GEOG 416a-516a 1Gary L. Christopherson

Lecture 10 – Mapping Quantities: Dot Density Maps

Introduction

Creating maps of features based on quantity are some of the most common and importanttypes of maps. In order to create maps that show quantity you need a quantifiableattribute that is tied to some form of geometry. For the next three lectures we will belooking specifically at area based geometry. In a GIS environment, the software managesand displays the geometry and the attributes, while the cartographer determines whichattributes she wants to display and determines how the geometry will be symbolized.

There are many different types of maps that display quantitative information, and we willsee examples of many of them during this semester, but in these lectures we will playspecial attention to dot density, graduated symbol, and choropleth maps.

Dot density maps use dots to representspecified quantities. In the map to theright, each dot represents 50,000 persons.These dots are based on population withinspecified enumeration units, in this casestates. The more dots, the higher thepopulation – California has more dots thatArizona because it has higher population.

Graduated symbols display the same dataas dot density, but by using graduatesymbols within the enumeration areas.That is the bigger the dot, the larger thenumber they represent. So in this map,California has a larger dot than Arizonabecause more people live in California.

GEOG 416a-516a 2Gary L. Christopherson

Choropleth maps use shaded areas todisplay quantitative data. Often in the formof color ramps, enumeration areas areshaded based on quantities. In thisexample, lighter colors indicate lowerpopulation and darker color higherpopulation for each state. Again,California is darker than Arizona because ithas higher population.

Dot Density Maps

Dot density maps are part of a larger group of maps that normalize data based on area.Called density maps, they show quantities per area unit as a way of normalizing data tofacilitate direct comparison between enumeration units of different size.

For example, a large enumeration area mayhave a larger population than a smaller one,but that population may be sparse becauseof the larger area. In the map to the right,the color ramp goes from green (lowestpopulaiton) to red (highest population).

In this map population has been normalizedby area to create population / square mile, adensity measure. The differences betweenthese two maps are obvious. In the mapnormalized by area, all the high values areattached to the smallest polygons in thecenter of Tucson, where population is mostconcentrated – dense.

GEOG 416a-516a 3Gary L. Christopherson

Dot density maps take a different approach, in that the area measure used to normalizethe quantitative measure is strictly visual. That is, the quantity is not divided by the area,but displayed within the enumeration unit. The number of dots per unit provides a visualmeasure of density. The maps below show both types of approaches for comparisonpurposes. The map on the left provides absolute numbers based on total populationdivided by total square miles in each enumeration unit. The map on the right shows anumber of dots, each representing 50,000 persons spread throughout the correspondingenumeration unit. The number of dots is based, in this case, on total population for eachenumeration unit divided by 50,000. The effect is to provide the map reader a quick,visual impression of population density.

Density map based on population persquare mile

Density map based on number of dots perenumeration area

Dot density maps have a number of advantages and disadvantages.

Advantages:

Easily understood by reader Illustrates variation in density Original data is recoverable More than one data set may be

illustrated simultaneously GIS allows the cartographer to

change dot value and sizecombination

Disadvantages:

Perception is not linear (reader cannot depict proportions betweenareas)

GIS randomizes dots withinenumeration units; may not be closeto the phenomena

Large ranges in data make itdifficult to select a single dot valuein areas of high and low density

Of the disadvantages, the biggest problem related to the way that software applicationslike ArcGIS automate the process of locating dots. This is usually done randomlythroughout the enumeration unit. This assumes a random distribution of the phenomenonbeing measured, something that is almost never true.

For example, in the map below population in Pima County is shown as a dot density map,with one dot equal to 500 persons. The random distribution of the dots in this map could

GEOG 416a-516a 4Gary L. Christopherson

easily give the wrong impression about population distribution to somebody not familiarwith population in the county.

Before computer software automated theplacement of dots, a cartographer wouldbase the placement of dots on spatialproximity to known data locations. This sinot possible with automated approaches, butit is possible to use higher resolution spatialdata to create dot patterns that more closelyrepresent actual distribution.

In the map below, dot density has been calculated for census tracts in Pima County. Bytying the distribution of the dots to the smaller territorial domain of the census tracts, it ispossible to see a population distribution that is closer to the actual distribution. But theboundary lines for the tracts create a level of busyness that distracts from the visualimpression of the map.

GEOG 416a-516a 5Gary L. Christopherson

By removing the boundary lines but retaining the dots, the map provides a muchimproved visual impression of population in Pima County. This technique of using adifferent resolution for creation of dot density than that used for display allows thecartographer to automate the creation of the map while retaining greater control over theplacement of the dots.

Conclusions

Dot density maps provide the user with a quick impression of quantities tied toenumeration units. They are relatively easy to create using GIS software, but there areissues with the lack of control over how the dots are distributed. Attention to differentresolution of enumeration units can allow the cartographer to create higher quality dotdensity maps.