Kernel Ratio

The Kernel Ratio is an operation that calculates the kernel map to two distinct attributes and the result is a ratio between these two maps.

It is accessible through:

PROCESSING → SPATIAL ANALYSIS → KERNEL RATIO


Input Information:

Layer Name: Select the input layer.

Kernel Parameters:

Kernel Map A

Attr Name: Attribute name that identifies the desired information.

Function: Quartic, Normal, Triangular, Uniform and Negative Exponential.

Estimation: Density, Spatial Moving Average and Probability.

Use adaptative radius: Uses adaptative radius or defines the percentage value of total width.

Kernel Map B

Attr Name: Attribute name that identifies the desired information.

Function: Quartic, Normal, Triangular, Uniform and Negative Exponential.

Estimation: Density, Spatial Moving Average and Probability.

Use adaptative radius: Uses adaptative radius or defines the percentage value of total width.

Combination: How the kernal ratio is calculated (ratio, log ratio, absolute difference, relative difference, absolute sum, relative sum).

Output Information:

Grid: The output is a grid (image) where the kernel map information is a pixel value.

Data Set: The output is the input data plus an attribute with kernel map information.

Repository: Select one type of repository by clicking on the button to save the output layer as a file.

Layer Name: Defines the name to create the output layer.

Click on the OK button and then the kernel map will be calculated.