GEOG 379 Lecture Notes - Lecture 16: Unmanned Aerial Vehicle, Openstreetmap, Waze
5 May 2018
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GEOG 379 Lecture Notes
Week 16
4/30 – Big Data and CyberGIS
Big Data
• Data sets so large or complex that traditional programs are inadequate
• Three Vs of Big Data –
o Variety
o Velocity
o Volume
Big Data Attributes
• Volume –
o Correlation, Optimization
o Mapping current check-ins
o – Interpolating crowd-sourced data
• Velocity –
o Real-time monitoring of moving objects
o Real-time map of all smart phones
o Real-time map of tweets related to disasters
• Variety –
o Fusion of multiple data sources
o Map of post-disaster situation on the ground
Spatial Big Data Examples
• Point data: Check-ins
• Line data: GPS-tracks from smart phones
• Raster data: Unmanned aerial vehicle (UAV)/Wide area motion imagery (WAMI) Video
• Graph: Temporally detailed roadmaps, Waze, Open Street Map
Big Data vs Spatial Big Data
• Big data questions –
o What are (previously unknown) side-effects of FDA approved medicines?
• Spatial Big Data questions –
o What are hotspots of spring-break vacationers today?
o What are critical places with many smart phone users in the last hour?
o Are there any hotspots of recent disaster-related tweets?
o Are there traffic congestion areas reported by Waze?
Applications of Spatial Big Data
• Climate Change: availability of tremendous amounts of climate and ecosystem data
o Global Climate Models (GCM) data
• Next-Generation Routing Services: GPS trace data, engine measurements, and temporally-
detailed roadmaps
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