Tag Archives: ArcMap

Mapping the GIS Adventure: Maps and Napkins – St. Louis

I recently was tuned into a company in the UK that creates “Mapkins” via a post through the GIS Lounge, and was intrigued. However, for a price tag of $60.00 per four napkin set, the likelihood I would be getting these city customizable napkins was highly unlikely. Also, each set gets one city, whereas I had four cities all picked out in my head. No thank you.

My husband commented that with our artist relatives and friends and my GIS skills, I could probably just make the designs myself and then get them screen-printed for less of a cost (or at least, to exactly my liking). Inspired, I went ahead and started with St. Louis, which is a city I recently visited and quickly loved, and because it’s one of the cities I’ve visited and liked in one of the two states I’ve ever lived in – along with being one of the cities in my list of four whose GIS data I haven’t played around with yet. So, I simply googled “St. Louis GIS data” and off I went.

It should be pointed out that St. Louis actually straddles the Illinois-Missouri state line, and the portion belonging to Illinois is actually referred to as “East St. Louis” and is considered a city separate from St. Louis, MO. I discovered this soon enough because while St. Louis, MO has their GIS stuff together, East St. Louis does not (sorry, East St. Louis – if there’s some secret website I don’t know about, I would love to make a correction). Easily enough, I found the city boundary and street line data for St. Louis, but could not for the life of me find anything for East St. Louis. I finally turned to TIGER data from the Census, and was able to download block level data for the entire state – which is certainly going to be useful for me to have some day, I suppose, but not right now. I was able to select from there the blocks from St. Clair county, where East St. Louis resides. But at that level, I was at a loss of how to select just the East St. Louis bound blocks.

At this point, exasperated, I told my husband we could do without East St. Louis – I really had only visited St. Louis anyway. He looked at me, and said, “I’m sure you can figure it out, you’re a GIS whiz.” Well. With a challenge like that, it was time to rise. I knew I had the tract numbers for the blocks, so if I could just go up a level and see which tracts belonged to East St. Louis, I could select the blocks through that information and bam, East St. Louis. The problem was that information was not particularly available. And here comes the part where someone, one day, will read this and know the easier way to do what I was trying to do and rolls their eyes. To them I say, discovery should not come that easily! Or at least, not while I’m trying to protect my ego.

First, I looked up the East St. Louis boundaries on Google Maps, so I could know what I was looking for exactly.

Google’s idea of where East St. Louis begins and ends, and my reference map.

I then went to American FactFinder and used their “Select Geographies” tool to figure out how to select for East St. Louis. After experimenting with several methods (including their draw a polygon tool – nifty!), I was able to select “East St. Louis” – but this did not yield what I was looking for because tract and block numbers did not appear to be listed within this small geography. But if you do attempt to map St. Clair County tract information (such as AGE BY SEX) through FactFinder’s map tool, you can see which tracts are in East St. Louis. Or, you can ultimately just map the Census tracts through ArcMap and now that you’ve intimately memorized

The various Census tracts of St. Clair county around the East St. Louis area.

the shape of East St. Louis according to Google, info-click each tract following the outline and record which tracts are within the boundary. Then, I selected each tract number within my block layer, and voila! East St. Louis.

Now, I am not a cold-hearted person. I may have just outlined the difficult way to do it, but for your convenience, I have listed the tract numbers I used to select East St. Louis blocks in the table below. Though again, discovery perhaps should not come so easily – but that’s for you to decide.

ctnumbersAlso, please see the rough draft of my potential napkin map below as well. My husband isn’t a fan of color on these potential future napkins, so I’ve gone for spidery black lines for the streets. There will probably also be a scale bar of a different caliber, and a few other stylistic details, but this is the basic idea. I’m already in love. Thanks for reading, and if you have any easier ways to obtain my hard-won information (such as some handy Census resource with a list of each town’s Census tract numbers), please share! I love learning the easy way.estl

 UPDATE: One of my good friends read this post and recalled that the Census has to list the tracts in each county, so she searched for such a list and came up with the map below. Link is here:

I told you someone would get me the easy way! From the U.S. Census
Zoomed in.

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 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?

Mapping the GIS Adventure – Lab 4: Maps Are Where “Y’all” and “Eh?” Can Be Said in the Same Breath


I remember this mapping assignment with strong feelings. This was our fourth assignment, and we were into our fifth week of the semester, and I was struggling a little when it came to these maps. I was also feeling inadequate, as I had not yet made friends in the class and was perceiving everyone around me to be plugging along just fine. Of course, actually, everyone was learning this new skill as I was, and we all probably would have benefited if we had started talking to each other a lot sooner. So the map that gave me such terror was actually pretty simple: provide a size comparison between the state of Texas and the Canadian province, Nunavut. Along with this, the skill we were to learn was that of projection, both on-the-fly and permanent.

If there's any question, I reprojected all of these themes into the Canada Lambert Conformal Conic coordinate system.
If there’s any question, I reprojected all of these themes into the Canada Lambert Conformal Conic coordinate system.

The requirements for this map were similar as those of the previous labs, but also required us to get a dose of ArcCatalog and create a table that listed all of the data that we were using for the Canada map, and their original projections, and then the projections we reprojected them to, which needed to be a conformal projection. These were to be permanent reprojections, while the Texas map didn’t require permanent reprojections, but instead on-the-fly projections.  Presently, this doesn’t seem hard at all. At the time, wrapping my mind around it was impossible. The biggest issue was merely that I didn’t understand that on-the-fly projection could trump permanent projections. So even though I reprojected all of my themes correctly, I never changed the coordinate systems of the data frame, so I never saw a difference, until I learned what was going on later.

One big thing: this was where we were supposed to learn the difference between the  “Define Projection” and actual “Project” tools. My professor warned us all, multiple times to be very, very careful that we understood the difference between the two. While I certainly had an unfortunate experience with this map, I do thank the heavens that I understood the difference almost immediately. It would probably have been the straw that broke the camel’s back otherwise.

Otherwise, this map is one of my favorite maps I’ve created so far. I won’t lie – it’s because I find it pretty. The raster I used to show the physiography of Canada utilizes the same color spectrum as most physiography maps, but never before have I wanted to wax poetic on one. That might just be a dedication to Canada’s physical appearance, and I’m not even ashamed. In terms of other map elements, we were also required to show the railroads and major roads of Canada and it took me a while to figure out which colors worked best, but I feel pretty good about my bright purple for major roads and midnight blue for railroads. And I must shout kudos to esri’s ArcMap railroad symbology. Well done.

Otherwise, we were also supposed to clearly highlight Nunavut and clearly show Iqaluit, the capital of Nunavut. You’ll note that someone has definitely learned to use the “select” tool, as Iqaluit is the only city on there. The only one. Hurrah for me, because when I first took a stab at this map, I still had the selection skills of Lab 2. As for highlighting Nunavut, I think I don’t do so as successfully as say, Texas is highlighted in the inset. This is partially due to the fact the physiography needed to be clear, but was also really strong. So even though Nunavut has a different overall coloring, a red outline, and two large names shouting out to the viewer, the eye is not immediately drawn to it. To rectify that, I would have probably made the physiography a lot lighter with transparency, so that way Nunavut would have stood out more. I also would have done something about the outline, such as a black outline to strengthen the border of it.

The inset of the Texas map was pretty easy. Texas was red, outlined in black, and the rest of the visible states were yellow, outlined in gray. Not too hard to make that work, given physiography wasn’t necessary. The only aspect I found giving me issue was the scale, but once I adjusted the data frame for the Texas map, I was able to have them at a matching scale. Based off of the map, I hope you all agree with me that Texas, while my favorite big state, is still definitely smaller than Nunavut. If you don’t, I’ve failed because Nunavut has some 500,000+ miles on Texas. No, not EVERYTHING is bigger in Texas…

As for my technical aspects of the map, such as the legend, scale bar, and North arrow, I’m pretty satisfied with my space usage and placement, though I definitely would have done well to somehow fit that scale bar directly beneath Canada, so that way the ends lined up with the edges of Nunavut. I just did the finger test myself and they totally would have matched up and would have saved a lot of readers the irritation of keeping their fingers the same width apart as they moved them to Nunavut.

What cracks me up now is how this map turned from a pain in my rear to truly, one of my favorite maps. Under the rules of our class, I was allowed one free lab that  could be turned in late with no late penalty. As we already had one lab due a week, I sat on this lab all the way to Spring Break to work on it with no other requirements breathing down my neck. I remember redoing the assigned tutorials and changing the projections and realizing just how not hard this assignment was. I was able to have fun with it, and realize that a colored background wasn’t always the best way to go. I understood things I hadn’t gotten before. Lastly, you can bet getting that map done and turning it in was the best kind of relieving success.

Most of all, I learned the importance of doing your work when you’re assigned it, and crawling before you walk. The struggle to understand a concept may be torture, but once you learn it, you learn it. It helps set you up for the next struggle, with a lot more ease than if you hadn’t survived the prior one.