Tag Archives: texas

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.

Lab6

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.

Mapping the GIS Adventure – Lab 3: Prior Planning Prevents Poor Map Presentation

So, I was working on my preparation for my post about Lab 3, only to realize that I had erred: my Lab 2 map that I had posted was actually my Lab 3 map. Apparently, I had since deleted my Lab 2 map because it was poorly done. So I thought to myself, what now?

Since I have already pointed out all of the issues with the map you saw previously, I decided it would be fun to try and redo the map again. I looked up all the requirements my professor had for us, and pulled out the old data, and here we are, the new and improved Texas Transportation Corridor map:Lab3Redo

So, the requirements aren’t much different from what I described for my first Texas Transportation Corridor. I needed the following:

  • Major Texas cities with built up areas, displaying relationship between cities and trans corridors
  • Smaller Texas cities and towns, labeled, showing how non-major metropolitan areas benefit
  • Existing roads and corridors, clearly differentiated
  • Visually pleasing raster image as background
  • Reasonable scale
  • Graphical scale bar and representative scale bar with appropriate units
  • Graticule
  • Legend
  • Title
  • Citation of data source and cartographer
  • Map projection and datum
  • Date created
  • Neatline

In my last map, all that marked the cities, major or not, were circles with varying sizes. I found myself choosing to represent the major cities this time with polygons of their areas, exactly for the proper display of their built up areas. For the major cities, I made sure to also bump up the text size and bold and add a small mask as well, so that way the names would stand out. I also minimized what I considered “major cities.” I originally hadnot only San Antonio, Houston, Dallas-Fort Worth and Austin, but Corpus Christi, Lubbock, and El Paso as major cities too. While these are certainly notable cities in Texas, they differ wildly in size when compared to the original four.

When I decided on the small towns I would include, I relegated Lubbock, El Paso, and Corpus Christi into that group. I chose the following cities for several reasons: they were either well known, near a junction of corridors, major roads, and interstates, or they were in an area where I had yet to include many cities to aid understanding of how areas may be affected. I included these reasons in the following list.city table

For the small cities, I simply used a light blue dot of the same size as representation.  The text size is smaller, and they aren’t bolded, although they do utilize Arial font. They also have a mask, because against that raster it is hard to get anything clear enough for reading.

When looking back on both my first version of this map, and the Department of Transportation’s map, I noticed that the DoT’s map had the corridors separated into two groups by color. This was originally unclear as to why for me, but once I dug through my data a little more, I found that they could be defined by priority, high or low. A google search later, I learned this meant the kind of traffic they handled. I agreed with DoT that this was important for map viewers to know and thus, my high priority roads are defined by a goldenrod color, while my low priority roads are defined by a sort of electric blue. I also bumped up their thickness to ensure they were clearly important. Interstates are a eye-catching but muted magenta and a little thinner than the corridors, with the major roads being a gray that’s even thinner, so not to draw from the most important map elements.

Beyond those major map elements, I am far more comfortable this time around with my usage of technical map requirements. I feel like I utilized my space more and properly balanced it. I also am far more comfortable with my bar scale. My only issue is that I failed to include the raster properties in my legend.

What I probably learned the most from doing this map over? The importance of making a plan before starting a map. I thought I was doing this by listing the requirements and noting why they were necessary, but I found myself wasting time on simple things like deciding what kind of a halo was necessary, what colors to use, and which cities were major cities. If I had taken the time to puzzle these all out before I started on the map, I wouldn’t have wasted so much time in ArcMap. Next map I make, there will definitely be a plan drawn up before I enter ArcMap.

So, what do we think? Improvement?