Digital Mapping
yyyyy10086
Week9Lecture2FastFoodandChoropleth.pptxComing up…
Lab #8 (Was due by the end of today)
Lab #9 – Will be due by the end of Tuesday (I’ll be around Monday for help if you need it)
4/2 and 4/4 Tuesday and Thursday – NO CLASS (Conference)
Thursday 4/11 – Lab #10 (Also Social Explorer Application from Lab #9) and Extra Credit Lab (posted by tonight)
Topics include:
Different types of maps and data visualizations
Communicating with numbers
How do you rock the crowd
Preparation for take home final
Last week of class
(Tuesday = Review and Release of Exam)
(Thursday = Lecture will be a drop in session – come to this class to ask questions)
(Friday by 5pm = Exam Due)
Last Time
Quantitative Literacy – Identifying and understanding pattern, trends, and relationships
Math (like maps) representing narrow slice of the world with purpose
Data… Collected Observations… Spatial Data… Have (x,y)/Lat Long
Spatial Analysis – Where is something? Why is it there?
Clustering
Size/Geographic Extent
Last Time
Fast Food and Spatial Analysis
In and Out vs McDonalds (clustering/scale/size/geographic extent)
Whole Foods vs. Walmart (clustering/scale/size/geographic extent)
Choropleth Maps and Density in Social Explorer
Walmart Locations (markets share)
What data do you need to make this map?
How might you collect it?
How are data represented on this map?
What scale are we working at?
Spatial Analysis?
Clustering, Size, Movement?
What other maps would be useful if we wanted spatially analyze Walmart (could be anything)
4
How are data represented for WF?
Which visualization is better?
Tell a story about these two maps?
Did they meet on Tinder?
What can we say about the location of WF?
Clustering? Scale?
Who would this information be valuable to?
What decisions would you make based on
Them?
Why do fast food locations cluster?
Location Selection for Fast Food
Visibility (Traffic Patterns)
Parking (Urban vs. Rural)
Lot Size (Trader Joes)
Crime Rates (Will people feel comfortable going there)
Location of Competitors
Accessibility (easy to reach)
Affordability (how much does the space cost per month)
Safety (on site)
1854 Broad street Cholera Outbreak on Broad Street (London)
Cholera – Contracted through drinking infected water
Pre-Germ Theory (1860’s)
Location Analysis
Water pumps?
8
8
8
8
Example: Dr. John Snow (1813-1858), a legendary figure in the history of public health, epidemiology and anesthesiology created one of the first uses of geographical analysis on a static map to solve a problem of stopping the spread of cholera through Soho, London, England.
8
In and Out vs. McDonalds
Tobler's Law of Geography
“Everything is related to everything else, but near things are more related than distant things.”
12
12
12
Movement (over time)
History of Excel
Lotus 123 dominated in early 80s
Goal is to make calculations user friendly
Think Productivity, easy of use, speed
Something an average person could use
Late 80’s packaging of office (suite) – really big
1995 – 32 -64 windows 95 – a PC could run more than one program at once!
Fundamental principle – efficiency (accomplish in short steps)
Now anyone (including you) can use excel and make a chart and seem smart!
Everyone needs to crunch data – make decisions
Data Promises and Controlling the World Dreams
Promise of truth telling through objectivity
Make a complex and intimidating world stable
Numbers can be used to make demands
Like putting phd on your website (flat earth)
Principles of Choropleth Mapping…
Choro = Color
Aggregated – Entire unit= one value
Lighter is less
Darker is more
One Color!
Classes and Class Breaks
Density
Mass per unit of value
Study participants per square meter
Are values(observation) close together in one place
Or far apart in many places
Problems with choropleth maps
MAUP
Modifiable Areal Unit Problem
“MAUP refers to the fact that the observed aggregated values will vary according to how we draw our area boundaries”
Ecological Fallacy
Confusion between individuals and groups
Classification
What kind of argument do you want to make?
Manipulate your audience please…
Equal Interval vs. Quantile in Lab
Which Classification should I use?
Each category is a color bucket
What is the size/range of your buckets?
Will your observations be evenly distributed into your buckets – or will you put more observations in some buckets than others?
Do you want your buckets to be different sizes (range of values) and filled equally (number of values in each bucket)?
Do you want all of your buckets to be the same size (equal intervals) but filled differently (number of values in each bucket)
Your task as cartographer
Determine meaningful buckets for your data
What kind of argument do you want to make?
Manipulate your audience please
In Class Assignment (they are slightly out of order because I took one home by accident)
Tell a story about this map…
