Week 6 - Data Classification

This week's lab highlighted the differences between various data classification schemes. The classification schemes we compared were Equal Interval, Quantile, Natural Breaks (Jenks), and Standard Deviation.

View of four different data classification schemes for the same dataset.

Technical Notes

The map is a compilation of four different inset maps arranged on a single page... and is very similar to what we created in lab last week. To make my inset maps stand out, I put a data frame around all of the map elements, then set the background to light brown (ArcGIS calls it 'Sand'). Each of the data frame backgrounds were then set to white so that they sort of pop off the page, so to speak.

I relied heavily on the guidelines for this exercise - not just to line up my individual data frames, but to also line up Escambia County, the legends, and each data frame title. Without them I'm pretty sure I wouldn't have been able to place everything with such precision by hand! 

Initially I had used a default color ramp (the Blue Green Bright ramp), but I was not satisfied with the results. So I went to ColorBrewer, and came up with what I think is a fairly decent multi-hue scheme of green. I did keep the default color ramp choice for the Standard Deviation map, but flipped the values so that my legend started at 'less than' and went down the line to 'greater than'.

Other Thoughts...

This week's lab was one of the quicker labs I've had in recent memory, however the concepts behind the map are definitely not something I'd want to rush. I personally think that the Standard Deviation map shows the variation in the data the best, although some good runners up would be either the Natural Breaks or the Equal Interval classification maps. One thing I'm fairly certain of is that the Quantile classification does not represent the data well, and in fact can be very misleading if one doesn't study that legend!