Piece of Eden GIS Blog

 This week we explored choropleth and dot mapping. Choropleth is a thematic form of mapping that focuses on color units, whose color intensity is proportional to its corresponding data value. Dot mapping is also thematic. It uses either a proportional or graduated thematic symbol (like a circle), whose size increases due to its data value. Using ArcGIS pro, I analyzed the population densities of countries in Europe (person per square kilometer), as well as their wine consumption (liters per capita) to determine if there was a correlation between the two. In my choropleth map, I decided to use a natural breaks classification. I chose not to use Equal Interval because only 2 classes (with slight 3 rd class) were represented in the map, and it looked like almost just one color in the lower range. The standard deviation classification appeared to be more diverse at first glance but was actually skewed to the top ranges. I was then between Quantile and Natural Breaks. While both these maps

 This week we learned about the different map data classification methods: equal intervals, quantile, standard deviation, and natural breaks. Utilizing these different methods, I analyzed how these methods highlight and possible skew different aspects of data while also comparing these same methods to normalized data tracts by area.  1. Equal Interval: In this classification method, you divide your max value by your desired number of categories. When analyzing our data, this method causes a huge skew in the data where most all of the data landed in the first category. 2. Quantile: This method looks to create an equal number of observations within the number of desired categories. This method helped to display the data in the most diverse way possible. 3. Standard Deviation: This method uses the bell curve and standard deviation to create 5 categories with +/- .5, 1.5, >/< 1.5 standard deviation from the mean. This method helps to visually see how the data various from the mea

 This week we focused on enhancing elements and dulling out background information to focus on certain details you want to stand out. We implemented this thinking through the Gestalt Principles: visual hierarchy, contrast, balance, and screening.  To implement visual hierarchy I ranked th e importance of a symbol by color and size. I made the school symbols increase in size (Elementary < Middle < High) and color intensity. To achieve contrast,  I created graphic variety by making the streets in Ward7 bubble lines, the other major roads bright red/blue with labels, and other details light plain background colors. For screening, I wanted to create a figure-ground relationship by making  the schools a darker/brighter color than its surroundings. Lastly, I balanced out the map by  removing all but the basic outlining information for the area outside Ward 7 to reduce the busyness. I used light/pastel colors for the background information and brighter primary colors for the symbols to

In Module 2 of Cartography, we learned about map typography and different ways to properly use map elements to highlight land and water data. Utilizing point (cities), line (water ways), and polygon (swamps) data in Florida, I created the map below.  Figure 1: Map of large cities and waterways in Florida. Utilizing ArcGIS pro, I first deleted any data that I did not need from the attribute tables. I then converted each category's symbology from single to unique depending on their data's correct name. Now I was able to create labels for the data I needed. (I originally used the Labels SQL function to narrow down the labels to only those that I needed, but that resulted in a very cluttered legend at the end.) I played around with colors/fonts for each category and saved all my actions. I also changed the positioning of the labels for the rivers to 'river placement." I then converted the data category to annotation (i.e. Rivers). (I learned the hard way to make sure to ch