components as predictors in a regression model.

Inputs

Grille

format
href
Please set a value for GRID.

number of first components in the output; set to zero to get all

integer

Output of Base Topographies

boolean

Overwrite Previous Results

boolean

Kernel Type

string

Kernel radius in cells.

integer

Method

string

Outputs

Base Topographies

format
transmission

Principal Components

format
transmission

Eigen Vectors

format
transmission

Execution options

successUri
inProgressUri
failedUri

format

mode

Execute End Point

View the execution endpoint of a process.

View the alternative version in HTML.

http://demo.mapmint.com/ogc-apihttp://localhost/ogc-api/processes/SAGA.statistics_grid.15.html
Last modified: Sat Feb 19 15:43:34 CET 2022