Mapping the GIS Adventure – Lab 7: Pollution is Bad, and It Might Be in Antarctica

Note: Sorry for the long hiatus. The fall semester took a lot of effort! But I’ve got tons of new maps and labs for y’all, so look out!

Lab 7 was a real turning point in the semester for me. I had made friends in my lab section, so I had back up when the technical parts got confusing, and even so, I managed to get the ArcGIS functions done correctly. The lab was turned in on time, and had received well enough marks. Also, the lab used real world data! Or as my professor puts it: “The good part about the lab is that it uses real world examples; the bad part about this lab is that it uses real world examples!”

Because yes, my wonderful professor was hoping to teach us an important detail about real world data: it’s not all it’s cracked up to be. We were working with soil sample data that my professor collects every year when he visits Antarctica (sidenote: he later left us before the semester ended to go there and would Skype with us during class). This data included the total petroleum hydrocarbons in randomly selected areas around McMurdo Station. So what technical things did I have to undertake?

  1. Create a personal geodatabase that contained only two of the feature classes that were available in the soil sample data and of course, create those two feature classes and convert them into point feature classes.
  2. Compute some selected statistics. This was just utilizing some statistics features because my professor, bless him, knows that statistics is important and we need to learn how to do statistical functions.
  3. Join data tables together. Shockingly to me now, one of the hardest parts about this lab for me to do back when. Another quote from my professor: “Sometimes success with joins just requires a bit of patience.”
  4. Then the map! It had to have color. It had to have graduated symbols. It had to show the distribution of Total Petroleum Hydrocarbons in the soil samples, overlaid on an aerial photograph of the station. They had to be broken into two categories, “random” and “intensive” and each category broken into three classes: 0-30.0 ppm, 30.1-4100.0 ppm, 4100.1-maximum TPH.

The boring part of this was that I had to make probably at least five geodatabases before I ever got near correctly making them correctly, only to realize my point feature classes were not actually converted into point feature classes, which was terrifying because none of my data was showing up in the data frame. Why did this happen? Because I didn’t completely read through my lab instructions, where my professor had purposely included bolded details on system quirks that may or may not derail us. A lot of this class was reading instructions, and a lot of my takeaway was the importance of reading instructions.

But once I figured out how to correctly join (or relate) some tables, make a geodatabase (and, ah, no, this was not with Python yet), and overlay it on the aerial photograph, it all came down to just the map. So what did I do? Well, we had three classes, and I broke up the data by those classes, and then had to have different corresponding colors with the classes and categories. With my colors, I was attempting to make a clear ascension into darker colors – now I probably would have used the same hue, with a different saturation, but ah well. I don’t think the ascension comes off cleanly here. With that, the bright pink and green for the small circles no longer works for me, because that draws more attention than say, the bigger circles. Of course, there are a ton of the small circles, but when you look at the map, the bigger circles sort of just fall away which is really disappointing because in terms of pollution, I would want to know immediately where the highest levels of pollution are.

Circles and bright colors, because what else is going to stand out against that drab Antarctica landscape?
Circles and bright colors, because what else is going to stand out against that drab Antarctica landscape?

Another issue that was pointed out to me by a fellow blogger was the lack of differentiation among the symbols. Now it’s obvious to me; different categories, different symbols, yeah? This is addressed in a later lab. Once again, my scale bar is a mess – all of those extra classes are unnecessary, and it just goes to show that I still didn’t know how to manipulate that little tool yet. I do like my map set up some. Something I would like to continue to experiment with is putting the title of my map on the map, as was done here. After taking my thematic cartography class, experimenting with text placement juxtaposed with map data seems like a fun experiment to look into. My north arrow was out of the way and discreet. I also liked all of the data information at the bottom as sort of a caption to the map.

That’s all for now, but wait until I show you the next map; I made one change, but oh how I wish there had been more. Any suggestions yourself?

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