M6 Lab: Isarithmic Mapping

This weeks lab assignment centered around the the elements of Isarithmic maps. The goal was to create a continuous color fill symbol,  hypsometric tinting, and contour maps with an existing PRISM precipitation data raster data of Washington State. 

 Completing the lab assignment was easy and fairly straight forward by first creating a map with continuous colors then adding a hypometric tinting or layer tenting showing the differences in relief. Basically, it accentuated the changes in elevation enhancing the users ability to see concentration of perceptional when encouraging changes in elevation.

The next step in the lab evolved reclassifying the raster from floating point values ot integer values. Using the raster of integer values it was necessary to create contour lines using the same manual breaks, shown in the final map below.

M5 Lab: Choropleth Mapping

 The focus this week are choropleth maps. Choropleth maps are one of the more common thematic maps which shows a aggregated data for an area. The area, an enumeration unit, represents some geographic division like state, country, county, etc.  To solidify the lecture and further develop our cartography skills using ArcGIS Pro the lab assignment guided us with just enough instructions to create a map showing population per kilometer and wine consumption per capita for European countries.

The map I created utilizes a color scheme inspired by one of my favorite wines, Juggernaut Vineyards, Hillside Cabernet Sauvignon. The base color of this wines label made for a great graduated color to show the population density of each European Country. Then the contrasting turquoise color is ideal to for a graduated symbol showing the wine consumption.

The map also use data from World Bank Official Boundaries and the IHO Sea Area from marinerregion.org provided by the Flanders Marine Institute. These two datasets were used only for labeling and accurate background context.

Creating the gradient color schema was easy once selecting the lowest value. Then it was just a mater of creating breaks at specific percentages and adjusting the colors value. Adjusting the value is best using either the HSL or HSV format. 

Another skill show in this lab is data exclusion us an SQL statement. This method would show the feature on the map but the data population and/or wine consumption was excluded from the statistical analysis. This is a great way to ensure that outliers are not skewing the data.

 

Data Classification

The first few labs focused on the graphic design aspect of cartography now in Lab 4 the focus is gear towards spatially representing data by looking at some of the data classification options available in ArcGIS Pro. 

Similar to the lecture for this module let us start with the easier classification methods, equal interval and quantile.

• Equal interval classification is derived from dividing the range of values by the number of classifications. This is show in the map on the lower-right corner. Although this an easy to understand method it does not represent the density of seniors in Miami-Dade County effectively.
• Quantile interval places the equal number of values in each class. Which is calculated by dividing the number of observations, data points, by number of classes. One disadvantage to this method is tying classes. Since values should not be placed in more than one class it might be necessary to establish manual breaks. 
• Standard Deviation classification groups the values by adding or subtracting the datasets standard deviation. This method might be difficult for some map user to interpreter and is best reserved for when the data is normally distributed. 
• Natural Breaks is the final classification method explored. This method will group data which minimizes the difference between values but maximizes the difference between classes.
  

Presented are the maps which shows the density of senior population in Miami-Dade County. This is accomplished by normalizing the total senior population by the Census tract area. From the form options, it easy to see that the Quantile and Equal Interval do a poor job of representing this type of information. The Natural Breaks and Standard Deviation clearly represent the area of the County with the highest density of senior population. 

However if an effort was made to target seniors calculating the percentage of seniors in a specific area is effective, as show in the map document below. As you can see here the equal interval clearly indicates the areas with high senior population.

Building on the previous labs for this map I wanted to do somethings a bit different. Since the assignment expected four map's the clear design choice is to divide the document into four quarters. Yet that was a bit box for my taste and decided to place the titles, attribution, and scale in a center circular badge. The colors chossen are complimentary values to provide some contrast between the area of interest and surrounding features.

Enjoy!