Module 10: Dot Mapping

The objective of this week's lab was to explore the concept of dot mapping in which each dot represents a certain amount of some phenomenon. The resulting map shows the 2010 population in South Florida. To create this map, I used ArcGIS Pro and data provided by UWF. I joined an Excel table of 2010 US census population data to a feature class of the South Florida counties and applied Dot Density Symbology. In order to exclude surface water areas from the dot density map, I applied a masking effect using a surface water feature class. To more accurately display the dot density in the areas outside the surface water, I clipped the county population with an urban land feature class. I included and labeled 4 major cities to provide geographic reference to the map. In addition, I uniquely symbolized the surface water by type. I then adjusted the dot size and dot value to find suitable values where the densest areas are just beginning to coalesce. In order to create the visual legend, I created mock data in a new map by creating a new feature class with 3 squares on a grid scaled to the dot map layout scale. I then added a field to the attribute table and used low, medium, and high values corresponding to the population data in Excel. I then applied the same population dot symbology to the new feature class. I used the snipping tool to create .png images of the squares, added them to the layout as pictures, and scaled them appropriately to the map. I drew rectangles around the images, grouped them, and added labels. 

Comments

Post a Comment

Popular posts from this blog

Module 2: Coordinate Systems

Image
In this week's lab I explore different coordinate systems and projections in order to better understand the nature of distortions introduced by the systems. For the last part of the lab, I was tasked with selecting a state in the contiguous US and selecting an appropriate projection for the area. I selected the state of Wyoming as my area of interest. Wyoming has 4 State Plane zones and two UTM zones, so neither a single State Plane nor UTM system would work for this area without distorting the size or shape of the state. Therefore, the best coordinate system for this area is Custom Coordinate system. I chose NAD 1983 WyLam (Meters), a custom system specifically for the state of Wyoming, as the projected coordinate system. This coordinate system is a Lambert secant-case normal-aspect conic type projection which preserves shape and is appropriate for a general reference map. The standard parallels are placed at 41N and 45N, the boundaries of the state of Wyoming, which minimizes
Read more

Module 6: Proportional Symbol and Bivariate Choropleth Mapping

Image
The objectives of this week's lab was to explore proportional symbol and bivariate choropleth mapping techniques, as well as customizing legends for each technique. One of the data sets for this lab included positive and negative values. The final map utilizes proportional symbols to show both positive and negative values. This map is essentially two proportional symbol maps overlaid on each other, one for positive job growth and another for negative job growth, with the symbols for both variables sized the same. Utilizing proportional symbols to show both positive and negative values is an effective way to visualize areas that show the greatest and lowest values. These areas are easy to see quickly on the map and give the map reader a simple way to visualize the variable being mapped. Fig 1. Proportional symbol map using positive and negative values.  Another data set for this lab examined contained two data variables: percent of the US population in each state that is obe
Read more

Module 4: Color Concepts & Choropleth Mapping

Image
In this week's lab, I explored using color and selecting color ramps in ColorBrewer, as well as applying these concepts to create meaningful choropleth maps. I created a map of population change from 2010 to 2014 in Georgia counties. I normalized the data and produced a choropleth map of population change using a diverging color scheme with 6 classes divided around a midpoint of 0. Fig 1. Choropleth map of population change in Georgia counties using a diverging color scheme. For the Georgia population data set, I chose to divide the data set into 6 classes around a midpoint of 0: 3 showing a decrease in population and 3 showing an increase in the population. The classes were grouped based on a manual classification closely based on the Natural Break classification, where the midpoint was adjusted to 0 with the other groups unchanged. Natural Breaks classification creates classes based on similarities in values in the data, thereby revealing patterns in the data. By adjust
Read more