5/10/2023 0 Comments Us population density mapHowever, the population number is certainly closer to reality as Trump won about 48.8% of the votes that went to either Trump or Clinton. Neither of these percentages is exactly correct because each county is colored fully red or blue and don’t take into account that some counties are won by a large percentage and some are essentially tied. More than 75% of the land area is red, when looking at the map based on land areas, while shifting to the population view only about 46% of the map is red. As a result, the blue counties tend to be the smaller ones so blue is visually less represented than it should be based on vote totals. Less densely populated counties tend to vote republican, while higher density, typically smaller counties tend to vote for democrats. An interesting thing to note is that this view is even more heavily dominated by the color red, for the same reasons. This map looks at the 20 presidential election results, county by county. Thus, when your eyes attempt to discern which color prevails, the comparison is more accurate and attempts to replicate the relative ratio of electoral votes for each side. That cartogram changed the size of the states so that large states with low population, and thus low electoral votes tended to shrink in size, while smaller states with moderate to larger populations tended to grow in size. On a normal election map, Red states dominate, especially because a number of larger, less populated states happen to vote Republican. The idea for that map was that by portraying a state as Red or Blue, your eye naturally attempts to determine which color has a greater share of the total. Previously, I created a map (cartogram) that showed the state by state electoral results from the Presidential Election by scaling the size of the states based on their electoral votes. This interactive map shows the election results by county and you can display the size of counties based on their land area or population size. The site editor may also be contacted with questions or comments about this Open Educational Resource.The map has been updated to include the latest 2020 results and also adds the option to color the circles by the win margin rather than just looking at the winner.Ĭlick here to view a visualization that looks more explicitly at the correlation between population density and votes by county. Please send comments or suggestions on accessibility to the site editor. The College of Earth and Mineral Sciences is committed to making its websites accessible to all users, and welcomes comments or suggestions on access improvements. This courseware module is part of Penn State's College of Earth and Mineral Sciences' OER Initiative.Įxcept where otherwise noted, content on this site is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Penn State Professional Masters Degree in GIS: Winner of the 2009 Sloan Consortium award for Most Outstanding Online Program Dutton e-Education Institute College of Earth and Mineral Sciences, The Pennsylvania State University. Dutton e-Education Institute and Assistant Program Manager for Online Geospatial Education, and Adrienne Goldsberry, Senior Lecturer, John A. Dutton e-Education Institute, Beth King, Senior Lecturer, John A. Dutton e-Education Institute Ryan Baxter, Senior Research Assistant, John A. Instructors and contributors: Jim Sloan, Senior Lecturer, John A. Dutton e-Education Institute, and Director of Education, Industry Solutions, Esri. As illustrated in the map below (Figure 3.17.4), the use of an unlimited set of color hues to symbolize unique data values leads to a confusing thematic map.Īuthor: David DiBiase, Senior Lecturer, John A. This symbolization strategy is designed for use with a small number of nominal level data categories. This option assigns a unique color to each data value. For this reason some might be tempted to choose ArcMap's Unique Values option to map rates, densities, or even counts. Logically or not, people prefer colorful maps. Most textbook cartographers would approve of this, since they have long argued that it is the lightness and darkness of colors, not different color hues, that most logically represent quantitative data. Color ramps are sequences of colors that vary from light to dark, where the darkest color is used to represent the highest value range. Users may choose a group of predefined colors, known as a color ramp, or they may specify their own custom colors. Users can adjust the number of classes, the class break values that separate the classes, and the colors used to symbolize the classes. Because our ability to discriminate among colors is limited, attribute data values at the ratio or interval level are usually sorted into four to eight ordinal level categories.
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