Module 7 - Choropleths

This week I created choropleths for the cartography lab. Everyone has seen a map like this but I doubt anyone actually knows what they are called, except for cartographers and other GIS nerds. At first glance choropleths seem simple and appealing to look at, at least in my opinion, but when you start working on one you realize just how complicated they can be. The most interesting facet for me was how easy it can be to lie using one of these maps. Using the right groupings or minor differentiation in color can hide all types of details that people might want to know and map makers can be real tricksters by using different methods of classification on one map. While creating the map graphic I also accepted the fact that statistics and I will become best friends much sooner than later.

My map for the week shows several population statistics for European countries including wine consumption. I utilized multiple layers in ArcMap to symbolize the same shapefile in several different ways. The large map shows population density and wine consumption rates. The population density is classified by quantiles and the wine consumption is classified by natural breaks. The female and male percentages by country are classified using natural breaks as well. All of the classifying was done within the Symbolgy Tab of the Properties for each shapefile. I viewed different methods for classifying the data including standard deviation, equal interval, manual in addition to the methods pictured. I also explored the difference between graduated and proportional symbols for the wine consumption icons but decided on graduated symbols as the display for classified data was easier to understand. 

Choosing color schemes was a whole different project for this lab. For me, sequential color schemes are difficult to differentiate no matter the hue. The various shades of color also made it difficult to find an appropriate background color. I even tried to set the page background to black and use white text in hopes that it would help me differentiate the lighter shades on the graphic but it was not successful so I reverted back to the white page. Every week I experience more of the tiny details that go in to making a map and I can say that choosing colors and fonts are becoming some of the most time consuming parts.

Module 6- Data Classification

This week was a little simpler than some of the weeks as the lab was centered on classifying data rather than learning graphic design software. We took another trip down memory lane and looked at statistics again. This time the focus was on determining the best way to classify a particular data so it could be accurately represented and easily understood by a map reader. The maps below show different classification methods for census data in Escambia County, Florida.

To create this graphic I used ArcMap and worked with the same shapefile in four separate layers. Each layer was classified by Quantities using Graduated Colors within the Properties of the shapefile. All of the classification methods depicted in the graphic are available as options in a drop-down menu with several other options not shown in the graphic. As for the color choice, at first I was unhappy with every choice of color ramp in ArcMap because the distinction between boundaries was a little unclear. Finally after choosing a darker color ramp and changing the outline to a light gray I think it turned out alright. The other thing I had to be careful with this week was the scale bar because there were so many different maps on one page. Before adding the scale bar I adjusted each map to a 1:800,000 scale in order to get a scale bar with numbers that were easy to work with.

*As side note, I even though I had my arguments with CorelDraw7 over the last few weeks, I decided it was the easiest way to add the text paths I needed for my graphic in Intro2GIS this week.

Week 6- Reprojections and Excel Data

We dove deeper into projections and reprojections this week and then topped off the lab with importing spatially defined Excel spreadsheets into ArcGIS. At first this week was a little overwhelming with all of the information from the lecture and ESRI course but it began to come together with the lab work.

Before any reprojection occured we started with downloading data from labins.org. Fortunately the page before you enter the FTP site provides the necessary spatial metadata for the files you want to download. We downloaded aerial images (some are used in the graphic below) and had to define the spatial references in ArcGIS using the metadata provided by LABINS. It sounded complicated when reading the directions but is actually a pretty simple process. I wish everyone that created and shared shapefiles learned this information because it would be really helpful when sharing data.

Then we downloaded more data from the FDGL website. That site contains a bunch of useful metadata for each of the files you want to download and it lists the original publisher. Most of the files I retrieved from the site were reprojected at some point during the lab at least once. Since there are times when you have to create you own files from data you collect we also learned how to import spreadsheets into ArcGIS. Aside from just importing the data we also used formulas to add decimal degrees to the spreadsheets in addition to the degree minute seconds coordinates that were originally listed. I think this is a very useful tool since decimal degrees are easier to format than the traditional degree minute second format.

The graphic I included this week shows eight aerial images and several shapefiles all projected in NAD 1983 State Plane Florida North FIPS 0903 with measurement units in feet. As for the graphic I decided to try shades of red this week because of the color of the images. I realized the county lines should be a little bolder but the graphic looked a little different while working on it than it does in the final JPEG. Otherwise I am pretty satisfied with how it turned out. I have to admit I did some of the graphic editing (a lot of text placement) using CorelDraw7, not just the layout editor in ArcMap. I made sure to group the images and scale bar to ensure the proper ratio was maintained.  

Module 5 - Spatial Statistics

Whoever thought statistics was fun was wrong. Fortunately ESRI made a set a spatial analyst tools for ArcMap that makes the work a little easier. In Module 5 for Cartography we took a look at spatial statistical analysis. I remember taking statistics. I remember thinking how useful statistics could be and how excited I was to learn to apply some of that math to may day job as an analyst. I also remember how overwhelmed I got at the end of the class and how I wished statistics never went beyond the point of standard deviation and normal distribution. Fast forward to today and now I'm back to thinking how cool statistics can be because the tools we learned about this week made the work much easier.

For our lab we followed an ESRI course (Exploring Spatial Patterns in Your Data Using ArcGIS) and spatially analyzed some of the attributes of a vector point file. For the graphic below we looked at weather stations in Western Europe and the temperatures they reported. The graphic simply displays the locations of the weather stations, the mean location, the median location, and the directional distribution of the locations. The great part is that I did not have to do any of the math behind the scenes to create the graphic because the Spatial Statistics Tools and the Geostatistical Analyst Toolbar did all of the hard work for me.

The Spatial Statistics Tools made finding the mean, median, and directional distribution of the weather stations easy because it was all done with the click of a button. Simply pick the tool you want to use, input the file you want to analyze, and click okay. The tool will process all of the data and create a new file displaying the statistic you chose.

What's not pictured in the graphic above is all of the other statistical analysis that the software can do. Using the  Geostatistical Analyst Toolbar I created a histogram, a normal qq plot, a voronoi map, a semivariogram/covariance cloud, a crosscovariance cloud, and a 3D trend line. My two favorite tools from the week were the histogram and the voronoi map. The histogram was something I easily recognized and am comfortable using and the voronoi map was really interesting. The polygon and color distribution of the voronoi map was much more intuitive for me than looking at a bunch of numbers and I think it will be a useful tool when trying to create graphics to explain statistic that I have to analyze.

Week 5- Projections

This week in Intro2GIS our focus was map projections. Along with learning about the different map projections we also saw how important metadata can be, specifically spatial references. In ArcMap we explored re-projecting vector and raster files as well as adding spatial references to files that were missing them. I have heard that missing or incomplete metadata was a huge problem but after this week I can certainly see why. How can you analyze data accurately if you don't know if the point file you are looking at is actually overlayed on a map or image with the same projection?

The process of re-projecting a file in ArcMap was pretty simple using the tools available in the ArcToolbox since we were given the coordinate systems to utilize. Doing this on my own without a lab guide would have taken a little more research to make sure I was picking the correct type of projection for the region and data I was trying to display. The graphic below is my final product for this week. It compares the areas of several counties in Florida and was based on one polygon vector file projected three different ways. It was really interesting to see how different the measurements can be simply by using different projections. After looking at the completed graphic I was happy to see that projection most commonly used by state and local governments (State Plane N) is also the one that measured the smallest areas. Hopefully that means less property taxes for everyone!

Week 4- ArcGIS Online

Our lab this week in Intro2GIS included a little ESRI online training to introduce us to ArcGIS Online. My previous GIS experience was all on a classified network and one of the first functions we disabled was ArcGIS online. After going through the ESRI training I can say we really missed out by not being able to use the ArcGIS Online function. It was neat to see all of the data that is already shared publicly and it was even better to see how a company could create a user group to share information within the company.

The first task was to modify a map package and the second task was to create and optimize a map package. Both packages were saved on ArcGIS Online and shared publicly. I'm not sure either of these packages are of much value to someone searching through all the data that is available but the skills we learned are very useful. I think this could also be a great tool for collaborative group projects because the files can be saved and protected or they can be editable. The two screenshots below are pictures of both of the map packages I created this week.

Module 4-Typography

This week was another adventure with CorelDraw7 but include a hard lesson in the value of different fonts as the main focus was typography. I call it an adventure because it really tests my patience until I am practically done with the project and then there is an ah-ha moment and I completely appreciate the software. The task this time around was to create a map of Marathon Key, Florida from a basic Adobe Illustrator file that contained the outline of the landmass.

 I struggled with the labeling for hours until I finally understood how to utilize the layers feature in Corel. After setting up different layers for water features, islands, the legend, essential map elements, and the map itself the project was much easier to complete. I turned off certain elements while editing others and used the visibility function when trying to select particular features that were difficult to click on.

Aside from just learning the software a little better, my favorite part of this exercise was creating my own little shape in order to depict the whole area of Curry Hammock State Park. I'm pretty proud of that green little polygon. I am no graphic designer but I truly do appreciate all of the work that goes into designing little maps on the back of pamphlets all the way through huge charts that take up a whole wall. This stuff is not easy.