🎯 Learning Objectives
- Calculate Central Tendency (Mean Center, Median Center) of a point distribution.
- Perform Kernel Density Estimation (KDE) to visualize "Hot Spots" of disease.
- Use Directional Distribution (Standard Deviational Ellipse) to see if the outbreak is trending in a specific direction.
- Prove causality using proximity analysis (Buffer).
📂 Scenario: The Blue Death
It is 1854. People in Soho, London are dying of Cholera. The prevailing theory is "Miasma" (bad air). Dr. John Snow believes it is the water.
You have two datasets: The locations of deaths, and the locations of water pumps. Your job is to statistically prove that the Broad Street Pump is the killer.
lab10_john_snow.zip
Contains: Cholera_Deaths.shp, Pumps.shp, Soho_Streets.shp
🛠️ Step-by-Step Instructions
Select your preferred GIS platform to view instructions:
Mean Center
1. Open Geoprocessing > Mean Center.
2. Input: Cholera_Deaths.
3. Weight Field: Count (if aggregated) or None (if individual points).
4. Run. Does the center land near a pump?
Kernel Density (Heat Map)
1. Search for Kernel Density (Spatial Analyst).
2. Input: Cholera_Deaths.
3. Search Radius: try 50 Meters (we are looking at a neighborhood scale).
4. Run. Symbolize from Blue (Low) to Red (High).
Standard Deviational Ellipse
1. Search for Directional Distribution.
2. Input: Cholera_Deaths.
3. Size: 1 Standard Deviation.
4. Run. This shows the "core" area containing ~68% of deaths.
✅ Submission & Assessment
To complete this lab, you must submit:
- The Evidence Map: A layout showing the Heat Map, the Mean Center, and the labeled Broad Street Pump.
- The Verdict: A short paragraph explaining why the statistical evidence points to the pump (and not the air).
- Bonus: Identify the "Anomaly" - the brewery workers who didn't die. Why?