Hispanic Population Cartogram


The purpose of this lab was to compare each states Hispanic population per square mile and adjusts the size of each state accordingly. Each population was compared to the average of the united states so big states have a surplus of Hispanics and small states have fewer than the average. You can easily see that California most likely has the largest Hispanic Population while places like North Dakota have the least. Maryland looks pretty close to normal size, maybe a bit bigger than it usually is. California, Texas and Florida have the most Hispanics per square mile. This map clearly shows each states Hispanic population in comparison to the national average per square mile and how certain states have the majority and many states have far fewer than they should.

Europe’s Waste per Houshold


The purpose of this lab was to understand how to use proportional symbols in ArcMap. I mostly struggled with the size of the symbol as in almost every version I made, the symbols were either massive and overlapping each other to the point that you could barely see the countries or they were way too small and the smaller ones could not be seen, I eventually settled on this one as it was the closest i could get to meeting halfway. With the version I chose, I think it best represents which countries are the problem countries and which ones should be viewed as a model for waste management.


Dot Density for Population in South Dakota


The purpose of this lab was to create a dot density map and the make a proper legend for it in Adobe Illustrator. I used 1 point dot size and i think that worked well since the dots in the highly dense areas are still able to be seen and any larger it would have been too thick. The areas of density closely resemble to those shown in the previous lab, with  the medium and high density areas are the same as the dark areas from the last lab. when assigning the values it is easy to make the dot value too low and over populate the map or to make it too high and have a largely empty map, so you need to experiment to find what value lands in between the two. In the areas of higher density it is very easy to see the county boundaries but the second you look at the areas of low density it is impossible to tell where the boundaries are.

Classification Method Test


The purpose of this lab was to indicate what each method of classification changed and which would be most appropriate for this specific occasion. The first two are poor classification methods for this instance since a majority of the counties fall into one category, this is due to the classifications place most into the lower categories. The bottom two are far better at conveying the information to the reader since there are more differences between counties. Most of these are placed into the higher categories thanks to these classifications. Quantile works best for this situation since more counties are represented in a more accurate and small range. Equal interval is the worst since most counties fall into the first category and not all categories are even used.

Text Lab


The purpose of this lab was to size and style the label of each major geographical location in a way that is coherent and legible. It was very easy to get all the text clustered up due to size and location but once I created a rules for how I styled it, it became much more clear. Font size and boldness differentiated state, city and water bodies. Looking back I might have made some of the towns bigger and tried to space them out more evenly.

Map Projection Experiment


The purpose of this lab was too experiment with map projections to determine which would be best for each scenario. I feel good about the projections I chose but I am sure there are other projections which would have been more appropriate that i just do not know of.