This course introduces concepts, algorithms, programming, theory and design of spatial computing technologies such as global positioning systems (GPS), Google Maps, location-based services and geographic information systems. Learn how to collect, analyze, and visualize your own spatial datasets while avoiding common pitfalls and building better location-aware technologies.
From Google Maps to consumer global positioning system (GPS) devices, spatial technology shapes many lives in both ordinary and extraordinary ways. Thanks to spatial computing, a hiker in Yellowstone and a taxi driver in Manhattan can know precisely where they are, discover nearby points of interest and learn how to reach their destinations. Spatial computing technology is what powers the Foursquare check-in, the maps app on your smartphone, the devices used by scientists to track endangered species, the routing directions that help you get from point A to point B, the precision agriculture technology that is revolutionizing farming, and the augmented reality devices like Google Glass that may soon mediate our interaction with the real world.
This course introduces the fundamental ideas underlying spatial computing services, systems, and sciences. Topics covered will include the nature of geospatial information, proper statistical frameworks for working with geospatial data, key algorithms and data structures, spatial data mining, and cartography/geovisualization. We will also address applied topics such as where to find spatial data, how to use powerful open source software to analyze and map spatial data, and frameworks for building location-based services.