HW09: Geospatial visualization

Nov 9, 2022 3 min read

Overview

Due by 11:59pm on November 15th.

Accessing the hw09 repository

Go here and find your copy of the hw09 repository. It follows the naming convention hw09-<USERNAME>. Clone the repository to your computer.

Generate a geospatial visualization

Your objective: use geopspatial visualizations to communicate a story.

Is that really all the help I get?

Yes.

Arrrrrrrrgh but that is so vague

I know. But at this point you should be able to rise to the occasion.

But where do I start?

Think of data you’ve seen in the past that you think would make for a good geospatial visualization. Which means it needs to include both a geographic component plus some additional data to overlay on top of the geography.

As for drawing the geographic boundaries, that depends on what you want to map. Find a relevant shapefile or GeoJSON which contains the boundaries for the region you wish to visualize. Google is a great starting point. If you need help finding a relevant shapefile, feel free to post on the discussion board to get help from the instructional staff/peers.

Some suggested sources compiled by Deblina Mukherjee, a previous TA for the course:

  • City Open Data Portals - Check here to see what any city has available.
  • The government more generally. Geospatial data is kind of hard to generate individually. Also consider the tidycensus package for any data related to the United States and demographics. Remember you can use tidycensus purely for the spatial features, then merge it with outside datasets that contain the substantive variables of interest.
  • The Array of Things - it contains lots of different data from independent street-level sensors, all based in Chicago.

Once you have your geographic boundaries data (either from an R package or imported from an external file), combine this with your substantive data you wish to visualize. Be sure to make the graph presentable - that is, make it look like a nice map. Things to consider include (but are not limited to):

  • A map projection system
  • Appropriate legends, titles, labels, etc.
  • Color palette

Along with the maps, write a brief description (250-500 words). Summarize the information being depicted and explain any major visual design choices (e.g. why this color palette, why split the continuous variable into XYZ intervals rather than ABC intervals).

How many maps do I need to make?

As many as it takes to tell your story. The more ambitious your analysis, the more you can be rewarded in your evaluation. Create a single map with all the default labels/settings? Your effort will be reflected in your evaluation.

Remember to make your assignment reproducible. If you get a shapefile from the internet, either include it in your repo or make sure your Quarto document/R script includes a function to download it from the internet.

Submit the assignment

Your assignment should be submitted an Quarto document using the gfm (GitHub Flavored Markdown) format. Follow instructions on homework workflow.

Rubric

Needs improvement: Cannot get code to run or is poorly documented. No documentation in the README file. Severe misinterpretations of the results. Overall a shoddy or incomplete assignment. Maps look amateurish or hard to interpret.

Satisfactory: Solid effort. Hits all the elements. No clear mistakes. Easy to follow (both the code and the output). Nothing spectacular, either bad or good.

Excellent: Interpretation is clear and in-depth. Accurately interprets the results, with appropriate caveats for what the technique can and cannot do. Code is reproducible. Writes a user-friendly README file. Graphs look crisp, easy-to-read, and communicates information honestly and accurately.

Benjamin Soltoff
Benjamin Soltoff
Lecturer in Information Science