Map Projections

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The lab this week based on Geospatial Data Management has been by far, the most enjoyable lab this quarter. While at the beginning the lab was a little bit confusing, one I had the first map finished the next five were very manageable and quite fun. One of the highlights in my opinion in this lab was the ability I had to creatively arrange and organize my map presentation. While the creative side of me was very happy with this lab, it also was extremely informative. When compared to last week’s lab, which was not only extremely stressful but so dense that I barely recall anything, and would in fact have to resort back to the tutorial, this lab allowed me to take away the knowledge and tools needed to create these map projections.

The map projections that were created this week served as a very large eye opener to me. I suppose I have never really given any thought to how inaccurate map projections can be. From the lectures that discussed preservation of one thing over many things, I am visually able to understand what Sheng meant. The first set of projections, which are the conformal map projections, allow for the reader to see that while distance may not be preserved, the angles of the grid are all right angles. From my own personal experience, I feel as if the most common map projections I have seen throughout school are conformal, with a key element being that Antarctica is blown severely out of proportion.

The second set of projections I created were the equal area projections. Consisting of the Mollweide and Bonne projections, these maps give way to an awkward shape of the earth, but in means of keeping the area of places preserved. These two projections are ones that I haven’t seen before, and I only found out about via this lab. The third set of projections used were the Sinusoidal and Plate Carree models, which preserve the distance from one place to another.

In this week’s lab we had to locate Washington D.C. and Kabul, and using different map projections find the distance between the two cities. Things of this nature to not come easily to me to visualize, so when Professor Sheng discussed this in lecture the concept was very hard for me to grasp. However, this lab was excellent in demonstrating to me how different methods of preserving key elements of a map can severely change the distance measured from one point to the next. For this exercise, each type of projection had two models. In two of the projection groups, conformal and equal distance I had large discrepancies in distance between point A (Washington) and point B (Kabul). The first set of models, Mercator and Gall Stereographic gave me distances of roughly 10,000 miles and 7,000 miles. The second set of models, Sinusoidal and Plate Carree had distances of roughly 10,000 miles and 8,000 miles (for exact distance see maps). A few thousand miles, in my opinion is a wide margin of discrepancy for maps preserving the same element. The last two models, Mollweide and Bonne came in with the closest distances at roughly 7,900 miles to 6,700 miles. While this projection still has a 1,000 mile discrepancy, it was the closest of the three projections. I will add that I do not know if these large margins of distance between similar models is normal or error.