Tag Archives: mapping the gis adventure

Mapping the GIS Adventure: I Need a Doctor, but I’m Brown in Chicago

What really convinced me to stay in my new cartography course despite having already taken a cartography course was not only that I would be expected to utilize Illustrator, but also that I would be encouraged to make maps that relate to my work. As a graduate student, I am planning on studying Latinx, specifically women in Chicago and possibly San Antonio, and their access to healthcare and how their ethnicity and race affect it. For this specific map assignment, we were expected to create a grayscale choropleth map with an inset, of any area and it needed to help us with our work, and hopefully would be “interesting.” In this case, I thought it might be interesting to check out what the City of Chicago had by way of healthcare facilities and population data. Sure enough, the City of Chicago has plenty of data and fairly well organized. Although, they don’t seem to get back to FOIA requests very quickly…or at all (more on that later).

At first, I had planned to use block data for this map, but there were so many blocks the map was virtually unreadable at a large scale in choropleth form. So, I chose census tracts instead and off I went. I then chose to add all of their current hospitals and clinics according to the City of Chicago. And as you can see, Latinx are clustered in specific areas of Chicago – areas that are wanting in large numbers of healthcare facilities. I was really happy with this map, because it was the first clear picture I had on the area and demographic I was interested in studying. Plus, dealing with the Chicago data was a delight, and reminding myself how to use Census data was of course a great exercise.

With this map, I thought it was important to differentiate between the types of healthcare facilities, which I tried to do using stars, squares, circles, and triangles, though at this scale, it was a bit difficult when they were clustered together. The font I used was Berlin Sans FB, which I really enjoyed as part of the tone of the map. In the original that I turned in for class, I received feedback from my classmates that the font choice was strange for the legend – which was because at the time, it was bolded, so I changed that and I agree that it’s much easier to read. I was also missing a North arrow, which I fixed here. Other comments from my reviewers included a disagreement on using equal interval to display my data which I question, considering we’re dealing with whole people here, and equal interval allows an equal distribution among census tracts – allowing for what I believe, would be the most fair display of where Latinx people are in Chicago. One other reviewer offered the suggestion of using ratio data, and I do believe that percentages might have been slightly clearer to the map reader, but I think it still makes a point.

I added the Expressway because my professor thought a major road would help people anchor themselves locationally around Chicago. This was a bit difficult to do because the road lines are in pieces in shapefiles and I had string them together as a selection. I also am not familiar with Chicago, or its major roads – one friend suggested I add the “loop” which is something to look into. But the rest of the pieces on this map were pretty straightforward. It was this map that made me realize I enjoy having insets on my maps. They help balance the map.

Some Illustrator points:

  • The symbols for healthcare facilities have two lines, which is hard to see on the map but in the legend it goes, white fill, gray inner stroke and then black outer stroke. I created this by going into the Appearance tab and added a stroke, bumped up the thickness, and changed the line color.
  • I then used the Graphic Styles tab to add this as a Graphic Style (I do this for most things) and then selected each symbol and then selected the Graphic Style to change it. I love the Graphic Styles tool.
  • I don’t exactly know what I did to the dashed line to make it hide behind parts of Chicago, but I know that it’s not because it’s behind it in the layers, especially with the scrunched up areas later. I’ll play with that.

What are your thoughts?

Oh, and as for my FOIA comment – I originally was having a hard time getting the block data (before I realized I didn’t want to use it) from the City of Chicago’s website when it should have been available according to the website. So I called the Information people who sent me to a GIS guy for the City of Chicago, and he told me that I would have to submit a FOIA request and he would be able to send it over within the week. I did so, and as of 10/26/2016, still have not received the data. Luckily, I know how to use the American FactFinder (Do you?)


Mapping the GIS Adventure – Lab 6: Y’all, That Texas Coastline is Killer

You might notice that I skipped Lab 5. This is due to the unfortunate fact that I accidentally lost my Lab 5 pdf. I still have the map, so I think I’ll be able to recreate it, but I haven’t had a chance to go digging. Since it’s been a little bit since my last post, I decided to skip ahead to Lab 6.

This lab was all about fun of digitizing, which my professor has frequently promised will be a skill I will utilize again and again. When I started the map, I was back in the midst of the crazy semester, getting swamped by all the new information and work coming my way in GIS. I was desperate to not turn in this map late, and also very, very confused.


Digitization isn’t too hard per say, but it is time consuming. And potentially painful. I remember the night I sat down to digitize the whole map of Texas. But before that nice recollection, the details: The goal of the map was to provide a clear map of the ecoregions of Texas for state parks of Texas.  The requirements:

  • projection of the Texas data to a Texas centric projection
  • georeferencing of the Texas image
  • correct digitization of the polygons
  • assigning two attributes to each polygon construction
    • attribute 1: integer field containing the ecosystem
      number from the map
    • attribute 2: a text field with enough characters to
      hold each ecosystem name
  • An intelligible legend

So, back to the night I sat down to digitize. I had already successfully georeferenced the Texas image – or so I had thought. One of my friends kindly showed me that my amount of georeferencing points was way too high (28 as opposed to an upper limit of 20) and I hadn’t applied the suggested 2nd polynomial warp. So after georefencing again, I found myself ready to digitize. I began drawing polygons and utilizing a snapping tool, so that way I could avoid the dreaded “polygon slivers.” I can only imagine what kind of ruination would have come to me with slivers.  As I created my polygons, I realized why it was going to be torture: as I descended upon the Texas

I believe this was about an hour after I started making those polygons.
I believe this was about an hour after I started making those polygons.

coastline, I found myself upon these craggy sections. I wanted to make sure I captured most of the detail, but also wanted to avoid having too many nodes. And as I clicked my way through that coast, I realized I was clicking my way to what also felt like carpal tunnel. Oooh, the agony. Worse, the polygons do still have some issues: along that coastline, which I did streamline a bit, you can see that the details aren’t highlighted due to coloring. This doesn’t worry me as much, because of the small number of parks along that coastline and the fact that such details of the coastline were less necessary for the goal of the map.

However, I did persevere and was able to complete the digitization. So I then proceeded to color the polygons and create that intelligible legend. As to how “intelligible” that legend actually was, well. I found I was able to simply pull the polygons into the legend, but I couldn’t figure out how to remove duplicates from the legend. I have since learned that it’s all in the legend details – simply delete the duplicates. But alas, at the time I did not know this, so for every region that exists, there is the color swatch and the number of those pops up. The Texas state parks locations also are included. However, I do wonder if my data had the names of the Texas state parks. If I did, that probably would have been a good addition to the map because I feel like while the state parks probably would have known where they are, thanks to the addition of the county lines. At the same time, there are a lot of state parks on that map and it would have just really added to the overall clarity of the map.  I also could have done well to provide more information about where my data came from. Because don’t we know that I did not make that stuff myself. I also didn’t mention my coordinate system or datum, which does no good.

In general, this is around the time that the labs starting becoming more about the technical aspects behind it. The results were of course extremely important, but the little things done behind the visual started to become very important. We went from simple technical aspects to understanding that while you could hypothetically fake a pretty map on the surface, if you started to leave out all that nitty gritty technical stuff, your map is fairly worthless. Of course, I didn’t figure this out until several maps later.