Course information
IS415 GeoSpatial Analytics and Applications
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Synopsis
In this globalising and competitive business environment, the value of location as a business measure is fast becoming an important consideration for organisation. GIS with its capability to capture, manage, display, and analyse business information spatially is emerging as a location intelligence tool.
This course provides students with an introduction to the concepts, principles and methods of geospatial analytics and their practical applications of geospatial analytics in real world operations. Emphasis will be placed on (i) locating, acquiring and integrating business data into geospatial data repository, (ii) understand the principles and methodologies of the geocoding process, (iii) become familiar with geovisualisation, spatial analysis and location modelling techniques, and (iv) explore the technologies and possibilities of server-based and/or web-based spatially enabled decision support systems.
Course Objectives
Upon completion of the course, students will be able to:
- Understand the basic concepts and theories of GIScience and geospatial analytics,
- Create and manage spatially-enabled real world data,
- Use appropriate geovisualisation and mapping techniques to analyse and visualise geographical data,
- Understand the basic concepts and methods of geocomputation and geospatial analytics,
- Use appropriate geospatial analysis methods in detecting, analysing and modelling geospatial patterns and relationships, and
- Design and implement spatially enabled geospatial analytics applications.
Competencies
- Explaining the concepts of and principles of Geospatial Analytics.
- Describing the differences between Geospatial Analytics and Geographic Information Systems (GIS).
- Importing, wrangling and transforming geographical data.
- Geocoding and georeferencing geographical data.
- Describing the basic principles and concepts of geographical data visualisation and thematic mapping design.
- Performing geoprocessing and spatial analysis for solving real world problems.
- Applying raster-based cartographic modelling for solving real world problems.
- Explaining the principles of spatial point patterns and providing accurate interpretation of spatial point patterns analysis results.
- Explaining the methods of area-based analysis and providing accurate interpretation of area-based analysis results.
- Explaining the methods of geographically weighted regression and providing accurate interpretation of the analysis results.
- Explaining the methods of spatial data mining and providing accurate interpretation of the analysis results.
- Designing geospatial application programmatically by using free and open source software and packages (i.e. R, R packages and R shinny).
