DV

Assignment

Mapping data

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1. Examples of encoding using points, lines, and areas

Find example maps on the Internet that encode information for each of the following cases:

1. Points showing qualitative information
2. Points showing quantitative information
3. Lines showing qualitative information
4. Lines showing quantitative information
5. Areas showing qualitative information
6. Areas showing quantitative information

2. “Globe view” in Google maps

In 2018, “Globe view” was added to Google maps (when viewing from a desktop, not a mobile application).

1. In THIS context, discuss the strengths and limitations of the Mercator projection. Any general strengths and limitations (uncontextualized to google maps) will be ignored.
2. When is it appropriate to use the “Globe view”? When is it not?
3. In mobile applications, Google maps does not offer “Globe view”. From the data analysis perspective, discuss the potential consequences of this missing feature.
4. What projection does the Globe view use?

3. John Nelson’s hurricanes map

John Nelson’s map below visualizes the paths of all hurricanes and tropical storms based on the National Oceanic and Atmospheric Administration records. It is a bottoms-up view of known tropical storms and hurricanes dating back to 1851. What projection is this figure? The options are Mollweide, Hammer, Eckert IV, Robinson, Lambert azimuthal, Albers equal-area, and Cylindrical equal-area (see Figure 10.6 in the TTA book).

4. Design a flow map using your data

A flow map, such as the one below, can show the movement of entities between geographic areas. Draw a flow map displaying your address area as the flow source and ten places you visit most frequently as the destinations. The thickness of the lines should reflect the average number of times you visit the place. To preserve your privacy, you are welcome to distort/fake some of your data.

5. Add a line of distortion

The map below is a conical equal-area projection of a region in the globe. The thick red lines are standard lines, i.e., areas of the globe tangent to the globe. Observing how blue lines of distortion can be used to show maximum and minimum distortion in Figure 10.2 of the TTA book, add a distortion line (along with gradients) to the map below.

6. Final version of the UMSL data graphic

This homework is a follow-up on the previous data graphic design homework and the peer-review homework just before this. After the classroom discussions and your own experiences of peer reviews, you now may have several ideas to improve the UMSL data graphic you designed. Improve your visualization design based on your observations of others’ tables, your peer-review experiences, and the peer-reviews you received (if you did).

Submit all three:

1. The original UMSL data graphic and the appropriate reference for finding it.
2. The data graphic you initially designed.
3. Final version of the data graphic.

Using bullets, also discuss what changes you made to your design after the evaluation and peer review discussions.

7. A project on choropleth map designs

General requirements:

• For all designs, please use an appropriate projection (i.e., do not use projections such as the Mercator).
• At each step, include a few sentences discussing your design process (i.e., which tool you used and how).
• All maps should include meaningful and appropriate legends.
• You are free to use any online tool or software as long as you include a sufficient description of how you used them.

Step 1:

Using the 2022 world population data, design a choropleth map showing the population density for all countries. Discuss at least one potential issue in your map visualization.

Below is what your visualization may look like. Please note this map was designed using different data.

Step 2:

Showing the population densities of all the countries, design a strip plot and/or histogram (similar to Figure 10.24 in the TTA book). Observing your histogram, discuss what you can infer about the distribution of the population densities.

Step 3:

Using the “intervals of constant size” approach, divide your data into 8 classes (bins) and redesign your choropleth map. Also, redesign and include the histogram (or strip plot) showing the 8 classes.

Step 4:

Using the “quantiles” approach, divide your data into 8 classes (bins) such that approximately an equal number of countries are placed inside each class and redesign your choropleth map. Also, redesign and include the histogram (or strip plot) showing the 8 classes. Discuss your process.

Step 5:

Using the “diverging color schemes” approach, divide your data into an appropriate number of classes (bins) and redesign your choropleth map. Also, redesign and include the histogram (or strip plot) showing the 8 classes. Discuss your process.

Step 6:

Choropleth maps generally have at least one shortcoming: they shadow (defocus) regions that are small in size. One way to overcome this shortcoming is to design a cartogram. Design a cartogram for visualizing the population density data. Countries should be labeled appropriately in your cartogram.