Data Classification

The module this week had us exploring different classification methods for data.  The ones we looked at most closely and used for this lab were equal interval, quantile, natural breaks, and standard deviation.  These different classification systems determine what groups data are divided into and thus was color they correspond to on a choropleth map.  Therefore, the classification style chosen for a map can greatly effect the message that it conveys to the audience.  It is important to know what each classification system does and when best to apply it as to not create maps that are misleading.

The equal interval system divides the data into range breaks of equal size based off of number of classes desired.  The range breaks will get however much data there is within the ranges - whether they contain most of the data or none at all.  The ranges are thus almost always going to be unequally filled because of how they are equally spaced out.

The quantile system classifies data into categories with an equal number of data values within each category.  The spacing within the categories will be uneven, but the quantity of content within each class is equal.

The natural break system uses a mathematical algorithm to calculate natural groupings within the data.  The algorithm computes a unique grouping of classifications for each data set. Because how tailored it is this is a preferred choice for many maps.

For standard deviation, classes are created by adding or subtracting the standard deviation from the mean of the dataset. Standard deviation does a good job at creating (statistically) evenly spaced classes.  The way that the data is broken into classes is statistically logical. However, a casual audience may not understand what standard deviation is.

For this project we used census tract data for Miami-Dade county to create maps showing the senior population using different classification methods.  I created eight maps in all.  The first set was the percentage of seniors in each census tract displayed via equal interval, quantile, natural breaks, and standard deviation classifications.  The second used the same grouping of classifications but normalized the population based off of square mileage to find the density of the senior population in each census tract.  The purpose of the lab was to get us to understand the differences between classification systems, how to normalize data, and the overall usage of choropleth maps.  All of this work was performed using ArcGIS Pro.

The percent of senior citizens living within different census tracts of Miami-Dade County.

The population density living within different census tracts of Miami-Dade County.  This data took the count of senior living in each census tract and normalized it based off of the square mileage of each tract.

Most of this maps all use the same graduated bluish-purple color ramp except for the standard deviation maps.  This is because standard deviation maps typically use a diverging color ramp - one color for the classes below the mean and another for those above.

The natural breaks map normalized by square mileage isolated.  This is a strong map for both presentation and for data interpretation. 

I organized the map frames in this order because I believe that they go from conceptually easiest to understand to hardest.  Equal interval is very straight-forward, and quantile is one step of complexity above that.  The actual algorithm behind natural breaks is fairly sophisticated, but it is easy to explain to someone that they are grouped into most alike classes.  Standard deviation is harder to explain to someone without a statistics primer first.  If your audience isn't mathematically inclined using this methodology requires an extra layer of explanation in a way that the others do not. 

The best classification method for this map is natural breaks.  Since the algorithm finds the best class sections within the data it creates a map with good contrast while taking into account possible outliers.  The equal interval maps for both percent and density make it look like there are hardly any seniors at all. While the standard deviation classification is mathematically sound, it is difficult to explain to an audience who is not mathematically oriented and may not be interested in a lengthy explanation.  Quantile also produces a pretty solid looking map, but I like how natural breaks takes into account the grouping of the data. Where people live is influenced by a lot of factors, such as cost of living and access to health care so to divide the data up arbitrarily in quantiles has the potential to be problematic.  It makes more sense to use natural breaks which is able to take into account natural clusters of data.

Additionally, using the natural breaks map that is normalized by square mileage makes the most sense. Normalized data is a more useful depiction than the percentage maps.  If a county official was using a map to determine funding for geriatric-specific medical care, it makes more sense for that official to consult a population density map.  The density map makes comparisons between counties equal, while a percent map the comparisons do not easily transfer between counties.

To further drive this point, imagine if the city official was tasked with allocating funding to ambulances for each tract.  If the official looked at just the percentage, they would assign a large number of ambulances to that rather small dark purple tract that shows up in the Northeast quadrant of the county, but hardly any to the much larger country directly West of it.  When consulting the normalized natural breaks map, these two quadrants are in the same class. Resources should probably be allocated approximately equally between them instead making that decision off of the less balanced population map.

Cartographic Design

This week's lesson introduced us to the elements of cartographic design.  This involved learning about the Gestalt principles of things like visual hierarchy, contrast, figure-ground, and balance.  Utilizing these principles serves as a framework for learning how to properly construct a map that is visually beautiful through its layout and how well it conveys its primary goals to the viewer. 

The goal of this map was to display the location of the public K-12 schools of Ward 7 in Washington, D.C. using the cartographic principles of design we had just learned.  The base data was provided for us, but I had to decide how to lay out the content in such a way to make it visually useful.  The bulk of the map work was preformed in ArcGIS Pro with some final touch up work being completed in Adobe Illustrator.

The location of K-12 public schools located within Ward 7 of Washington, D.C.  The primary objective of this lab was to understand and implement the various principles of proper cartographic design.

In creating a map that will show the schools of Ward 7, part of the assignment was to create appropriate symbology for the schools.  I made the school symbols increase in size with the elementary schools having the smallest icons and the high schools having the largest.  The icons are a vibrant purple and yellow which make them contrast against the duller neutral earth tones of the map.  The assignment did not explicitly request the the names of the schools be listed, but without that information the utility of the map is limited.  So I took the symbology another step and coded the shade of yellow to the school type.  This makes it so looking at the list of schools it is easy to pick out the school's designation and unite it to its symbol.

Another thing I learned in this lab was the use of annotations in ArcGIS.  I used this to create text for the neighborhoods within Ward 7.  The default placement of the text contested with some of the other map elements so I carefully had to change their placement so they appropriately blended in with the rest of the map.  A large part of this lab was dealing with the design principle known as "visual hierarchy" which means placing the most important elements in such a way that they are most visible while deemphasizing the background information.  The names of the neighborhoods provides great contextualizing content - especially considering what school a child goes to often depends on what neighborhood they live in.  However, the neighborhoods are not the most important part of the map so they are displayed in a more washed-out gray text.

The concept of figure ground is the notion of making the most important part of the map distinct against the background.  This put focus on the area of interest.  For this lab, I used the screening technique to make Ward 7 lighter than it surroundings and pop out against the darker background.

The shape of Ward 7 naturally lends itself to creating empty space for the placement of other map elements.  By putting content such as the legend and the scale bar in these places it creates a sense of balance within the map.  I tried not to cluster too much information in one particular place so that no part of the map seemed too heavy but instead complemented the central focus of the map.

Typography

The focus of this week's module was typography. This involved learning a lot about the anatomy of a font, when it is appropriate to use certain kinds of fonts, and standard cartographic practices in order to create maps that are easy to understand. The objective of this module was to design a map of Marathon, Florida using the typographic principles we have learned to label designated features in a way that makes sense to the viewer.  I used ArcGIS Pro to create the initial map which was then shared to ArcGIS Online.  Using the ArcGIS Maps extension  I was able to import the map into Adobe Illustrator Creative Cloud where most of the cartographic work was performed.

A map of Marathon, Florida showing some key landmarks such as the airport. The vector file for the land was exported from ArcGIS Pro and most of the map creation was done using Adobe Illustrator Creative Cloud.

For my map of Marathon, Florida I used the font Trebuchet MS. This sans serif font is not only easy to read but one of the most popular fonts in web design making it familiar to viewers. Additionally, the font family includes bold, italic, and a bold italic style in addition to its regular style giving it versatility.

Varying how type is used creates a visual hierarchy for the map. This is important so that the reader of the map can quickly seek out and determine what is the most important information for them. Most of the visual hierarchy on this map was created using ordinal differences of size. For example, the text used for the cities is larger than the text used for the points of interest.

Due to the narrow nature of the keys themselves, I had to make use of leader lines to point to key features on the map. All the leader lines are the same color and thickness. I made sure to place the leader lines on only a few different angles as not to overly clutter up the map. I also used different symbols for places like the airport or the state park to make them easy for the viewer to seek out.

We were instructed to make three customizations on the map to make it visually our own. One of the customizations I made was a water color paper effect on the blue water background. This was added with the Effect>Artistic>Watercolor. This makes the edges around the map lighter and giving it more visual intrigue. In the same vein, I added a light drop shadow around the islands as well.

Another addition I made was to add in a line for the overseas highway. Without the highway Marathon looks completely disconnected from the rest of Florida which is not accurate to life. I made the road red which is an intuitive standard for roadways. I also added in highway shields so that it is clear which road it is.

My third customization was to place an outer glow behind the text for each of the keys. The keys already are in all uppercase and have a modified kerning so that even though it is the same font family as all the other text on the map they already look distinct. I added the glow to make it even more apparent that they have a different geographic meaning (they indicate the islands) than other text.