Author note: This exercise was written by Leah Meisterlin and Grga Basic (2017). Updated in 2022 by Mario Giampieri and Leah Meisterlin.
Given the reliance of spatial analysis on the geographic specificities of our data, working toward developing analytical methods also means developing a firm grasp of coordinate systems and their implications for measuring position and other spatial relationships.
For this exercise, you are tasked with communicating the distance between major cities of your choosing around the world. Imagine you are tasked with conveying to a lay audience how near (or distant) cities are to each other relative to popular conception.
Most map users give little thought to the map projection used for a large-scale map (map of a small area). As the map scale becomes smaller and the area shown increases, the properties of a map projection become increasingly more important and apparent. Whether we are reading or creating a map, it is important to be aware of the projection. Purposely or not, maps are political objects, and the choice of projection is a critical one. What aspects of a map are represented accurately, and which are distorted – and are those choices appropriate to what’s being communicated? In this exercise, we will familiarize ourselves with different map projections, reveal its characteristics, advantages (and disadvantages), and explore the workflow between CAD/Rhino and GIS software in the process.
Complete the exercise, answering the embedded questions for discussion.
Once completed, produce four maps composed as landscape 8.5”x11” pages and submit combined together as a single PDF (each on its own page).
You should have developed Mercator, Peters, and Robinson maps—and one more with a projection of your choosing. Make sure the paths are clearly visible in all four maps and are the primary focus in the overall composition of each map. Remember that the primary goal of each map is to convey the spatial relationships between the cities you chose, so include labels for each city and the distance between each cities expressed as miles.
<aside> 💾 Download and unzip the exercise data package, saving it to your working directory. Exercise Data packages are accessible via Google Drive with a Columbia University UNI login. If you would like a copy of the full course materials, see here.
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This exercise uses data compiled by Esri: World Countries, World Cities, and World Latitude and Longitude Grid, from the same collection described in the “Data Sources” section of our previous Mapping Basic Data Types: Representing Global Urbanity exercise.
<aside> 💻 This section does not introduce new software skills, but does rely on a few basics we covered in the previous exercise. You should be able to access attributes (within a vector layer’s table) and apply categorical symbols to vector features (those tutorials are included below as a review). For additional review of symbology see Basic Symbology & Classification in ArcGIS Pro.
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Open a new, blank map project. Add the World Countries feature layer to the map, and symbolize the countries with a fill color of 60% grey and a white outline color.
Add the World Cities layer and the Grid layer to the map, ensuring that the grid is at the top of the drawing order. You will notice that the 1-degree grid is not legible at this scale.
Open the attribute table for the grid layer and inspect the layer’s attributes. You will notice attributes that allow for the display the grid at intervals of 1, 5, 10, 15, 20, and 30 degrees.
Create a categorical symbology for the layer using the Degree5 field, and adjust the line width and color to create a more legible reference grid for your map.