Module 7: Choropleth and Proportional Symbols

This week we were learning about creating choropleth maps, graduated symbols, and proportional symbols. In this lab we were to use ArcMap to create 3 maps on one page. First, a choropleth map of population densities of countries in Europe along with either graduated or proportional symbols showing the wine consumption per capita in European countries. The second map was another map of Europe showing the number of females per total population, and the third was a European map showing the number of males per total population. In addition, of course, we were to add the essential map elements. Below is my map.

For these maps, the quantile classification method seemed to work the best, as it distributes a set of values into groups that contain an equal set of values, which works well here. I used a light to dark purple color scheme, with lighter colors showing lower values and darker colors showing higher values of population density. I like this color scheme as it shows the data clearly without being too bright and distracting. I used circular graduated symbols for the wine consumption data, and I felt that 5 classes here shows the data effectively. The symbols are a color that is easy to read and also allows the underlying population density map to be easily seen. I see that the countries with the most wine consumption tend to be in central and southern Europe and the countries with the least are in eastern Europe. The countries with the lowest population densities seem to be those with cold climates (Russia and the Nordic countries).
The gender per population maps were also created using the quantile classification scheme. This shows a high percentage of females in countries such as Russia and a high percentage of males in the Nordic countries and Iceland. Most other countries are relatively balanced. Looking at the two gender ratio maps side by side, one sees that one is nearly the inverse of the other, which makes sense, as these are percent per total population.

I enjoyed learning about choropleth maps as they are seen everywhere, and it was interesting to learn how they are used and misused. I also gained an appreciation for the use of graduated and proportional symbols on maps.

Module 6 - Projections Part 2 / Data Search

In this week's lab, our objectives were to explore and download different types of files, including aerial photographs, topographic maps, shapefiles, and tabular data, for use with ArcMap. Additionally, these were in different coordinate systems, so one major objective of this lab was to reproject the data into one coordinate system. Our final product was to be a map of petroleum tanks in Florida's Storage Tank and Petroleum Contamination/Cleanup Monitoring (STCM) network.

I learned quite a bit this week, especially how to use aerials and tabular data in the ArcMap environment. Finding and downloading the data was rather straightforward, even though the website (Labins.org) wasn't too clear as far as which quadrangles were adjacent to each other. In ArcMap, I added the aerial data first, as this is the coordinate system in which we wanted all our data. I then added all the other layers I wanted, and reprojected them into the desired coordinate system using the data management tools in ArcMap. After adding the tabular data and reprojecting it into our state plane coordinate system, what was left was "Owning our Map." This was the section I had the most trouble with honestly. I struggled with the raster files and manipulating their size and extent, but I think that will come with working more with ArcMap. One thing I did to make it a bit easier was to create a mosaic raster, which allowed me to manipulate the raster files a little easier.

Below is an image of my map. I used petroleum tank symbology and I decided to use different colors to show the status of the tanks in my two quads. I used brighter colors so they would stand out on my map. I also placed an inset map and highlighted where my two quads were in Escambia County. I have a scale bar both on the map and the inset, as the scales are different. I considered placing a halo effect around the major road names that I labeled, but I thought it would be distracting attention away from what I was supposed to be showing, namely, the STCM sites.

I enjoyed working with the different types of data and reprojections in this lab. I think having this knowledge will help me in labs to come.

Module 6 - Data Classification

In this week's lab, we learned about different methods of data classification and when each is used to best represent data. One major objective for this week was to learn how to use ArcGIS (ArcMap) to create maps using these classification techniques, and to compare and contrast the various techniques. The most difficult part of this assignment for me was determining when a specific classification technique is better than another for a particular set of data, but I think a lot of that probably comes from experience.

The map below shows the percentage of people over age 65 in Escambia County using four classification methods: natural breaks, equal interval, quantile, and standard deviation. The entirety of this lab was done using ArcMap. I was able to get all 4 data frames on one map here with some helpful hints from the online lecture video. Getting all 4 frames on one map is very useful for comparing and contrasting the different techniques. I found the process of creating the different symbologies very easy to do ... the hardest part for me was deciding what color scheme represented the data the best.

I think all the methods do a reasonably good job of representing this particular set of data well. I like the standard deviation and the equal interval methods the best here. The standard deviation method clearly shows where the lowest and highest percentages of people over 65 are (they are more than 2.5 standard deviations from the mean in either direction). I know I have to be careful using this method however, as it only is effective with normally distributed data. If I want to know the numbers, I like the look of the equal interval method in this case. I think it shows the minimum and maximum values the best when compared to the surrounding census tracts, and is easy for the user to interpret.

Module 5 - Projections Part I

This week in lab, we were learning about projected coordinate systems, which are map projections that use mathematical formulas to relate spherical coordinates to 2-dimensional planar coordinates. We were first provided with data showing a map of the counties of Florida in Albers equal-area conic projection, and we wanted to display this data in the Albers and two other coordinate systems. We used the project tool in ArcMap to do this. Found in ArcToolbox --> Data Management Tools --> Projections and Transformations, the "project" tool reprojects a starting data layer into a different coordinate system (the original layer is not lost). Using the project tool, we created the map of Florida counties in a total of 3 coordinate systems: the original Albers projection, a UTM projection, and a state plane coordinate system. Each of these was placed in its own data frame, so we could display all three at once on our map.
We created another data layer out of 4 selected counties within Florida, and created another value showing the geographic area of those counties (for each data frame). We then can see how the area for each county varies depending on which coordinate system is used. This is due to distortion that comes from projecting a three dimensional object into a two dimensional representation. We wanted to display this and "own our map", and mine is below.

First, I wanted to center and label the three coordinate system figures on my map. I made sure that the scale of my three figures were the same so that I could use the same scale bar for all three. In my legend, I show the 4 selected counties and the areas in square miles so one can see at a glance the difference in area between projections. We were asked to create a table showing the difference in area for different coordinate systems, so I created one in Excel and copied and pasted it to my map. I placed a caption to explain to the end user a little about what they were looking that, although I tried to make it clear with the title as well. After that, I placed my essential map elements.

The main thing I took from this assignment is the importance of choosing a proper projection based on the geographic location and the extent of the area that I'm interested in.

Module 5 - Spatial Statistics

For this module we were to take an ESRI online course on spatial statistics. We had temperature data and a basemap of western Europe provided from the National Climatic Data Center. Our objective was to use spatial statistics using the ESRI learning course to determine where freeze warnings should be issued. During the course of the exercise, we examined our data using various spatial statistical techniques, including mean center, median center, and directional distribution. Mean center identifies the average X and Y value of all our data values, where the median center is the point at which the Euclidean distance between all points is at a minimum. When these two points are at the same location, the data is said to be normally distributed. We also looked at directional distribution in this exercise. This tool creates standard deviational ellipses that show the spatial characteristics of features, such as central tendency, dispersion, and directional trends (ArcMap).

This map shows an analysis of spatial statistics of western Europe weather monitoring stations and focuses on temperature data. The median center is the red triangle and the mean center is the blue square. They are geographically near each other, so the data is relatively normal in distribution. The directional distribution shows a generally west to east trend (WSW to ENE). I then added essential map elements to this map and the final result is seen above.
After this section, we also learned about histograms, normal QQ plots, Vernoi charts, semivariograms, and trend analysis.
I think this was a very good exercise to not only learn about spatial statistics in general, but also in how we can use these tools within ArcMap to gain valuable information about our data.

Module 4: Map Elements and Typography

In this lab, our assignment was to create a map of Marathon, Florida using CorelDraw.

The benefit I gained from using CorelDraw exclusively for this lab was the opportunity to learn new features of the program and to gain a better understanding of features I didn't quite get the hang of last time. We loaded a blank map of the region as a *.ai file and saved it as a *.cdr file; only the physical features were there, our task was to label the map properly.

This is a map of Marathon, Florida and the surrounding area. I labeled the features using the text box and the line feature to point to areas as needed. I labeled the cities with a standard point symbol as is seen on many maps. I used a tent symbol to symbolize the state park, an airplane symbol for the airport, and a man swinging a golf club for the country club. I found all three symbols in CorelDraw when looking at different fonts for text (ESRI symbols, MapSheets, etc). I appreciated this because I found it much easier than I think it would have been to find and insert images from online. I bolded the cities so they are not confused with other features. I used the drop shadow feature on the names of the Keys labels, and I think that brings a bit of style to the map. I used the text on a path feature for the two larger bodies of water; although we weren't assigned to label those two, I didn't like the empty space at the top, and I thought it was reasonable to label those two features.

The main issue I had was with the neatline. I would have preferred my map to be all one color, but I'm not sure how to make that work and still show the neatline, so I displayed it as seen above. The map and everything related to the map itself are within the area with the blue background, where the other map essentials are arranged on the outer border. I enjoyed making this map, and although I'm still not really that comfortable with CorelDraw, I'm much more so than I was before.

Module 4 -- ArcGIS Online and Map Packages

In this lab we learned about ArcGIS Online and creating and uploading map packages. Prior to this, I had some experience uploading to ArcGIS Online through another course, but not with map packages. We learned the differences between Map Packages and Tile Packages, and when to use which.

One aspect of this lab that I found interesting was having different layer groups displayed at different extents of the map. We had one group layer that we set to not display if you zoom too close and another that we set to not display if you zoomed too far out. I think this can be very useful if you have a lot of data layers that you want to display at different distances. Also of interest to me was the creation of a map package with only layers relevant to the end user, and then uploading it to ArcGIS Online where I can choose which group or groups to share the end product with. Below are two screenshots of the map packages after they were uploaded to ArcGIS Online.