Singapore University of Social Sciences

Geospatial Analytics for Decision-Making

Geospatial Analytics for Decision-Making (LOG363)

Applications Open: 01 October 2021

Applications Close: 15 December 2021

Next Available Intake: January 2022

Course Types: Modular Undergraduate Course

Language: English

Duration: 6 months

Fees: To be confirmed

Area of Interest: Business Administration

Schemes: Lifelong Learning Credit (L2C)

Funding: To be confirmed

School/Department: School of Business


Synopsis

The amount of data being handled by managers is rapidly increasing. Data is commonly analysed and presented using graphs, charts, trends, and lists. Geospatial analytics provides a new data perspective by illustrating the relationship between the data and its location in physical space. Maps with spatial data offer valuable insights that can be used by managers for better decision-making and communication between peers and customers. LOG363 Geospatial Analytics for Decision-Making aims to equip students with knowledge on principles and methods of Geographic Information Systems (GIS) using QGIS open-source software. The course investigates the processes of manipulation, analysis, presentation and output of geographical data in a GIS. It provides opportunities for the development of problem-solving, decision-making and digital skills. Students will acquire these skills through hands-on exercises and data application.

Level: 3
Credit Units: 5
Presentation Pattern: Every January

Topics

  • Geographic Information System (GIS) and Geospatial Analytics
  • Applications of Geospatial Analytics
  • Map Projection and Coordinate Reference Systems
  • Cartography
  • GIS Digital Data
  • Spatial Representation of Data
  • Vector Data Geometry and Attributes
  • Vector Data Usage and Issues
  • Georeferencing
  • Topology Errors, Tools and Interpretation
  • Industry Applications of Geospatial Analytics
  • Challenges and the Future of Geospatial Analytics

Learning Outcome

  • Interpret concepts related to geospatial analytics for decision-making.
  • Inspect coordinate reference system for mapping the data.
  • Prepare data for geospatial analysis and decision-making.
  • Discuss the relevance of vector data in geospatial analytics.
  • Set up data for georeferencing and topology analysis.
  • Indicate the relevance and challenges of different spatial analyses.
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