Dot Pop!

This weeks class focused on creating a "dot density" map. Essentially, it's a map that has a lot of little dots that represents certain data (in our case, one dot representing many, one-to-many). We had to create a map showing population density in South Florida. Each dot represents 5,000 people. The interesting part about dot mapping with one-to-many dots that they are randomly distributed and do not correspond to geographic points. Though I tried so hard to get the dots to only appear within urban areas, ArcGIS being the ever expensive glitchy  program it is, crashed repeatedly. So I had to make do with excluding the dots from the water layer.

I created this map entirely in ArcGIS, never using AI once (I know, I know, I can't believe it either. It's such a good looking map). The first step in creating any map is figuring out the base layers and the colors to use. I went with natural colors. A blue background (the sea) and a light green for the south Florida area. You'll notice a grayed out section of Florida to the north. This is the county layers from previous modules. I decided to include this layer to create continuity instead of making south Florida look like it had been hacked off and is floating in a nebulous space.It think it's quite clear that the green area is the area we're concerned with. For the water layer, I used a layer from a previous module as opposed to the one given to us. I did this because, the water layer you see is more refined and shows major water sources. The layer given to us for Module 10 was all water and instead of taking hours to clean up that layer, I took the easy route and just clipped this layer! ( I think it was from my Intro to GIS class). For the colors, a dark blue for the lakes and a lighter blue for the streams. As for the wetlands,I went with the ESRI wetland but removed the background color and changed the foreground color to blue. By removing the background color, it allows the wetland feaure to blend into the green of the county layer map. For the urban areas, I went with the color you see. I think it's easy to see on the map while not conflicting with the colors. Essentially, it's not jarring to the eye. I then included an insert map using a US State boundary shape file I had on my computer. Next was the cities. I went with the following cities because I felt they gave the best reference points on either coast. Originally, I was using the city picture to represent the cities on the map, however, when the dots were added, the cities became covered in red dots and it was hard to see not aesthetically pleasing. Instead, I went with the circle dot and turned it blue. It's easier to see when the dots were added. The dots, I decided to go with red. Red is easy to see against blue and green. Also, the red made the dots the most prominent feature.

For the dots, I tried to have them mask by the urban layer. However, every time I attempted to mask it to be only in the urban area, Arc crashed. I tried changing the ordering of the layers. I tried deleting everything and relayer it and masking it different times in different ways. But every time I selected the urban layer and try to mask the dots to only appear there, it crashed. So I had to settle with excluding the water layer. This then inspired me to write a summary about the map (something we've done on other maps in the class and in the intro to GIS course). I wanted to make it clear that the dots are not geographic points. (Not one to one dots). Originally, I went with dots that represented 15,000 people but I felt it wasn't accurate. Instead, I went with each dot representing 5,000 people.

Dot Density map of overall population in South Florida. As the disclaimer explains above, the dots are not geographic points. The map was created entirely in ArcGIS. 

Flowy Lines of Migrants

This week's lesson in cartography was in flow lines. Essentially, they're nice long, flowing lines with an arrow on one end. (In simplistic terms.) We were tasked with creating a flow line map that displays immigration by continent to the US. During this process I realized something, AI is not meant for maps. Thank god the file we were given already had the layers organized. Exporting an arc map to AI, creates such chaos on the layer front. I digress.

In making this map, I first considered how the lines would work. I decided to have all the lines run into each other. I did this to reduce clutter. I do regret, however, making each line a different color. Looking at it below, I feel it didn't quite come out the way I wanted. It's hard to see the Oceania line, for example. I then changed the color of each continent, except for the US. For the US, I changed the color to a red so it could stand out. Europe, sadly, looks washed out. (oh the pain of last minute work).  For the insert, I didn't go with an at scale. I blew up Hawaii and Alaska, though I kept their directionality. I made the legend in ArcGIS and then copied it over to AI.

I made a legend using the arrows and matching the arrows to the line width I figured out in the lab exercise (5pt being the maximum). I then put the respective number of immigrants next to each one.

I added drop shadows where I though would best show the lines and other information. Also, I like to keep things simple. I felt the large white border with the space to show my legend without a neatline, worked well. I felt my color choice on the map is also simple. The colors aren't too bright. I find the colors to be demur.

I like the central concept of flow lines, however, I'm I feel most stories can be told in better ways than with flow lines. They're thematic and can look compelling but also can clutter the map quite easily.

Europeans and Wine

This week we had to learn the basics of choropleh mapping and proportional symbology. This was building on our work with data classification (which sadly, I'm still wrapping my head around). The last two weeks saw me travelling about frustratingly building maps on my laptop while wedged into airplane seats in turbulent skies.,  Now that I'm settled again, I was really able to put some good work into this map.

To create the map, I starting in ArcGIS. I have it up and running on my pc, though that doesn't mean it's much faster compared to running it through the remote desktop. The first part I focused on was getting the choropleth right. This meant two things: 1) Determing the classification and 2) the color scheme. First, I tried to pick the best classification that best suited the population density. (For this part I picked random wildly different colors for each class so I could see it best). After re-reading the text and some google searches on the classification methods I boiled it down to equal interval and quantile. After classifying and reclassifying, I picked quantile. I felt it displayed population density the best. It's quite easy to determine which countries are most dense and least dense. (I did exclude a large set of outliers, mainly the small regions, statelets and countries. To ensure accuracy I excluded the same areas from the wine consumption data.) I'm assuming this map is meant for a more casual observer given the information so I wanted to be as easily understood as possible. I then selected the green color ramp and tweaked each color somewhat individually through their individual properties. I used colorbrewer but honestly, I'm at a lost at how to use it in arc. I found some information on scripting, but I was running out of time so I decided to use the colorbrewer as a guide as I tweaked the green colors.

Now the wine. For this part, I decided to go with the graduated symbology. I did this for two reasons. First, proportional wasn't displaying nicely on the map and second, the graduated symbols displayed nicely on the legend and was thus easier to understand. For this data, I selected equal interval classification because I felt it displayed better on the map and in the legend when compared to others. Again, I was concerned with how easy it is for the reader to determine the information. I changed the symbology from the default dot to a wine glass. I found this picture on google. In arc, I went to layer properties > symbology > graduated symbols > template > edit symbol. Here by going to type, I can go to "Picture Marker Symbol" it allows me to import the picture (png file) to use as a symbol. I then graduated it from 15 to 50. For the most part, it displayed nicely, though there was overlap in geographically close areas (i.e. the Balkans).  For the Balkans I created an insert map and added the same data from the main map. I then included the basics: legends, north arrow,and  scale.

After that I exported my arc map to AI. In adobe, I added the title and the description. I changed the background to be the pale blue which sat nicely behind the green color ramp. I then had to modify the legend. I was having this problem (which seems somewhat common) in which the symbols wasn't displaying correctly in the legend (or even in the layer bar on the left side in Arc). I had to build the legend from scrap by copy-pasting the wine glass symbol off the map into a rectangle then added the numerical data below each one. I liked the finished product, though I'm not happy where I placed it. I feel with the map, I left too much dead space in the upper left hand corner, but given the layers in AI, it was too cumbersome to re-position the map. I eliminated the glasses that were overlapping or covered too much of the country. For example, I used one symbol for Switzerland and France since they were the same size. I was happy for small countries that don't drink much wine, because it was easy fitting the symbol within the borders. For the insert I removed all the information from the Balkans area on the primary map and ensured that in the insert it was well displayed. I had to use leader lines to clean up the clutter. Over all, I was happy with the final product. I feel AI allowed me more freedom in creating a more polished map (albeit I find it more cumbersome than Arc).

Using choropeth for the population density and a graduated symbology for the wine consumption, we see where wine is consumed the most per capita. The most densely populated countries are the UK, Belgium and the Netherlands.