Urban Big Data Analytics

July 23, 2019

Instructor: Andy Hong, PhD
Lead Urban Health Scientist
The George Institute for Global Health
University of Oxford

Any quetions about Assignment 3?

• Help you get familiar with R coding
• If you are new to R, it will be difficult
• If you are new to coding, it will be extremely difficult
• Don't worry, we will cover it tomorrow
• Remember, coding is like talking to a computer

Spatial database

What are Spatial data?

• Data that have geographic information
• Coordinates, addresses, postal codes
• Spatial data are mulit-dimensional: x, y, z ...
• Long history: geography, forestry ...

Why spatial data?

• Locational data are valuable
• Satellites, mobile devices, drones, vehicles, etc.
• Tracking people movement
• Tracking goods movement
• Tracking animal movement
• Big companies: Google, Apple, Microsoft, Baidu, Uber, Didi

New York City Transit

15 Global Challenges

Four use cases

• Vegetation health
• Global fishing Watch
• Extreme weather events
• Terrorist incidents

Vegetation health

Global fishing watch

Extreme weather events

Terrorist incidents

Types of spatial data

Key elements

Projection! Projection! Projection!

• Most important information
• The earth is not flat
• If it's not correct, maps won't match
• Most maps have WGS84 projection

Spatial data files

• ArcGIS Shapefiles: *.shp
• Google map files: *.kml, *.kmz
• GeoJSON: spatial version of JSON (Javascript Object Notation)
• Text: Longitude (X), Latitutude (Y) information

Coordinates (points)

Joining data

• Need a common column
• Need to match data types
• Left join mostly, some times inner join, but hardly right join

Class 5 - Group session