Data Classification

Data Classification Map 1

The first map of week three demonstrates the percentage of African Americans living in Escambia county.  By using the exact same data for each map, but different data classification, you can see how the data can visually change.

Data Classification Map 2

The second map of the week shows the Natural Breaks classification that I chose to best represent the data. I felt that the Natural Breaks classification represented the data better than the other classifications. Equal Intervals classification had large range values that contained values not included in the data. Standard Deviation classification was difficult to understand and data are positively skewed.  Quantile classification allows for data of the same range to be placed into different classes. Without examining the raw data, one could be misled by the placement of data elements.

As an additional note/self critique, I did not realize until I uploaded my maps to the blog, that I apparently forgot to install a map frame for both maps.  That stinks.

GIS & Cartography Lab

GISCarto Map 1

My first map this week, GISCarto Map 1, shows the states of Mexico by population.  It was unclear as to the time frame of the population data.  I used a small halo on the state names to make them pop a little more.  I converted the world country labels to text so that I could move United States out from under my title.

GISCarto Map 2

My second map this week, GISCarto Map 2, shows the most densely populated urban areas of central Mexico.  So that only the largest areas were labeled, I used advanced labeling to create a class called "millions' and then used a SQL query to only select the cities with a population greater than 1,000,000.

GISCarto Map 3

My third and final map this week, GISCarto Map 3, was something new for me.  This was my first time working with raster layers or elevations.  My daily interactions with ArcGIS only involve line and point features.  I used a stretched symbology to demonstrate the changes in elevation.  Notice the purple area indicate lower, at or below sea level, elevations and the darkest green indicate the tallest peaks. Something different I did with this map is that I chose to move the title above the map frame as opposed to within the map frame.

GIS3015 - Statistics

This week we learned about histograms and line graphs.  The graphic below illustrates the population growth and predicted population growth for the states of California, Florida, New York, and Texas from  1990-2025.   To create the graph, I selected, from the supplied data, the corresponding cells for each state, used the Insert menu to insert a scatter plot and then added a trendline while choosing to display the equation and the R-squared value.  So why is this graph useful?  Linear trendlines are a visual representation of a gradual increase in data point values.  Since Excel can create the equations needed, it enables us to use this same equation in predicting future values for a particular data set.

This lesson caused me to visit a part of my brain that I haven't been in for quite some time.  While I might do basic algebra on a regular basis, statistical equations are way out of my league. With a little more practice and a whole lot of Khan Academy videos, I just might figure it out.

GIS4043 - Own Your Map

I picked up some neat things this week. I learned about installing multiple data frames and inset maps to help give perspective to a map.  I also worked with clipping for the first time and learned some nifty keyboard shortcuts like Insert key to zoom world.  Now, if I can just remember to use them.

Below is my map for the week.  I think I owned it.

GIS3015 - Good Map, Bad Map

Good Map Example

The purpose of the map is to detail the location of the ECS Integrated Design Services in the Transportation Research building as was stated on the website.  From the onset, you can see that this map is pleasing to eye with no map-crap.  The location of the ECS Integrated Design Services building is presented in a contrasting color that does not fade into the existing data.  Labels are clear and easy to read.  The North arrow is present which would be important in this instance as this map is not oriented in true north.  These elements cover Tufteisms 1, 3, 4, 5, and 7 and commandment 4.   

http://design.ecs.psu.edu/2.0/Design/contact.html

Bad Map Example

This is an example of a bad map.  The map is heavily cluttered, there is no legend, and no data is visible.  There is no way for the map reader to understand what the map is trying to convey.

GIS4043 - ArcMap Overview

I work with ArcGIS on a daily basis, so the lab itself wasn't too difficult.  Keeping track of where to pull data from, where to save it to, how to submit it, etc has been completely overwhelming to say the least.  I am only hoping that I will eventually get this down and it will become second nature to me very soon.  I'm not an overly stressed person, but this past week has wreaked havoc on my nerves.

Something I learned from this lab:
Fit to margins.  For the past three years I've been dragging corners to get my maps to fit nicely into the printable space.

So, here is my first map.  I kept it pretty basic and to the point of the lab.