Introduction to Human Geography Using ArcGIS Online. J. Chris Carter
instead of using shades or colors to distinguish values, circles of different sizes are used. A large circle represents a high value, while smaller circles represent lower values (figure 1.9).
Figure 1.9.Thematic maps: Choropleth and graduated circle. Choropleth maps use colors or shades within areal features to represent data. Graduated circle maps use circles of different sizes to represent data. Log in to your ArcGIS Online account to explore these maps. Choropleth map of median income: https://arcg.is/1WiuC4. Graduated circle map of market potential for regular exercise routines: https://arcg.is/1jjKHz. Maps by author. Data sources: 2016 USA Median Household Income, Esri, US Census Bureau. 2016 USA Adults That Exercise Regularly, Esri and GfK US, LLC, the GfK MRI division.
Isoline maps consist of lines that connect points of the same value. Typically, these are used to map continuous surfaces, where data values change often over the earth’s surface, such as with temperature or elevation (figure 1.10).
Dot density maps use dots to represent a specified value within a geographic feature (figure 1.10). If the population of a county is 10,000 people, then a dot density map where one dot equals 1,000 people would have ten dots randomly placed within the county borders.
Figure 1.10.Thematic maps: Isoline and dot density. Elevation contours on a topographic map are a type of isoline. Dot density maps use dots to represent values, such as number of households. Log in to your ArcGIS Online account to view these maps. USGS National Map with topographic isolines: https://arcg.is/91zf1. Dot density map of income extremes: https://arcg.is/m8DHL. Data sources: USGS National Map by Esri—USGS The National Map: National Boundaries Dataset, National Elevation Dataset, Geographic Names Information System, National Hydrography Dataset, National Land Cover Database, National Structures Dataset, and National Transportation Dataset; US Census Bureau—TIGER/Line; HERE Road Data. Income Extremes by Lisa Berry—Esri.
Flowline maps use lines of varying thickness to show the direction and quantity of spatial interaction between places. Thicker lines represent larger quantities, while thinner lines represent smaller quantities. These maps are often used to represent trade and migration flows between countries (figure 1.11).
Cartogram maps distort the area of features based on the value of a variable. A cartogram of population will show places with more people as larger and places with fewer people as smaller. In figure 1.11, state populations are shown for three time periods. The size of each state varies according to its population size. Note how western states, such as California, change in size in each time period.
Figure 1.11.Thematic maps: Flowline and cartogram. The flowline map shows Syrian refugee flows in 2014. View the Syrian refugee flow map at https://storymaps.esri.com/stories/2016/the-uprooted/index.html. Cartogram from US Census. Image sources: The Uprooted by Esri Story Maps Team; data sources: UNHCR, Airbus Defense and Space. Cartograms of State Populations in 1890, 1950, and 2010 by US Census Bureau; data sources: Census 2010 tables.
Map scale
Scale is another issue to be aware of when creating and interpreting maps. Real estate companies often produce maps with no scale or with distorted scales to make desirable places seem closer. For instance, a real estate map may include the location of a new housing development, with lines showing freeways, beaches, and parks, giving the impression that they are all nearby. However, with no given scale, these places are often drawn to appear much closer than they really are.
Properly produced maps include a clearly defined map scale that indicates the ratio of map distance to real-world distance. The scale allows map readers to measure the size of features and the distance between them. Map scale is represented verbally, graphically, or as a ratio or fraction.
Verbal scale: 1 inch equals 1 mile
Graphic scale:
Ratio scale: 1:24,000
Fraction scale: 1/24,000
In the case of ratio and fraction scales, the units remain the same on both sides of the scale. Using the examples noted. 1 inch on the map represents 24,000 inches in the real world.
Maps are often described as being large scale or small scale (figure 1.12). A large-scale map refers to a larger fraction or ratio, while a small-scale map refers to a smaller fraction or ratio. For instance, 1:24,000 is a larger ratio than 1:100,000, so it is a larger scale map.
Large-scale maps are more “zoomed in.” They cover a smaller area and include more detail. A city map is a larger-scale map than a country map. Small-scale maps are “zoomed out” and cover a larger area with less detail. A country map is a smaller-scale map than a city or neighborhood map.
Figure 1.12.Small-scale and large-scale maps. Large-scale maps are more zoomed in than small-scale maps. Explore this map at https://arcg.is/rjL8K. Maps by author. Data sources: 2016 USA Median Household Income by Esri. Esri, US Census Bureau.
To remember the difference between large- and small-scale maps, either think in terms of ratios or fractions, or use this trick: your neighborhood looks larger on a large-scale map (because it is more zoomed in), while your neighborhood looks smaller on a small-scale map (because it is more zoomed out).
While map scale is important for measuring size and distance and determining the level of detail shown, it is also important to understand scale in terms of how it affects the spatial patterns observed by geographers.
This is often referred to as the modifiable areal unit problem (MAUP). In essence, the unit of measurement used for analysis, be it countries, states, counties, cities, or some other area, can strongly influence the patterns observed on the map. For instance, at a state scale, the “red state/blue state” divide in US presidential elections clearly shows states such as Texas as solidly red (Republican). But by changing the scale of analysis, new spatial patterns emerge. At a county scale, large urban areas within Texas appear as blue (Democratic) patches (figure 1.13). So, while a state level of analysis is useful in understanding the Electoral College for presidential elections, a county-scale analysis is more useful for understanding House of Representative and local election results.
There is no single “proper” scale of analysis for all geographic questions. Rather, the proper scale depends on the question being asked. If the US government has funds available to help states tackle high unemployment, then analyzing unemployment rates at a state level makes sense. On the other hand, if a city government wants to identify neighborhoods with high unemployment rates, then the proper scale of analysis would be urban neighborhoods.
Figure 1.13.Scale of analysis and the modifiable areal unit problem. Explore these maps at https://arcg.is/yDHKy. Maps by author. Data sources: State level—Federal Election Commission. Texas counties—Texas Office of the Secretary of State.
Geographers are interested in spatial patterns at a wide range of scales, always keeping in mind how patterns and processes interact between global and local levels. These interactions have become even more essential to understand due to globalization, the process whereby places become increasingly interconnected through communication networks, transportation technology, and political