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.