Joel Heilman

Thematic Cartography Project Report: Unique Spatial Trends in the United States

Maps can reveal a lot of interesting information about the spatial patterns of this nation. This

project looks specifically at four surprising trends that many people don’t realize. The first map looks at

the distribution of Ultimate teams. It was surprising how little clustering there was. Montana shows an

interesting distribution of population change. New England shows a large range of population density.

The ethnicity of Hawaii may not be what you think. These maps show that spatial patterns need to be

observed before they are assumed.

County and state shapefiles as well as demographic information were obtained from the

National Atlas. The National Atlas compiles data from the U.S. Geological survey and the U.S. Census

Bureau. The location of college Ultimate teams was obtained from USA Ultimate. This data was

processed in Arc Map to produce the maps.

Top College Ultimate Teams (Map 1)

The first map displays the distribution of college Ultimate teams. This map shows if there is any

spatial pattern to the distribution of Ultimate teams. Does the map show clustering of the top teams;

does one area of the country produce a lot of Ultimate teams? People often assume Colorado and the

Pacific Northwest are hot spots for Ultimate. It was surprising to see how much the teams were located

somewhat evenly across the country. Most of the clustering is related to the distribution of the

country’s population. A look at the top 20 teams reveals the same even distribution.

Graduated symbols were used to display the teams based on rank. The better ranked teams are

shown as the bigger symbols. Graduated symbols are great for displaying point data with a variable.

Color value was also used to display the variability of rank. The sequential color plan shows higher

ranked teams in darker blue and lower ranked teams in light blue. This simply makes the variability

easier to see. Since the United States is located in the mid-latitudes, the equidistant conic projection was

used. Conic projections are best for displaying mid-latitudes.

Classification was a simple process. Each team has a unique value from 1 to 100. So each

classification process produced the same equal interval results. Five classes of 20 each were used. The

color of teams is blue because it advances more than the light colored states. However, the states still

advance slightly past the white background.

The text in the map is all basic Arial font because it is easy to read. The title is most important

and therefore the largest text and is top and center. The legend text is important for understanding the

map so it appears at a good size but off to the side. Supplemental text is used to explain the projection,

the source of the data and the cartographer. This text is small and located at the bottom of the map.

Montana Population Change (Map 2)

The second map displays the population change in Montana by county from 1980 to 2000.

Montana and the northern Great Plains states are known for their decreasing populations. Rural

populations are moving to the cities as the number of farmers in the nation decreases. Although parts of

Montana decreased a lot during 20 years, a large part of the state saw an increase in population. Some

areas increased a lot. Some of these counties grew because of their growing cities, but many of the

counties are largely rural. Urbanization must not be the only factor affecting population change in

Montana.

A choropleth map was used to display the population change data. Choropleth maps are great at

displaying discrete quantitative information. Choropleth maps are generally used for derived forms of

data so the percent change is displayed. The diverging color scheme uses two contrasting colors to show

the difference between population increase and decrease. The blue shows population decrease with

darker blue being a larger decrease, while red shows population increase with darker red showing a

larger increase. Red implies excitement and busyness while blue is more relaxed. Red makes sense for a

growing population while blue works well to show a decreasing population. Since Montana is located in

the mid-latitudes, the equidistant conic projection was used. Conic projections are best for displaying

mid-latitudes.

Jenks Natural Breaks was used for the classification. Six classes sufficiently show the variability

without making the map too complex. Six is also an even number which means there is the same

number of classes above and below zero. One class break was adjusted slightly so that it was exactly

zero, or no change. This way, it was clear which areas grew and which areas decreased. As mentioned,

the colors made it clear which areas increased and which decreased. The colors also advance from the

white background.

Figure 1: Jenks Natural Breaks classification with a slight adjustment.

The text in the map is all basic Arial font because it is easy to read. The title is most important

and therefore the largest text and is top and center. The legend text is important for understanding the

map so it appears at a good size. The title explains very simply what the map is displaying, while the

legend specifies what is being shown but is to the side of the more important map body. Supplemental

text is used to explain the projection, the source of the data and the cartographer. This text is small and

located at the bottom of the map.

New England Population Density (Map 3)

The third map shows the population density of New England. The Atlantic coast is known to be

the most densely populated part of the country. Although parts of New England are crowded, like

Boston, other parts are not very densely populated. Most of Maine, Vermont, and New Hampshire are

sparsely populated. Boston is the only city in the region with a population of over 200,000.

A dasymetric map is great for displaying population density. Counties are used as the

enumeration unit, but dasymetric maps don’t display enumeration unit boundaries. State boundaries

are used for reference. The sequential color plan shows denser areas in darker red-brown and sparsely

populated areas in tan. The increase in color value also implies more, in this case denser. Since New

England is located in the mid-latitudes, the Albers Equal Area Conic projection was used. Conic

projections are best for displaying mid-latitudes. Area is good to preserve when displaying density

because it deals with population per unit area.

Jenks Natural Breaks was used for the classification. Five classes sufficiently show the variability

without making the map too complex. The color of the map body advances nicely from the white

background. The legend also advances subtly from the background.

Figure 2: Jenks Natural Breaks. Suffolk County, where Boston is located, is on the far right.

The map uses all basic Arial font because it is easy to read. The title is most important and

therefore the largest text and is top and center. The legend text is important for understanding the map

so it appears at a good size but in a convenient open space on the side. The title explains very simply

what the map is displaying, while the legend specifies the units being displayed as well as the year of the

data. Supplemental text is used to explain the projection, the source of the data and the cartographer.

This text is small and located at the bottom of the map.

Hawaii Ethnicity (Map 4)

The last map shows the percentage of ethnicity in Hawaii. Surprisingly, the data shows that

about half of the population is Asian. It is unclear whether native Hawaiians are listed under Native

American or some other class. The map displays the large amount of migration from Japan, the

Philippines, and other parts of Asia.

The pie map is useful for showing a variety of variables that contribute to a whole. In this case,

the different ethnicities shown together represent the whole population. In this way, it can be shown

what percentage of the whole each ethnicity represents. The enumeration units are counties; each

county is represented by a pie chart. Different color hues are used to represent the different variables

(different ethnicities). The different ethnicities can be thought as qualitative, but the different

percentages of each ethnicity are quantitative shown by size of each “slice” of the pie. Since Hawaii is

located in the mid-latitudes, the Albers Equal Area Conic projection was used. Conic projections are best

for displaying mid-latitudes. The background is blue because the area around Hawaii is water. The

islands are shown as tan to represent land. The pies advance from the land and water; they are the

important part of the map.

The map uses all basic Arial font because it is easy to read. The title is most important and

therefore the largest text and is top and center. The legend text is important for understanding the map

so it appears at a good size but in a convenient open space on the side. The title explains very simply

what the map is displaying, while the legend specifies the color of ethnicity. Supplemental text is used to

explain the projection, the source of the data and the cartographer. This text is small and located at the

bottom of the map.

Discussion

The data took much effort to manipulate for easy use in Arc Map. Much of the demographic

information had to be joined to the correct shapefiles. The projections had to be defined for the

shapefiles. New fields in the tables had to be made to produce the population change map. The ultimate

teams required geocoding. Overall, there was a lot of extra data processing.

Each map had its own unique problems and limitation, for example, the legend in the Montana

map looks cluttered. The Ultimate map had many overlapping symbols. The larger symbols also appear

on top of the smaller symbols, making them invisible.

It is still unclear what category the native Hawaiian population falls under. They take up about

10% of the state’s population so they cannot be included in the Native American group. Perhaps they

are completely missing. This is something that needs to be improved.

The map of New England has a large portion of the area in the lowest class. Almost all of Maine

falls into this class. A quantile classification would show more variation in these areas, but would also

deemphasize the density of Suffolk County, where Boston is located.

Each map displayed a unique trend in the United States. Exploring these trends will reveal even

more surprises. We can use these maps to help identify the causes of these trends. Understanding the

causes of these trends will reveal a lot about this country.

References

"Hawaii QuickFacts from the US Census Bureau." United States Census Bureau, 2014.

"Map Layers." National Atlas. National Atlas of the United States, 2013.

"USA Ultimate." USA Ultimate, 2010.