Let’s take a subset of a points from a points of interest dataset. This subset represents the majority of chain pubs located across the United Kingdom. As a simple point dataset, it gives a good initial indication of the spread and density of pubs across the country.
See AttachmentHowever, an improved and more accurate display of this data can be created using an interpolation as outlined below.
Raster > Create Raster > Hotspot Density.
Enter the settings in the Create raster callout window, many of the default and Automatic options are very good for a first pass at the interpolation.
See AttachmentOnce the density map has been processed it will be displayed in the map. This gives a hotspot view of the density of the pubs. In order to focus the map on the areas that truly have a high density, color and color stretch changes are required.
Raster > Color > Choose a color ramp that color the less dense values as white.
Raster > Color > Color Stretch > Linear 5-95%.
Histogram and Linear Stretch along with their clip options are designed to stretch a smaller range of values (the raster grid values) over a wider range in order to accentuate contrast between features of interest in order to improve detail.
The result of these simple changes can be seen below. The image on the left show’s a less defined pattern. It appears that much of the UK has a high density of pubs, this does not provide value to a marketeer (or pub enthusiast) for example. After some basic manipulation of the color and histogram, a much more realistic and intuitive story appears. In regard to making informed decisions based on location, the second map gives a much more accurate and precise set of locations.
See Attachment