In this method, each raster cell value is the sum of the contributions from all sample points that lie within a specified distance (radius) from the center of the cell. It is weighted by the kernel density function.
The kernel density function, computed for the distance of the sample from the center of the cell, assigns more weight to samples closer to the center of the raster cell than those further away. This method ensures that the Heatmap is smoothly varying. You can choose a Kernel function from the Method Options list.
- Quartic
- Triweight
- Tricube
- Gaussian
- Sharpened Gaussian
By default Quartic is selected for you.
The Quartic, Triweight and Tricube kernels produces a smooth and pleasing surface. If you want a larger search radius but want to retain a high level of details, you can use Sharpened Gaussian kernel.
A color gradient is used to indicate areas of increasingly higher density. Areas with sparse distributions are shown in a light color. You can apply a color gradient for better visualization.