From GPS and Google Maps to Spatial Computing

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Free Online Course: From GPS and Google Maps to Spatial Computing provided by Coursera is a comprehensive online course, which lasts for 4-10 hours a week. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from Coursera. From GPS and Google Maps to Spatial Computing is taught by Brent Hecht and Shashi Shekhar.

Overview
  • 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.


    Three Ways to Enjoy this Course:

    This course is designed to support three different types of students and educational goals:

    Curiosity Track: Most of us interact with spatial technologies every day. This track is for students who wish to learn about one or two spatial computing topics, but not commit to an entire course. Curiosity track students are not interested in a certificate of accomplishment.

    Concepts Track: This track is for students who want to learn about spatial computing concepts in order to make informed choices, but who are not programmers and do not have extensive experience with statistical methods. For example, concepts track students will learn about Tobler’s First Law of geography and map projections, but will not delve into the quantifications of either. Students who complete the concepts track with sufficiently high scores will receive a Statement of Accomplishment.

    Technical Track: This track builds on the concepts track, but adds math and programming. For example, we will cover spatial statistical indicators like Moran’s I and Ripley’s K when discussing Tobler’s First Law and will have students calculate the distance between two points using two different coordinate systems and open-source APIs. Students who complete the technical track with sufficiently high scores will receive a Distinguished Statement of Accomplishment.

Syllabus
  • Topics Covered:
    Module 1 - Introductio
    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
    Spatializatio 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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