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From GPS and Google Maps to Spatial Computing

Course Summary

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


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    Course Syllabus

    Topics Covered:
    Module 1 - Introduction
    Course Introduction
    Defining Spatial Computing
    Course Structure
    Interviews with Johannes Schöning, Loren Terveen and Martin Raubal Module 2 - Spatial Query Languages What is a Query? Query Language?
    An example database with 3 tables
    SQL overview
    SELECT statement with 1 table
    Multi-table SELECT statement
    Why spatial extensions are needed
    1-table spatial queries
    Trends
    Module 3 - Spatial Networks Motivation, Societal use cases
    Example spatial networks
    Conceptual and mathematical models
    Need for SQL extensions
    CONNECT statement
    RECURSIVE statement
    Storage and data structures
    Algorithms for connectivity query
    Algorithms for shortest path
    Interviews with Dev Oliver and Betsy George Module 4 - Spatial Data Mining Motivation, Spatial Pattern Families
    Spatial data types and relationships
    Limitations of Traditional Statistics
    Location Prediction model
    Hotspots
    Spatial outliers
    Colocations and Co-occurrences
    Summary: What is special about mining spatial data? Module 5 - Volunteered Geographic Information (VGI) Introduction to Volunteered Geographic Information
    Producing VGI
    Pros and Cons of VGI
    Interview with Michael Goodchild Module 6 - Positioning Introduction to Positioning
    Overview of GPS
    Overview of Wifi and Cellular Positioning
    Introduction to Content-based Positioning
    Geoparsing
    Location-field Positioning Module 7 - Cartography Introduction to Cartography
    Overview of Maps and Mapping
    Reference Maps
    Thematic Maps
    Spatialization Module 8 - Future Directions Introduction
    Spatial Databases: Representative projects
    Data Mining: Representative projects
    Advances in Cartography
    Advances in Positioning
    Interviews with Vipin Kumar, Wan Bae, Mohammed Mokbel and Len Kne

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    Course Format

    Students in this course will learn through topical lectures as well as interviews with and guest lectures from academic and industry experts.


Course Fee:
Free

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

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