# Density geoprocessing functions

With the Density geoprocessing functions, you can calculate the density of input features within a neighborhood around each output raster cell.

By calculating density, you are in a sense spreading the values (of the input) out over a surface. The magnitude at each sample location (line or point) is distributed throughout the study area, and a density value is calculated for each cell in the output raster.

For density maps, a circular search area is applied that determines the distance to search for sample locations (line or point) or to spread the values out around each location and calculate a density value.

The following table lists the available geoprocessing functions and provides a brief description of each.

Geoprocessing FunctionDescription

Calculate Kernel Density Ratio

Calculates a spatial relative risk surface using two input feature datasets. The numerator in the ratio represents cases, such as number of crimes or number of patients, and the denominator represents the control, such as the total population.

Kernel Density

Calculates a magnitude-per-unit area from point or polyline features using a kernel function to fit a smoothly tapered surface to each point or polyline. A barrier can be used to alter the influence of a feature while calculating kernel density.

Line Density

Calculates a magnitude-per-unit area from polyline features that fall within a radius around each cell.

Point Density

Calculates a magnitude-per-unit area from point features that fall within a neighborhood around each cell.

Space Time Kernel Density

Expands kernel density calculations from analyzing the relative position and magnitude of the input features to include other dimensions such as time and depth (elevation). The resulting output identifies the magnitude-per-unit area using the multiple kernel functions to fit a smoothly tapered surface to each input point.

Geoprocessing functions in the Density category