How Kernel Density works

Kernel Density calculates the density of features in a neighborhood around those features. It can be calculated for both point and line features.


Kernel Density for point features

Kernel Density calculates the density of point features around each output raster cell.

Conceptually, a smoothly curved surface is fitted over each point. The surface value is highest at the location of the point and diminishes with increasing distance from the point, reaching zero at the Search radius distance from the point. Only a circular neighborhood is possible. The volume under the surface equals the Population field value for the point, or one if NONE is specified. The density at each output raster cell is calculated by adding the values of all the kernel surfaces where they overlay the raster cell center. The kernel function is based on the quadratic kernel function described in Silverman (1986, p. 76, equation 4.5).

If a population field setting other than NONE is used, each item's value determines the number of times to count the point. For example, a value of three would cause the point to be counted as three points. The values can be integer or floating point. If an area unit is selected, the calculated density for the cell is multiplied by the appropriate factor before it is written to the output raster. For example, if the input ground units are meters, comparing a unit scale factor of meters to kilometers will result in the values being different by a multiplier of 1,000,000 (1,000 x 1,000).

Possible uses include finding density of houses, wildlife observations, or crime reports. The population field could be used to weigh some points more heavily than others, depending on their meaning, or to allow one point to represent several observations. For example, one address might represent a condominium with six units, or some crimes might be weighed more severely than others in determining overall crime levels.

Increasing the radius will not greatly change the calculated density values. Although more points will fall inside the larger neighborhood, this number will be divided by a larger area when calculating density. The main effect of a larger radius is that density is calculated considering a larger number of points, which can be further from the raster cell. This results in a more generalized output raster.


Kernel Density for line features

Kernel Density calculates the density of linear features in the neighborhood of each output raster cell.

Conceptually, a smoothly curved surface is fitted over each line. Its value is greatest on the line and diminishes as you move away from the line, reaching zero at the search radius from the line. The surface is defined so the volume under the surface equals the product of line length and the Population field value. The density at each output raster cell is calculated by adding the values of all the kernel surfaces where they overlay the raster cell center. The use of the kernel function for lines is adapted from the quadratic kernel function for point densities as described in Silverman (1986, p. 76, equation 4.5).


A line segment and the kernel surface fitted over it

The illustration above shows a line segment and the kernel surface fitted over it. The contribution of the line segment to density is equal to the value of the kernel surface at the raster cell center.

A default unit is selected based on the linear unit of the projection definition of the input point or polyline features. If the linear unit of the feature class is meters, the area units will default to SQUARE_KILOMETERS and the resulting line density will be meters per square kilometer. To set the density in meters per square meter, set the area units to SQUARE_METERS. When the linear units of the feature class is feet, the area units will default to SQUARE_MILES. Similarly, to have the density in units of feet per square foot, set the area units to SQUARE_FOOT.

If a population field other than NONE is used, the length of the line is considered to be its actual length multiplied by the value of the population field for that line.

Possible uses include finding density of roads as an influence on wildlife habitat or density of utility lines in a town. The Population field can be used to weigh some roads or utility lines more heavily than others, depending on their size or class. For example, a divided highway probably has more impact than a narrow dirt road, and a high-tension line has more impact than a standard electric pole.


References

Silverman, B.W. Density Estimation for Statistics and Data Analysis. New York: Chapman and Hall, 1986.